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1
Xu, Yuan, and Xiyuan Chen. "Online cubature Kalman filter Rauch–Tung–Striebel smoothing for indoor inertial navigation system/ultrawideband integrated pedestrian navigation." Proceedings of the Institution of Mechanical Engineers, Part I: Journal of Systems and Control Engineering 232, no. 4 (May 31, 2017): 390–98. http://dx.doi.org/10.1177/0959651817711627.
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Accurate position information of the pedestrians is required in many applications such as healthcare, entertainment industries, and military field. In this work, an online Cubature Kalman filter Rauch–Tung–Striebel smoothing algorithm for people’s location in indoor environment is proposed using inertial navigation system techniques with ultrawideband technology. In this algorithm, Cubature Kalman filter is employed to improve the filtering output accuracy; then, the Rauch–Tung–Striebel smoothing is used between the ultrawideband measurements updates; finally, the average value of the corrected inertial navigation system error estimation is output to compensate the inertial navigation system position error. Moreover, a real indoor test has been done for assessing the performance of the proposed model and algorithm. Test results show that the proposed model is able to reduce the sum of the absolute position error between the east direction and the north direction by about 32% compared with only the ultrawideband model, and the performance of the online Cubature Kalman filter Rauch–Tung–Striebel smoothing algorithm is slightly better than the off-line mode.
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Yang, Lan. "Fourier-Hermite Rauch-Tung-Striebel Smoothing Optimized Particle Filter." Journal of Information and Computational Science 12, no. 10 (July 1, 2015): 4031–46. http://dx.doi.org/10.12733/jics20106133.
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Goll, Stanislaw, and Elena Zakharova. "An active beacon-based leader vehicle tracking system." ACTA IMEKO 8, no. 4 (December 16, 2019): 33. http://dx.doi.org/10.21014/acta_imeko.v8i4.685.
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This article focuses on mobile robot convoying along a path travelled by a certain leader carrying the active ultrasonic beacon. The robot is equipped with the three-dimensional receiver array in order to receive both the ultrasonic wave and the RF wave marking the beginning of the measurement cycle. To increase measurement reliability, each receiver contains two independent measurement channels with automatic gain control. The distance measurements are pre-processed in order to identify the artefacts and then either remove them or replace them with the interpolated value. To estimate the position of the beacon in the robot’s local coordinate system, several methods are used, including the least squares method with subsequent exponential smoothing, the linear Kalman filter, the Rauch-Tung-Striebel smoother, the extended Kalman Filter, the unscented Kalman filter, and the particle filter. The experiments were undertaken in order to estimate the estimation method preferable for following the leader’s path.
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Nguyen, Tran, and Du Kim. "GLMB Tracker with Partial Smoothing." Sensors 19, no. 20 (October 12, 2019): 4419. http://dx.doi.org/10.3390/s19204419.
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In this paper, we introduce a tracking algorithm based on labeled Random Finite Sets (RFS) and Rauch–Tung–Striebel (RTS) smoother via a Generalized Labeled Multi-Bernoulli (GLMB) multi-scan estimator to track multiple objects in a wide range of tracking scenarios. In the forward filtering stage, we use the GLMB filter to generate a set of labels and the association history between labels and the measurements. In the trajectory-estimating stage, we apply a track management strategy to eliminate tracks with short lifespan compared to a threshold value. Subsequently, we apply the information of trajectories captured from the forward GLMB filtering stage to carry out standard forward filtering and RTS backward smoothing on each estimated trajectory. For the experiment, we implement the tracker with standard GLMB filter, the hybrid track-before-detect (TBD) GLMB filter, and the GLMB filter with objects spawning. The results show improvements in tracking performance for all implemented trackers given negligible extra computational effort compared to standard GLMB filters.
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Ali, Wasiq, Yaan Li, Zhe Chen, Muhammad Asif Zahoor Raja, Nauman Ahmed, and Xiao Chen. "Application of Spherical-Radial Cubature Bayesian Filtering and Smoothing in Bearings Only Passive Target Tracking." Entropy 21, no. 11 (November 7, 2019): 1088. http://dx.doi.org/10.3390/e21111088.
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In this paper, an application of spherical radial cubature Bayesian filtering and smoothing algorithms is presented to solve a typical underwater bearings only passive target tracking problem effectively. Generally, passive target tracking problems in the ocean environment are represented with the state-space model having linear system dynamics merged with nonlinear passive measurements, and the system is analyzed with nonlinear filtering algorithms. In the present scheme, an application of spherical radial cubature Bayesian filtering and smoothing is efficiently investigated for accurate state estimation of a far-field moving target in complex ocean environments. The nonlinear model of a Kalman filter based on a Spherical Radial Cubature Kalman Filter (SRCKF) and discrete-time Kalman smoother known as a Spherical Radial Cubature Rauch–Tung–Striebel (SRCRTS) smoother are applied for tracking the semi-curved and curved trajectory of a moving object. The worth of spherical radial cubature Bayesian filtering and smoothing algorithms is validated by comparing with a conventional Unscented Kalman Filter (UKF) and an Unscented Rauch–Tung–Striebel (URTS) smoother. Performance analysis of these techniques is performed for white Gaussian measured noise variations, which is a significant factor in passive target tracking, while the Bearings Only Tracking (BOT) technology is used for modeling of a passive target tracking framework. Simulations based experiments are executed for obtaining least Root Mean Square Error (RMSE) among a true and estimated position of a moving target at every time instant in Cartesian coordinates. Numerical results endorsed the validation of SRCKF and SRCRTS smoothers with better convergence and accuracy rates than that of UKF and URTS for each scenario of passive target tracking problem.
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Razali, Saifudin, Keigo Watanabe, Shoichi Maeyama, and Kiyotaka Izumi. "An Unscented Rauch-Tung-Striebel Smoother for a Vehicle Localization Problem." Journal of Advanced Computational Intelligence and Intelligent Informatics 15, no. 7 (September 20, 2011): 860–68. http://dx.doi.org/10.20965/jaciii.2011.p0860.
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The Unscented Kalman Filter (UKF) has become relatively a new technique used in a number of nonlinear estimation problems to overcome the limitation of Taylor series linearization. It uses a deterministic sampling approach known as sigma points to propagate nonlinear systems and has been discussed in many literature. However, a nonlinear smoothing problem has received less attention than the filtering problem. Therefore, in this article an unscented smoother based on Rauch-Tung-Striebel formis examined for discretetime dynamic systems. It has advantages available in unscented transformation over approximation by Taylor expansion as well as its benefit in derivative free. To show the effectiveness of the proposed method, the unscented smoother is implemented and evaluated through a vehicle localization problem.
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Gao, Zhouzheng, Lin Chen, Yu Min, Jie Lv, and You Li. "Evaluation on Nonholonomic Constraints and Rauch–Tung–Striebel Filter-Enhanced UWB/INS Integration." Mathematical Problems in Engineering 2020 (October 13, 2020): 1–14. http://dx.doi.org/10.1155/2020/7274181.
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Precise and seamless positioning is becoming a basic requirement for the Internet of Things (IoT). However, there is a gap for precise positioning in Global Navigation Satellite System- (GNSS-) denied indoor areas. Thus, a multisensor integration system based on ultrawide-band (UWB), inertial navigation system (INS), nonholonomic constraints (NHCs), and Rauch–Tung–Striebel (RTS) smoother is proposed. In this system, the UWB performs as the major precise positioning system, while the INS bridges the UWB-degraded and UWB-denied periods. Meanwhile, the NHC restrains the drifts of INS, while the RTS smoother further upgrades the navigation accuracy. The contributions of this article are as follows. First, it presents the robust least square- (RLS-) based UWB positioning. The proposed method is effective in mitigating the impact of the effect of non-line-of-sight (NLOS), which is one of the most significant error sources for UWB positioning. Second, it derives the mathematical model of the UWB/INS/NHC/RTS integration, which is new compared to the existing approaches. Results illustrate that the proposed system can provide centimeter-level positioning accuracy, millimeter-level velocimetry accuracy, and accuracy of better than 0.05 and 0.15 degrees for horizontal and vertical attitude angles, respectively. Even in the scenario with short-term UWB outages (30 s), simulation results show that the three-dimensional position still can be better than 20 cm. Such accuracy values reach the state-of-the-art for indoor positioning using UWB and INS.
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Koller, Tom L., and Udo Frese. "The Interacting Multiple Model Filter and Smoother on Boxplus-Manifolds." Sensors 21, no. 12 (June 17, 2021): 4164. http://dx.doi.org/10.3390/s21124164.
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Hybrid systems are subject to multiple dynamic models, or so-called modes. To estimate the state, the sequence of modes has to be estimated, which results in an exponential growth of possible sequences. The most prominent solution to handle this is the interacting multiple model filter, which can be extended to smoothing. In this paper, we derive a novel generalization of the interacting multiple filter and smoother to manifold state spaces, e.g., quaternions, based on the boxplus-method. As part thereof, we propose a linear approximation to the mixing of Gaussians and a Rauch–Tung–Striebel smoother for single models on boxplus-manifolds. The derivation of the smoother equations is based on a generalized definition of Gaussians on boxplus-manifolds. The three, novel algorithms are evaluated in a simulation and perform comparable to specialized solutions for quaternions. So far, the benefit of the more principled approach is the generality towards manifold state spaces. The evaluation and generic implementations are published open source.
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Kwon, Bokyu. "Adaptive Fading-Memory Receding-Horizon Filters and Smoother for Linear Discrete Time-Varying Systems." Applied Sciences 12, no. 13 (July 1, 2022): 6692. http://dx.doi.org/10.3390/app12136692.
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In this paper, an adaptive fading-memory receding-horizon (AFMRH) filter is proposed by combining the receding-horizon structure and the adaptive fading-memory method. In the recent finite horizon, state error covariance is adapted with an adaptive fading factor; then the process noise covariance matrix adaption is realized by adjusting the properties of systems. An AFMRH fixed-lag smoother is also proposed by combining the proposed AFMRH filtering algorithm and a Rauch–Tung–Striebel smoothing algorithm to improve the estimation accuracy. Because the proposed AFMRH filter and smoother are reduced to the optimal receding-horizon (RH) filter and smoother when all measurements have the same weight, the proposed adaptive RH estimators could provide a more general solution than the optimal RH filter and smoother. To reduce the complexity and improve the estimation performance of the proposed RH estimators, an adaptive horizon adjustment method and a switching filtering algorithm based on an adaptive fading factor are also proposed. In particular, the proposed adaptive horizon adjustment method is designed to be computationally efficient, which makes it suitable for online and real-time applications. Through computer simulation, the performance and adaptiveness of the proposed approaches were verified by comparing them with existing fading-memory approaches.
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Tchegho, A., H. Gräb, U. Schlichtmann, H. Mattes, and S. Sattler. "Analyse und Untersuchung der Quantisierungseffekte beim Goertzel-Filter." Advances in Radio Science 7 (May 18, 2009): 73–81. http://dx.doi.org/10.5194/ars-7-73-2009.
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Abstract. Digitale Filter können in praktischen Anwendungen nur mit endlicher Wortbreite realisiert werden. Deshalb müssen Quantisierungseffekte verstanden werden, um die Eigenschaften und die Performanz der digitalen Filter geeignet einstellen zu können. Die am stärksten beeinflussten Aspekte sind neben Frequenzgang, die Stabilität und das Signal-Rausch-Verhältnis. Zu geringe Wortbreiten führen zu drastischen Veränderungen der Filtereigenschaften. Eine zu konservativ gewählte Wortbreite hingegen, erhöht die Größe und somit die Anzahl der Operationen des Filters unnötigerweise. Ziel dieses Beitrages ist es, für eine bestimmte Filterklasse optimale Wortbreiten zu finden, welche sowohl die Anzahl der Berechnungen und damit Operationen minimieren als auch sicherstellen, dass vorgegebene Toleranzbereiche für spezifizierte Filtereigenschaften eingehalten werden können. Die Untersuchungen werden an einem Goertzel-Filter durchgeführt, welches aufgrund seiner effizienten Eigenschaften besonders für die spektrale Bewertung von Mixed-Signal Schaltungen und Systemen geeignet ist.
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Vanhooren, H., D. De Pauw, and P. A. Vanrolleghem. "Induction of denitrification in a pilot-scale trickling filter by adding nitrate at high loading rate." Water Science and Technology 47, no. 11 (June 1, 2003): 61–68. http://dx.doi.org/10.2166/wst.2003.0587.
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Oxygen transferred from the liquid phase into a biofilm can be used for aerobic degradation of organic matter and for nitrification. A second possible pathway for the removal of organic matter is denitrification in anoxic zones deeper in the biofilm. At high organic loading rates with insufficient oxygen supply to the biofilm, denitrification could be induced by providing the biofilm with external nitrate. This possibility was tested in a pilot-scale trickling filter by adding a pulse of nitrate to a highly loaded trickling filter. The experiment showed that denitrification can indeed be induced by adding nitrate at high loading conditions and that this way a considerably increased substrate removal capacity can be obtained. The fact that denitrification occurred was confirmed by the increased production of CO2 from bioconversion processes, without a major change of the O2 consumption. The simplified mixed-culture biofilm model developed by Rauch et al. was extended for the description of off-gas measurements and was able to describe the results of the experiment very well.
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Liu, Hongqiang, Haiyan Yang, Tao Zhang, and Bo Pan. "Gauss process state-space model optimization algorithm with expectation maximization." International Journal of Distributed Sensor Networks 15, no. 7 (July 2019): 155014771986221. http://dx.doi.org/10.1177/1550147719862217.
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A Gauss process state-space model trained in a laboratory cannot accurately simulate a nonlinear system in a non-laboratory environment. To solve this problem, a novel Gauss process state-space model optimization algorithm is proposed by combining the expectation–maximization algorithm with the Gauss process Rauch–Tung–Striebel smoother algorithm, that is, the EM-GP-RTSS algorithm. First, a theoretical formulation of the Gauss process state-space model is proposed, which is not found in previous references. Second, a Gauss process state-space model optimization framework with the expectation–maximization algorithm is proposed. In the expectation–maximization algorithm, the unknown system state is considered as the lost data, and the maximization of measurement likelihood function is transformed into that of a conditional expectation function. Then, the Gauss process–assumed density filter algorithm and the Gauss process Rauch–Tung–Striebel smoother algorithm are proposed with the Gauss process state-space model defined in this article, in order to calculate the smoothed distribution in the conditional expectation function. Finally, the Monte Carlo numerical integral method is used to obtain the approximate expression of the conditional expectation function. The simulation results demonstrate that the Gauss process state-space model optimized by the EM-GP-RTSS can simulate the system in the non-laboratory environment better than the Gauss process state-space model trained in the laboratory, and can reach or exceed the estimation accuracy of the traditional state-space model.
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Vanhooren, H., D. Demey, I. Vannijvel, and P. A. Vanrolleghem. "Monitoring and modelling an industrial trickling filter using on-line off-gas analysis and respirometry." Water Science and Technology 41, no. 12 (June 1, 2000): 139–48. http://dx.doi.org/10.2166/wst.2000.0258.
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The process characteristics of an industrial scale trickling filter plant were quantified by means of a five day intensive measurement campaign with the use of on-line respirometry and on-line off-gas analysis. Respirometry was used to measure the readily biodegradable CODst and the off-gas sensor was used to monitor the O2 and CO2 content of the off-gases. To model the biodegradation in the filters, the model developed by Rauch et al. (1999) was used. It is based on the decoupling of two basic processes in biofilm systems, substrate diffusion and biodegradation. This model was extended with equations for the production and the pH-dependent liquid-phase equilibrium for inorganic carbon (IC). The measured effluent and off-gas concentrations could be followed very closely by the calibrated model. O2 and CO2 measurements revealed that the system was not always oxygen limited. The model calibration thus required the use of a very low value of the diffusion constant for readily biodegradable substrate.
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Zheng, Jiangtao, Sihai Li, Shiming Liu, Bofan Guan, Dong Wei, and Qiangwen Fu. "Research on the Shearer Positioning Method Based on the MEMS Inertial Sensors/Odometer Integrated Navigation System and RTS Smoother." Micromachines 12, no. 12 (December 8, 2021): 1527. http://dx.doi.org/10.3390/mi12121527.
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The shearer positioning method with an inertial measurement unit and the odometer is feasible in the longwall coal-mining process. However, the positioning accuracy will continue to decrease, especially for the micro-electromechanical inertial measurement unit (MIMU). In order to further improve the positioning accuracy of the shearer without adding other external sensors, the positioning method of the Rauch-Tung-Striebel (RTS) smoother-aided MIMU and odometer is proposed. A Kalman filter (KF) with the velocity and position measurements, which are provided by the odometer and closing path optimal estimation model (CPOEM), respectively, is established. The observability analysis is discussed to study the possible conditions under which the error states of KF can be estimated. A RTS smoother with the above-mentioned KF as the forward filter is built. Finally, the experiments of simulating the movement of the shearer through a mobile carrier were carried out, with a longitudinal movement distance of 44.6 m and a lateral advance distance of 1.2 m. The results show that the proposed method can effectively improve the positioning accuracy. In addition, the odometer scale factor and mounting angles can be estimated in real time.
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Ullah, Ihsan, Muhammad Qureshi, Uzair Khan, Sufyan Memon, Yifang Shi, and Dongliang Peng. "Multisensor-Based Target-Tracking Algorithm with Out-of-Sequence-Measurements in Cluttered Environments." Sensors 18, no. 11 (November 20, 2018): 4043. http://dx.doi.org/10.3390/s18114043.
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A localization and tracking algorithm for an early-warning tracking system based on the information fusion of Infrared (IR) sensor and Laser Detection and Ranging (LADAR) is proposed. The proposed Kalman filter scheme incorporates Out-of-Sequence Measurements (OOSMs) to address long-range, high-speed incoming targets to be tracked by networked Remote Observation Sites (ROS) in cluttered environments. The Rauch–Tung–Striebel (RTS) fixed lag smoothing algorithm is employed in the proposed technique to further improve tracking accuracy, which, in turn, is used for target profiling and efficient filter initialization at the targeted platform. This efficient initialization increases the probability of target engagement by increasing the distance at which it can be effectively engaged. The increased target engagement range also reduces risk of any damage from debris of the engaged target. Performance of the proposed target localization algorithm with OOSM and RTS smoothing is evaluated in terms of root mean square error (RMSE) for both position and velocity, which accurately depicts the improved performance of the proposed algorithm in comparison with existing retrodiction-based OOSM filtering algorithms. The effects of assisted target state initialization at the targeted platform are also evaluated in terms of Time to Impact (TTI) and true track retention, which also depict the advantage of the proposed strategy.
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Gong, Xiaolin, and Tingting Qin. "Airborne Earth Observation Positioning and Orientation by SINS/GPS Integration Using CD R-T-S Smoothing." Journal of Navigation 67, no. 2 (September 20, 2013): 211–25. http://dx.doi.org/10.1017/s0373463313000623.
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This paper addresses the issue of state estimation in the integration of a Strapdown Inertial Navigation System (SINS) and Global Positioning System (GPS), which is used for airborne earth observation positioning and orientation. For a nonlinear system, especially with large initial attitude errors, the performance of linear estimation approaches will degrade. In this paper a nonlinear error model based on angle errors is built, and a nonlinear estimation algorithm called the Central Difference Rauch-Tung-Striebel (R-T-S) Smoother (CDRTSS) is utilized in SINS/GPS integration post-processing. In this algorithm, the measurements are first processed by the forward Central Difference Kalman filter (CDKF) and then a separate backward smoothing pass is used to obtain the improved solution. The performance of this algorithm is compared with a similar smoother based on an extended Kalman filter known as ERTSS through Monte Carlo simulations and flight tests with a loaded SINS/GPS integrated system. Furthermore, a digital camera was used to verify the precision of practical applications in a check field with numerous reference points. All these validity checks demonstrate that CDRTSS is a better method and the work of this paper will offer a new approach for SINS/GPS integration for Synthetic Aperture Radar (SAR) and other airborne earth observation tasks.
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Bartlett, Susan J., Skye P. Barbic, Vivian P. Bykerk, Ernest H. Choy, Rieke Alten, Robin Christensen, Alfons den Broeder, et al. "Content and Construct Validity, Reliability, and Responsiveness of the Rheumatoid Arthritis Flare Questionnaire: OMERACT 2016 Workshop Report." Journal of Rheumatology 44, no. 10 (August 15, 2017): 1536–43. http://dx.doi.org/10.3899/jrheum.161145.
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Objective.The Outcome Measures in Rheumatology (OMERACT) Rheumatoid Arthritis (RA) Flare Group was established to develop a reliable way to identify and measure RA flares in randomized controlled trials (RCT). Here, we summarized the development and field testing of the RA Flare Questionnaire (RA-FQ), and the voting results at OMERACT 2016.Methods.Classic and modern psychometric methods were used to assess reliability, validity, sensitivity, factor structure, scoring, and thresholds. Interviews with patients and clinicians also assessed content validity, utility, and meaningfulness of RA-FQ scores.Results.People with RA in observational trials in Canada (n = 896) and France (n = 138), and an RCT in the Netherlands (n = 178) completed 5 items (11-point numerical rating scale) representing RA Flare core domains. There was moderate to high evidence of reliability, content and construct validity, and responsiveness. Factor analysis supported unidimensionality. Rasch analysis showed acceptable fit to the Rasch model, with items and people covering a broad measurement continuum and evidence of appropriate targeting of items to people, ordered thresholds, minimal differential item functioning by language, sex, or age. A summative score across items is defensible, yielding an interval score (0–50) where higher scores reflect worsening flare. The RA-FQ received endorsement from 88% of attendees that it passed the OMERACT Filter 2.0 “Eyeball Test” for instrument selection.Conclusion.The RA-FQ has been developed to identify and measure RA flares. Its review through OMERACT Filter 2.0 shows evidence of reliability, content and construct validity, and responsiveness. These properties merit its further validation as an outcome for clinical trials.
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Zhao, Hongyu, Zhelong Wang, Qin Gao, Mohammad Mehedi Hassan, and Abdulhameed Alelaiwi. "Smooth estimation of human foot motion for zero-velocity-update-aided inertial pedestrian navigation system." Sensor Review 35, no. 4 (September 21, 2015): 389–400. http://dx.doi.org/10.1108/sr-03-2015-0032.
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Purpose – The purpose of this paper is to develop an online smoothing zero-velocity-update (ZUPT) method that helps achieve smooth estimation of human foot motion for the ZUPT-aided inertial pedestrian navigation system. Design/methodology/approach – The smoothing ZUPT is based on a Rauch–Tung–Striebel (RTS) smoother, using a six-state Kalman filter (KF) as the forward filter. The KF acts as an indirect filter, which allows the sensor measurement error and position error to be excluded from the error state vector, so as to reduce the modeling error and computational cost. A threshold-based strategy is exploited to verify the detected ZUPT periods, with the threshold parameter determined by a clustering algorithm. A quantitative index is proposed to give a smoothness estimate of the position data. Findings – Experimental results show that the proposed method can improve the smoothness, robustness, efficiency and accuracy of pedestrian navigation. Research limitations/implications – Because of the chosen smoothing algorithm, a delay no longer than one gait cycle is introduced. Therefore, the proposed method is suitable for applications with soft real-time constraints. Practical implications – The paper includes implications for the smooth estimation of most types of pedal locomotion that are achieved by legged motion, by using a sole foot-mounted commercial-grade inertial sensor. Originality/value – This paper helps realize smooth transitions between swing and stance phases, helps enable continuous correction of navigation errors during the whole gait cycle, helps achieve robust detection of gait phases and, more importantly, requires lower computational cost.
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Jiang, Yinfeng, Wenxiang Song, Hao Zhu, Yun Zhu, Yongzhi Du, and Huichun Yin. "Extended Rauch–Tung–Striebel Smoother for the State of Charge Estimation of Lithium-Ion Batteries Based on an Enhanced Circuit Model." Energies 15, no. 3 (January 28, 2022): 963. http://dx.doi.org/10.3390/en15030963.
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The state of charge (SOC) of a lithium battery system is critical since it indicates the remaining operating hours, full charge time, and peak power of the battery. This paper recommends an extended Rauch–Tung–Striebel smoother (ERTSS) for estimating SOC. It is implemented based on an improved equivalent circuit model with hysteresis voltage. The smoothing step of ERTSS will reduce the estimation error further. Additionally, the genetic algorithm (GA) is employed for searching the optimal ERTSS’s smoothing time interval. Various dynamic cell tests are conducted to verify the model’s accuracy and error estimation deviation. The test results demonstrate that ERTSS’s SOC estimation error is limited to 4% with an initial error between −25 ∘C and 45 ∘C and that the root mean square error (RMSE) of ERTSS’s SOC estimation is approximately 5% lower than that of extended Kalman filter (EKF). The ERTSS improves the SOC estimation accuracy at all operating temperatures of batteries.
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Gong, Xiaolin, Xiaorui Zheng, Xing-Gang Yan, and Zhaoxing Lu. "Unscented Particle Smoother and Its Application to Transfer Alignment of Airborne Distributed POS." International Journal of Aerospace Engineering 2018 (September 30, 2018): 1–13. http://dx.doi.org/10.1155/2018/3898734.
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This paper deals with the problem of state estimation for the transfer alignment of airborne distributed position and orientation system (distributed POS). For a nonlinear system, especially with large initial attitude errors, the performance of linear estimation methods will degrade. In this paper, a nonlinear smoothing algorithm called the unscented particle smoother (UPS) is proposed and utilized in the off-line transfer alignment of airborne distributed POS. In this algorithm, the measurements are first processed by the forward unscented particle filter (UPF) and then a backward smoother is used to achieve the improved solution. The performance of this algorithm is compared with that of a similar smoother known as the unscented Rauch-Tung-Striebel smoother. The simulation results show that the UPS effectively improves the estimation accuracy and this work offers a new off-line transfer alignment approach of distributed POS for multiantenna synthetic aperture radar and other airborne earth observation tasks.
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Zhang, Qiuzhao, Wei Yang, Shubi Zhang, and Xin Liu. "Characteristics of BeiDou Navigation Satellite System Multipath and Its Mitigation Method Based on Kalman Filter and Rauch-Tung-Striebel Smoother." Sensors 18, no. 2 (January 12, 2018): 198. http://dx.doi.org/10.3390/s18010198.
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Li, Xiaohua, Bo Lu, Wasiq Ali, Jun Su, and Haiyan Jin. "Passive Sonar Multiple-Target Tracking with Nonlinear Doppler and Bearing Measurements Using Multiple Sensors." International Journal of Aerospace Engineering 2021 (October 11, 2021): 1–11. http://dx.doi.org/10.1155/2021/4163766.
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The major advantage of the passive multiple-target tracking is that the sonars do not emit signals and thus they can remain covert, which will reduce the risk of being attacked. However, the nonlinearity of the passive Doppler and bearing measurements, the range unobservability problem, and the measurement to target data association uncertainty make the passive multiple-target tracking problem challenging. To deal with the target to measurement data association uncertainty problem from multiple sensors, this paper proposed a batch recursive extended Rauch-Tung-Striebel smoother- (RTSS-) based probabilistic multiple hypothesis tracker (PMHT) algorithm, which can effectively handle a large number of passive measurements including clutters. The recursive extended RTSS which consists of a forward filter and a backward smoothing is used to deal with the nonlinear Doppler and bearing measurements. The target range unobservability problem is avoided due to using multiple passive sensors. The simulation results show that the proposed algorithm works well in a passive multiple-target tracking system under dense clutter environment, and its computing cost is low.
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Yin, Yuming, Jinhong Zhang, Mengqi Guo, Xiaobin Ning, Yuan Wang, and Jianshan Lu. "Sensor Fusion of GNSS and IMU Data for Robust Localization via Smoothed Error State Kalman Filter." Sensors 23, no. 7 (April 1, 2023): 3676. http://dx.doi.org/10.3390/s23073676.
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High−precision and robust localization is critical for intelligent vehicle and transportation systems, while the sensor signal loss or variance could dramatically affect the localization performance. The vehicle localization problem in an environment with Global Navigation Satellite System (GNSS) signal errors is investigated in this study. The error state Kalman filtering (ESKF) and Rauch–Tung–Striebel (RTS) smoother are integrated using the data from Inertial Measurement Unit (IMU) and GNSS sensors. A segmented RTS smoothing algorithm is proposed in order to estimate the error state, which is typically close to zero and mostly linear, which allows more accurate linearization and improved state estimation accuracy. The proposed algorithm is evaluated using simulated GNSS signals with and without signal errors. The simulation results demonstrate its superior accuracy and stability for state estimation. The designed ESKF algorithm yielded an approximate 3% improvement in long straight line and turning scenarios compared to classical EKF algorithm. Additionally, the ESKF−RTS algorithm exhibited a 10% increase in the localization accuracy compared to the ESKF algorithm. In the double turning scenarios, the ESKF algorithm resulted in an improvement of about 50% in comparison to the EKF algorithm, while the ESKF−RTS algorithm improved by about 50% compared to the ESKF algorithm. These results indicated that the proposed ESKF−RTS algorithm is more robust and provides more accurate localization.
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Ruscio, Francesco, Giovanni Peralta, Lorenzo Pollini, and Riccardo Costanzi. "Information Communication Technology (ICT) Tools for Preservation of Underwater Environment: A Vision-Based Posidonia Oceanica Monitoring." Marine Technology Society Journal 55, no. 4 (July 1, 2021): 11–23. http://dx.doi.org/10.4031/mtsj.55.4.5.
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Abstract Underwater monitoring activities are crucial for the preservation of marine ecosystems. Currently, scuba divers are involved in data collection campaigns that are repetitive, dangerous, and expensive. This article describes the application of Information Communication Technology (ICT) tools to underwater visual data for monitoring purposes. The data refer to a Posidonia Oceanica survey mission carried out by a scuba diver using a Smart Dive Scooter equipped with visual acquisition and acoustic localization systems. An acoustic-based strategy for geo-referencing of the optical dataset is reported. It exploits the synchronization between the audio track extracted from a camera and the transponder pings adopted for the acoustic positioning. The positioning measurements are employed within an extended Kalman filter to estimate the diver's path during the mission. A visual odometry algorithm is implemented within the filter to refine the navigation state estimation of the diver with respect to the acoustic positioning only. Moreover, a smoothing step based on the Rauch-Tung-Striebel smoother is applied to further improve the estimated diver's positions. Finally, the article reports the results of two different data processing for monitoring applications. The first one is an image mosaicking obtained by concatenating subsequent frames, whereas the second one refers to a qualitative distribution of the Posidonia Oceanica over the mission area accomplished through an image segmentation process. The two outcomes are plotted over a satellite image of the surveyed area, showing that the proposed process is an effective tool capable of facilitating divers in their monitoring and inspection activities.
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Kwon, Bokyu, and Pyung Soo Kim. "Novel Unbiased Optimal Receding-Horizon Fixed-Lag Smoothers for Linear Discrete Time-Varying Systems." Applied Sciences 12, no. 15 (August 4, 2022): 7832. http://dx.doi.org/10.3390/app12157832.
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This paper proposes novel unbiased minimum-variance receding-horizon fixed-lag (UMVRHF) smoothers in batch and recursive forms for linear discrete time-varying state space models in order to improve the computational efficiency and the estimation performance of receding-horizon fixed-lag (RHF) smoothers. First, an UMVRHF smoother in batch form is proposed by combining independent receding-horizon local estimators for two separated sub-horizons. The local estimates and their error covariance matrices are obtained based on an optimal receding horizon filter and the smoother in terms of the unbiased minimum variance; they are then optimally combined using Millman’s theorem. Next, the recursive form of the proposed UMVRHF smoother is derived to improve its computational efficiency and extendibility. Additionally, we introduce a method for extending the proposed recursive smoothing algorithm to a posteriori state estimations and propose the Rauch–Tung–Striebel receding-horizon fixed-lag smoother in recursive form. Furthermore, a computational complexity reduction technique that periodically switches the two proposed recursive smoothing algorithms is proposed. The performance and effectiveness of the proposed smoothers are demonstrated by comparing their estimation results with those of previous algorithms for Kalman and receding-horizon fixed-lag smoothers via numerical experiments.
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Duong, Thanh Trung, Kai-Wei Chiang, and Dinh Thuan Le. "On-line Smoothing and Error Modelling for Integration of GNSS and Visual Odometry." Sensors 19, no. 23 (November 29, 2019): 5259. http://dx.doi.org/10.3390/s19235259.
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Global navigation satellite systems (GNSSs) are commonly used for navigation and mapping applications. However, in GNSS-hostile environments, where the GNSS signal is noisy or blocked, the navigation information provided by a GNSS is inaccurate or unavailable. To overcome these issues, this study proposed a real-time visual odometry (VO)/GNSS integrated navigation system. An on-line smoothing method based on the extended Kalman filter (EKF) and the Rauch-Tung-Striebel (RTS) smoother was proposed. VO error modelling was also proposed to estimate the VO error and compensate the incoming measurements. Field tests were performed in various GNSS-hostile environments, including under a tree canopy and an urban area. An analysis of the test results indicates that with the EKF used for data fusion, the root-mean-square error (RMSE) of the three-dimensional position is about 80 times lower than that of the VO-only solution. The on-line smoothing and error modelling made the results more accurate, allowing seamless on-line navigation information. The efficiency of the proposed methods in terms of cost and accuracy compared to the conventional inertial navigation system (INS)/GNSS integrated system was demonstrated.
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Dietrich, Michael. "Technische Grundlagen der Neurographie/Evozierten Potentiale – Teil IV Mittelungen/Averager." Klinische Neurophysiologie 54, no. 01 (March 2023): 54–56. http://dx.doi.org/10.1055/a-1991-8459.
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In Teil I und II dieser Serie habe ich die Eigenschaften des Verstärkers, der Ableitelektroden und Filter vorgestellt und daraus hergeleitet wie man sich diese für optimale Messergebnisse zu nutzen machen kann und was man vermeiden sollte 1 2. All diese Maßnahmen dienen dazu das gewünschte Signal möglichst ohne Störungen und Rauschen darzustellen und so möglichst genau messen und für eine zuverlässige Diagnostik nutzen zu können. Die Qualität einer Messkurve kann mit dem Signal-Rausch-Verhältnis (engl. signal to noise ratio, SRV) quantifiziert werden. Ist das zu erwartende Signal sehr klein (im µV Bereich) und das Rauschen oder die Hintergrundaktivität trotz aller technischen Optimierung im gleichen Bereich wie die Signalamplitude oder sogar größer, ist das SRV 1 oder kleiner 1. Das macht eine sichere Auswertung der Kurven unmöglich.
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Shi, Bo, Mengke Wang, Yunpeng Wang, Yuntian Bai, Kang Lin, and Fanlin Yang. "Effect Analysis of GNSS/INS Processing Strategy for Sufficient Utilization of Urban Environment Observations." Sensors 21, no. 2 (January 17, 2021): 620. http://dx.doi.org/10.3390/s21020620.
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The occlusion of buildings in urban environments leads to the intermittent reception of satellite signals, which limits the utilization of observations. This subsequently results in a decline of the positioning and attitude accuracy of Global Navigation Satellite System (GNSS)/Inertial Navigation System (INS) integrated system (GNSS/INS). This study implements a smooth post-processing strategy based on a tightly coupled differential GNSS/INS. Specifically, this strategy used the INS-estimated position to reinitialize integer ambiguity. The GNSS raw observations were input into the Kalman filter to update the measurement. The Rauch–Tung–Striebel smoothing (RTSS) algorithm was used to process the observations of the entire period. This study analyzed the performance of loosely coupled and tightly coupled systems in an urban environment and the improvement of the RTSS algorithm on the navigation solution from the perspective of fully mining the observations. The experimental results of the simulation data and real data show that, compared with the traditional tightly coupled processing strategy which does not use INS-aided integer ambiguity resolution and RTSS algorithm, the strategy in this study sufficiently utilized INS observations and GNSS observations to effectively improve the accuracy of positioning and attitude and ensure the continuity of navigation results in an obstructed environment.
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Han, Houzeng, Jian Wang, and Mingyi Du. "A Fast SINS Initial Alignment Method Based on RTS Forward and Backward Resolution." Journal of Sensors 2017 (2017): 1–11. http://dx.doi.org/10.1155/2017/7161858.
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For the strapdown inertial navigation system (SINS), the procedure of initial alignment is a necessity before the navigation can commence. On the quasi-stationary base, the self-alignment can be fulfilled with the high quality inertial sensors, and the fine alignment is usually executed to improve the alignment performance. Generally, fast estimating of heading misalignment is still a challenge due to the existence of gyro errors. An innovative data processing strategy called forward and backward resolution is proposed for INS initial alignment. The Rauch-Tung-Striebel (RTS) smoothing is applied to obtain the smoothed attitude estimates with the filter information provided by the forward data processing. The obtained attitudes are then treated as aiding measurements to implement the forward resolution with the repeated data set, the converged sensor biases are used as constraints, and the iterative processing is conducted to obtain the updated attitudes. Simulation studies have been conducted to validate the proposed algorithm. The results have shown that the alignment accuracy and convergence rate have been improved with the added RTS aided forward and backward resolution; more stable heading estimates can be obtained by calibrating with estimated gyro bias. A real test with a high quality inertial sensor was also carried out to validate the effectiveness of the proposed algorithm.
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Han, Yulong, Haili Sun, Yue Lu, Ruofei Zhong, Changqi Ji, and Si Xie. "3D Point Cloud Generation Based on Multi-Sensor Fusion." Applied Sciences 12, no. 19 (September 20, 2022): 9433. http://dx.doi.org/10.3390/app12199433.
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Traditional precise engineering surveys adopt manual static, discrete observation, which cannot meet the dynamic, continuous, high-precision and holographic fine measurements required for large-scale infrastructure construction, operation and maintenance, where mobile laser scanning technology is becoming popular. However, in environments without GNSS signals, it is difficult to use mobile laser scanning technology to obtain 3D data. We fused a scanner with an inertial navigation system, odometer and inclinometer to establish and track mobile laser measurement systems. The control point constraints and Rauch-Tung-Striebel filter smoothing were fused, and a 3D point cloud generation method based on multi-sensor fusion was proposed. We verified the method based on the experimental data; the average deviation of positioning errors in the horizontal and elevation directions were 0.04 m and 0.037 m, respectively. Compared with the stop-and-go mode of the Amberg GRP series trolley, this method greatly improved scanning efficiency; compared with the method of generating a point cloud in an absolute coordinate system based on tunnel design data conversion, this method improved data accuracy. It effectively avoided the deformation of the tunnel, the sharp increase of errors and more accurately and quickly processed the tunnel point cloud data. This method provided better data support for subsequent tunnel analysis such as 3D display, as-built surveying and disease system management of rail transit tunnels.
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Hansen, A. B., J. Brandt, J. H. Christensen, and E. Kaas. "Semi-Lagrangian methods in air pollution models." Geoscientific Model Development 4, no. 2 (June 24, 2011): 511–41. http://dx.doi.org/10.5194/gmd-4-511-2011.
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Abstract. Various semi-Lagrangian methods are tested with respect to advection in air pollution modeling. The aim is to find a method fulfilling as many of the desirable properties by Rasch andWilliamson (1990) and Machenhauer et al. (2008) as possible. The focus in this study is on accuracy and local mass conservation. The methods tested are, first, classical semi-Lagrangian cubic interpolation, see e.g. Durran (1999), second, semi-Lagrangian cubic cascade interpolation, by Nair et al. (2002), third, semi-Lagrangian cubic interpolation with the modified interpolation weights, Locally Mass Conserving Semi-Lagrangian (LMCSL), by Kaas (2008), and last, semi-Lagrangian cubic interpolation with a locally mass conserving monotonic filter by Kaas and Nielsen (2010). Semi-Lagrangian (SL) interpolation is a classical method for atmospheric modeling, cascade interpolation is more efficient computationally, modified interpolation weights assure mass conservation and the locally mass conserving monotonic filter imposes monotonicity. All schemes are tested with advection alone or with advection and chemistry together under both typical rural and urban conditions using different temporal and spatial resolution. The methods are compared with a current state-of-the-art scheme, Accurate Space Derivatives (ASD), see Frohn et al. (2002), presently used at the National Environmental Research Institute (NERI) in Denmark. To enable a consistent comparison only non-divergent flow configurations are tested. The test cases are based either on the traditional slotted cylinder or the rotating cone, where the schemes' ability to model both steep gradients and slopes are challenged. The tests showed that the locally mass conserving monotonic filter improved the results significantly for some of the test cases, however, not for all. It was found that the semi-Lagrangian schemes, in almost every case, were not able to outperform the current ASD scheme used in DEHM with respect to accuracy.
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Hansen, A. B., J. Brandt, J. H. Christensen, and E. Kaas. "Semi-Lagrangian methods in air pollution models." Geoscientific Model Development Discussions 3, no. 4 (December 15, 2010): 2361–438. http://dx.doi.org/10.5194/gmdd-3-2361-2010.
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Abstract. Various semi-Lagrangian methods are tested with respect to advection in air pollution modeling. The aim is to find a method fulfilling as many of the desirable properties by Rasch and Williamson (1990) and Machenhauer et al. (2008) as possible. The focus in this study is on accuracy and local mass conservation. The methods tested are, first, classical semi-Lagrangian cubic interpolation, see e.g. Durran (1999), second, semi-Lagrangian cubic cascade interpolation, by Nair et al. (2002), third, semi-Lagrangian cubic interpolation with the modified interpolation weights, Locally Mass Conserving Semi-Lagrangian (LMCSL), by Kaas (2008), and last, semi-Lagrangian cubic interpolation with a locally mass conserving monotonic filter byKaas and Nielsen (2009). Semi-Lagrangian (SL) interpolation is a classical method for atmospheric modeling, cascade interpolation is more efficient computationally, modified interpolation weights assure mass conservation and the locally mass conserving monotonic filter imposes monotonicity. All schemes are tested with advection alone or with advection and chemistry together under both typical rural and urban conditions using different temporal and spatial resolution. The methods are compared with a current state-of-the-art scheme, Accurate Space Derivatives (ASD), see Frohn et al. (2002), presently used at the National Environmental Research Institute (NERI) in Denmark. To enable a consistent comparison only non-divergent flow configurations are tested. The test cases are based either on the traditional slotted cylinder or the rotating cone, where the schemes' ability to model both steep gradients and slopes are challenged. The tests showed that the locally mass conserving monotonic filter improved the results significantly for some of the test cases, however, not for all. It was found that the semi-Lagrangian schemes, in almost every case, were not able to outperform the current ASD scheme used in DEHM with respect to accuracy.
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Langley, Paul C. "Evidentiary Standards for Patient-Centered Core Impact (PC-CIS) Value Claims." INNOVATIONS in pharmacy 13, no. 3 (October 25, 2022): 15. http://dx.doi.org/10.24926/iip.v13i3.5016.
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Proposals for a patient centered core impact set (PC-CIS) are of little relevance to formulary and health system decisions, let alone patients and providers, unless the elements included in the data set meet the standards of normal science and fundamental measurement. Adhering to these standards will have the effect of focusing on the adequacy of proposed core impact measures, with a filter in place to accept only those that meet the standards not only of the physical sciences but also mainstream economics. and health economics. Fortunately, we are well aware of what the criteria for acceptance and rejection of the core impacts within disease states should be in terms of their required attributes and their relevance for supporting evaluable value claims, notably for patient reported outcomes, Rasch or modern measurement theory. Care must be taken to delineate the core impact elements: separately identifying those that are purely clinical from core patient centric impacts, which is turn should be separated from impacts defined in terms of drug utilization and resource utilization. The purpose of this brief commentary is to set out the required standards for core impact patient-centric value claims and the framework for evaluating those claims. The critical issue for patient-centered core impacts is to recognize the constraints imposed by the standards of fundamental measurement for target patient populations within disease areas; unless these constraints are recognized we will fail. The leads to the role of Rasch or modern measurement theory calibration as the framework for patient centric measures of latent traits or attributes. From these perspectives PC-CIS is premature; until we have agreed standards for measurement for the impact or outcomes for clinical, patient-centric and resource utilization as a core set of disease specific instruments, it seems pointless to push forward to a wider scope when the present evidentiary foundation is so weak.
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Sun, Jie, Feng Hu, Wenming Jin, Jin Wang, Xu Wang, Yeteng Luo, Jiancheng Yu, and Aiqun Zhang. "Model-Aided Localization and Navigation for Underwater Gliders Using Single-Beacon Travel-Time Differences." Sensors 20, no. 3 (February 7, 2020): 893. http://dx.doi.org/10.3390/s20030893.
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An accurate motion model and reliable measurements are required for autonomous underwater vehicle localization and navigation in underwater environments. However, without a propeller, underwater gliders have limited maneuverability and carrying capacity, which brings difficulties for modeling and measuring. In this paper, an extended Kalman filter (EKF)-based method, combining a modified kinematic model of underwater gliders with the travel-time differences between signals received from a single beacon, is proposed for estimating the glider positions in a predict-update cycle. First, to accurately establish a motion model for underwater gliders moving in the ocean, we introduce two modification parameters, the attack and drift angles, into a kinematic model of underwater gliders, along with depth-averaged current velocities. The attack and drift angles are calculated based on the coefficients of hydrodynamic forces and the sensor-measured angle variation over time. Then, instead of satisfying synchronization requirements, the travel-time differences between signals received from a single beacon, multiplied by the sound speed, are taken as the measurements. To further reduce the EKF estimation error, the Rauch-Tung-Striebel (RTS) smoothing method is merged into the EKF system. The proposed method is tested in a virtual spatiotemporal environment from an ocean model. The experimental results show that the performance of the RTS-EKF estimate is improved when compared with the motion model estimate, especially by 46% at the inflection point, at least in the particular study developed in this article.
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Aboudan, Alessio, Andrea Bulgarelli, Valentina Fioretti, Andrea Giuliani, Marco Tavani, and Stefano Debei. "A Multimission Method for the Reconstruction of Gamma-ray Events on Silicon Tracker Pair Telescopes." Astrophysical Journal 928, no. 2 (April 1, 2022): 141. http://dx.doi.org/10.3847/1538-4357/ac5626.
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Abstract γ-ray astronomy in the energy range from MeV to GeV can provide a unique detection window for γ-ray bursts and other transient sources, fundamental information on particle acceleration mechanisms, MeV-blazar population studies up to z ∼ 4.5, and a full overview of line emission from cosmic-ray interaction. Silicon-based pair tracking telescopes rely on γ-ray conversion into an electron–positron pair and its tracking using a stack of silicon strips. The method presented in this work is based on a Rauch–Tung–Striebel smoother. Its internal Kalman filter enables keeping multiple hypotheses about particle tracks and implementing statistically meaningful measurement selection among hits on different planes of the tracker. The algorithm can be easily configured to work with different tracker geometries and mass models. It can be used for the exploitation of data from past and current γ-ray missions as well as to assess the performances of new pair-tracking telescopes. The proposed method has been validated on Astrorivelatore Gamma a Immagini Leggero data and then used to investigate the performances of both e-ASTROGAM and All-Sky-ASTROGAM telescopes. The algorithm efficiency and its accuracy in estimating both the photon direction and energy were evaluated on γ-ray events simulated at different energies in the range between 30 MeV and 3 GeV. The point-spread function of each tracker was then compared with its angular resolution limit showing both the expected performances of the instrument and the margin of improvement that could be obtained by optimizing the reconstruction method.
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Zakharova, E. A. "Structure of the Information-Measuring Complex for Determining the Mutual Position of the Master and Slave Vehicles and Its Calibration." Intellekt. Sist. Proizv. 20, no. 1 (April 2, 2022): 13–21. http://dx.doi.org/10.22213/2410-9304-2022-1-13-21.
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The information-measuring complex for determining the mutual position of master and slave vehicles is necessary for the functioning of a robotic vehicle as a part of an autonomous convoy. The complex is based on a spatial array of ultrasonic receivers receiving periodically emitted signals by an active ultrasonic beacon with a built-in receiver of the global navigation satellite positioning system. The structure of information-measuring complex is designed to provide free connection of additional modules of ultrasonic wave receivers, included in the spatial array placed on the slave vehicle, without significant changes in the work of the complex as a whole. The number of required modules depends on the design features of the robotic vehicle, as well as on the required viewing angle of the complex. An active beacon, which is a portable device, is attached to its master, which can be another robotic vehicle, being a member of an autonomous convoy, or a human operator. The coordinates of each ultrasonic receiver in the local coordinate system of the slave robotic vehicle are needed to calculate the position and trajectory of the master by the Kalman filter with smoothing according to the Rauch-Thung-Strubel algorithm. To automatize the coordinate measurement process, a procedure for calibrating the spatial array of ultrasonic receivers has been developed. A distinctive feature of the calibration procedure is obtaining the coordinates of the ultrasonic receiver modules in the local coordinate system of the slave vehicle in automatic mode using a reference rangefinder mounted on the slave vehicle. In the course of experimental studies, it was found that the calibration of the information-measuring complex allowed to reduce the systematic component of the error in assessing the position of the master up to three times.
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Goll, S. A., and E. A. Zakharova. "Combined Estimation of the Mutual Position of the Master and Slave Vehicle by Ultrasonic Receivers and Gnss-Module Data." Intellekt. Sist. Proizv. 20, no. 1 (April 2, 2022): 4–12. http://dx.doi.org/10.22213/2410-9304-2022-1-4-12.
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The problem of determining the position of master vehicle when implementing a scenario of robotic vehicle as a part of caravanning driving system is studied. The mentioned scenario is expected the slave vehicle to replicate the motion trajectory of master vehicle represented by human operated vehicle, by another robotic vehicle or by human operator. To provide reliable operation of robotic vehicle within autonomous convoy a reliable and precise assessment of master vehicle position and trajectory regardless of environment is required. Implementation of ultrasonic receivers and emitters within information and measurement complex to determine master-slave vehicle mutual position allows to function at any time of the day inside and outside the premises in the presence of dynamic obstacles, smoke, precipitation, etc. Estimation of position and trajectory of master vehicle is accomplished by means of measuring arrival time of ultrasonic wave emitted by active beacon prior to spatial array of ultrasonic receivers. Similar indirect distance measurement between bacon and each receiver allowed to receive a system of equations to be solved by implementation of Kalman filter with Raugh - Tung - Striebel smoother. Major disadvantage of the approach is 20-meter range, which is enough for complex maneuvering. To increase the range of the complex operation, a combined estimation of the master's position based on measuring data of the spatial array of ultrasonic receivers and the module of global navigation satellite system is proposed.
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Deverell, Lil, Denny Meyer, Bee Theng Lau, Abdullah Al Mahmud, Suku Sukunesan, Jahar Bhowmik, Almon Chai, et al. "Optimising technology to measure functional vision, mobility and service outcomes for people with low vision or blindness: protocol for a prospective cohort study in Australia and Malaysia." BMJ Open 7, no. 12 (December 2017): e018140. http://dx.doi.org/10.1136/bmjopen-2017-018140.
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IntroductionOrientation and mobility (O&M) specialists assess the functional vision and O&M skills of people with mobility problems, usually relating to low vision or blindness. There are numerous O&M assessment checklists but no measures that reduce qualitative assessment data to a single comparable score suitable for assessing any O&M client, of any age or ability, in any location. Functional measures are needed internationally to align O&M assessment practices, guide referrals, profile O&M clients, plan appropriate services and evaluate outcomes from O&M programmes (eg, long cane training), assistive technology (eg, hazard sensors) and medical interventions (eg, retinal implants). This study aims to validate two new measures of functional performance vision-related outcomes in orientation and mobility (VROOM) and orientation and mobility outcomes (OMO) in the context of ordinary O&M assessments in Australia, with cultural comparisons in Malaysia, also developing phone apps and online training to streamline professional assessment practices.Methods and analysisThis multiphase observational study will employ embedded mixed methods with a qualitative/quantitative priority: corating functional vision and O&M during social inquiry. Australian O&M agencies (n=15) provide the sampling frame. O&M specialists will use quota sampling to generate cross-sectional assessment data (n=400) before investigating selected cohorts in outcome studies. Cultural relevance of the VROOM and OMO tools will be investigated in Malaysia, where the tools will inform the design of assistive devices and evaluate prototypes. Exploratory and confirmatory factor analysis, Rasch modelling, cluster analysis and analysis of variance will be undertaken along with descriptive analysis of measurement data. Qualitative findings will be used to interpret VROOM and OMO scores, filter statistically significant results, warrant their generalisability and identify additional relevant constructs that could also be measured.Ethics and disseminationEthical approval has been granted by the Human Research Ethics Committee at Swinburne University (SHR Project 2016/316). Dissemination of results will be via agency reports, journal articles and conference presentations.
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Spies, T., F. Olivier, F. Martinez-Pastor, D. M. Barry, and P. Bartels. "214USE OF FLOURESCENT PROBES TO ACCESS EPIDIDYMAL SPERMATOZOA OF THE BLUE WILDEBEEST CONNOCHAETES TAURINUS AND IMPALA ANTELOPE AEPYCEROS MELAMPUS MELAMPUS." Reproduction, Fertility and Development 16, no. 2 (2004): 228. http://dx.doi.org/10.1071/rdv16n1ab214.
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Sperm quality assessment may be a useful tool not only for evaluating the reproductive health of free-ranging populations, but also for selecting individuals for future assisted-reproduction technology programs. The aim of this study was to assess the functionality of epididymal spermatozoa collected from blue wildebeest (Connochaetes taurinus) and impala (Aepyceros melampus melampus) during the non-breeding season, using the fluorescent probes, propidium ioide (PI;; Sigma, South Africa) and JC-1 (Molecular Probes, The Netherlands). Six blue wildebeest and eight impala were harvested as part of a wildlife management program on a game ranch in South Africa. Testes were removed and transported to the laboratory within 6 hours while being maintained at 4°C. The cauda epididymides were removed and flushed with 1mL of Tris-citrate egg yolk extender (fraction A, Biladyl;; Minitüb, Germany). The sperm sample was diluted 1:4 in HEPES washing medium (Sigma;; 20mM HEPES, 355mM sucrose, 10mM glucose, 2.5mM KOH;; 400mOsm/kg, pH 7), and centrifuged for 5min at 600g, followed by re-suspending the pellet in 0.1mL of HEPES saline medium (Sigma;; as for washing medium, except 197mM NaCl instead of sucrose). The percentage of motile (MS) and progressively motile (PS) spermatozoa were determined using phase contrast microscopy (×200, 37°C). Sperm plasma membrane integrity and mitochondrial status were assessed using fluorescence microscopy (×400, 450–490nm excitation filter, 510nm dichroic-beam splitter, 520nm barrier filter) after staining with PI (50ngmL−1; 10min, RT) and JC-1 (7.5μM; 30min, 37°C), respectively. Spermatozoa with damaged plasma membranes showed a red fluorescence and spermatozoa with active and inactive mitochondria (MIT) fluoresced orange and green, respectively. Spearman correlation coefficients were calculated between spermatozoa with intact plasma membranes (IPM) and MIT, and with motility (Statistica™ package). A summary of the results is shown in the table 1. Although samples were not collected during the breeding season, sperm quality appeared to be good for the blue wildebeest, but less so for the impala. In general, impala results were more varied. Significant correlations were found for impala (n=8, P<0.05) MS-IPM: 0.75; IPM-MIT: 0.83, and for blue wildebeest (n=6, P<0.05), MS-IPM: 0.84; IPM-MIT: 0.81, and for pooled data (n=14, P<0.01), MS-IPM: 0.93; MS-MIT: 0.87; PS-IPM: 0.67; PS-MIT: 0.66; IPM-MIT: 0.95. These correlations suggest a relationship of functional parameters to sperm motility. Both membrane integrity and mitochondrial status are important for sperm flagellar activity. The correlation between IPM and MIT indicates a relationship or the effect of common factors. In conclusion, sperm collected from blue wildebeest and impala during the non-breeding season appear functional, a fact that may be useful for future conservation programs based on assisted reproduction technology or for assessing the reproductive health status of free-ranging wildlife populations. The fluorescent probes PI and JC-1 appear useful for assessing sperm quality in these two species and should be considered for further sperm quality assessment studies in other antelope species. Table 1 Results of the analyses, showing mean±SD (max.–min.)
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Wu, Chengyue, Casey E. Stowers, Zhan Xu, Ernesto A. B. F. Lima, Clinton Yam, Jong Bum Son, Jingfei Ma, Gaiane M. Rauch, and Thomas E. Yankeelov. "Abstract 5569: Quantification of tumor-associated vasculature as an imaging biomarker for monitoring the response of triple-negative breast cancer to neoadjuvant chemotherapy." Cancer Research 83, no. 7_Supplement (April 4, 2023): 5569. http://dx.doi.org/10.1158/1538-7445.am2023-5569.
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Abstract Introduction: Patients with locally advanced, triple-negative breast cancer (TNBC) typically receive neoadjuvant systemic therapy (NAST). However, the response of TNBC to NAST is varied and a prognostic marker is still lacking. Since angiogenesis plays an important role in cancer progression, the quantification of changes in the tumor vasculature during treatment has the potential to provide useful information for characterizing the treatment response. We have recently developed a method to quantify changes in tumor-associated vasculature through a novel analysis of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI). In this study, we investigated its ability to monitor the response of TNBC to NAST. Methods: Dynamic contrast-enhanced (DCE) MRI was acquired in TNBC patients (N = 50; 25 pathological complete response (pCR), 25 non-pCR) before, after 2 and 4 cycles of Adriamycin/Cyclophosphamide (A/C), as part of the ARTEMIS trial (NCT02276433). Using DCE-MRI, we identified the tumor-associated vessels via a breast vasculature analysis. Specifically, the difference between pre- and post-contrast DCE-MRI images was enhanced by a histogram-based intensity transfer function. The 3D vasculature in the breast was then segmented by applying a Hessian filter. Given the vasculature segmented by the algorithms and the tumor masks segmented by radiologists, a lowest-cost tracking algorithm was used to automatically detect the vessels that are most likely to contact the tumor. These vessels are defined as tumor-associated vessels (TAV). The number of TAVs per patient was tabulated and the Wilcoxon rank sum test compared the TAV values before (V1), after 2 cycles (V2), and after 4 cycles of NAST (V3). Additionally, we compared the percent change of TAV from V1 to V3 between the pCR patients and non-pCR patients. Statistical significance was defined as P < 0.05. Results: A significant decrease in the number of TAVs was observed during the NAST. In particular, the number of TAVs has a median (interquartile range) of 15 (7 - 24), 7 (3 - 14), and 2 (0 - 8) at V1, V2, V3, respectively, which are (pair-wise) significantly different (P < 0.01). Moreover, pCR patients showed a significantly greater decrease in the number of TAVs as compared to non-pCR patients. The percent changes in the number of TAVs from V1 to V3 have a median (range) of -88.89% (-100.00% - -60.00%) and -66.67% (-87.85% - -40.88%) in the pCR and non-pCR patients, respectively (P < 0.05). Conclusion: These preliminary results demonstrate that tumor-associated vasculature may be a valuable imaging biomarker for monitoring the response of TNBC to NAST. Ongoing efforts include additional investigation of the TAVs beyond their number, as well as applying the analysis to more patients. Citation Format: Chengyue Wu, Casey E. Stowers, Zhan Xu, Ernesto A. B. F. Lima, Clinton Yam, Jong Bum Son, Jingfei Ma, Gaiane M. Rauch, Thomas E. Yankeelov. Quantification of tumor-associated vasculature as an imaging biomarker for monitoring the response of triple-negative breast cancer to neoadjuvant chemotherapy. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 5569.
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Weaver Adams, Davis, Caleb Peck, and Manoranjan Majji. "Doppler Light Detection and Ranging-Aided Inertial Navigation and Trajectory Recovery." Journal of Guidance, Control, and Dynamics, June 1, 2023, 1–19. http://dx.doi.org/10.2514/1.g007318.
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A sensor fusion approach to terrain relative navigation is proposed in this paper. Sensor data from Global Position System (GPS), Inertial Navigation System (INS), and Doppler light detection and ranging (LIDAR) provide a relative state estimate through a novel multiplicative extended Kalman filter. The measurement model of the Doppler LIDAR is derived from first principals and employed by the filter to update the estimates propagated by the GPS/INS data stream. The line-of-sight Doppler velocity measurement provides direct feedback to the velocity states and improves sensitivity to these state estimates. A novel Rauch–Tung–Striebel smoother framework is derived that is compatible with states exhibiting multiplicative error that enables seamless postprocessing of state estimates filtered with a multiplicative extended Kalman filter. This new filter and smoother framework is tested with suborbital flight data from Blue Origin’s New Sheppard ascent and landing missions.
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Xia, Runlong, Yuantao Chen, and Binbin Ren. "Improved anti-occlusion object tracking algorithm using Unscented Rauch-Tung-Striebel smoother and kernel correlation filter." Journal of King Saud University - Computer and Information Sciences, February 2022. http://dx.doi.org/10.1016/j.jksuci.2022.02.004.
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Gu, Mengyang, Xubo Liu, Xinyi Fang, and Sui Tang. "Scalable Marginalization of Correlated Latent Variables with Applications to Learning Particle Interaction Kernels." New England Journal of Statistics in Data Science, 2022, 1–15. http://dx.doi.org/10.51387/22-nejsds13.
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Marginalization of latent variables or nuisance parameters is a fundamental aspect of Bayesian inference and uncertainty quantification. In this work, we focus on scalable marginalization of latent variables in modeling correlated data, such as spatio-temporal or functional observations. We first introduce Gaussian processes (GPs) for modeling correlated data and highlight the computational challenge, where the computational complexity increases cubically fast along with the number of observations. We then review the connection between the state space model and GPs with Matérn covariance for temporal inputs. The Kalman filter and Rauch-Tung-Striebel smoother were introduced as a scalable marginalization technique for computing the likelihood and making predictions of GPs without approximation. We introduce recent efforts on extending the scalable marginalization idea to the linear model of coregionalization for multivariate correlated output and spatio-temporal observations. In the final part of this work, we introduce a novel marginalization technique to estimate interaction kernels and forecast particle trajectories. The computational progress lies in the sparse representation of the inverse covariance matrix of the latent variables, then applying conjugate gradient for improving predictive accuracy with large data sets. The computational advances achieved in this work outline a wide range of applications in molecular dynamic simulation, cellular migration, and agent-based models.
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Wu, Jie, Huigang Xu, and Peiyi Zhu. "SOC and SOH Joint Estimation of Lithium-Ion Battery Based on Iterative Unscented Kalman Particle Filtering Algorithm with Fused Rauch-Tung-Striebel Smoothing Structure." Journal of Electrochemical Energy Conversion and Storage, December 23, 2022, 1–9. http://dx.doi.org/10.1115/1.4056557.
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Abstract Traditional particle filtering has a large estimation error in the state of charge and Lithium-ion battery health of electric Vehicle lithium batteries. For the above problems, the lithium battery second-order RC equivalent circuit model is established, and then the model parameters are identified using the multi-innovation least square algorithm (MILS). Finally, Iterative unscented Kalman particle filtering algorithm with fused Rauch-Tung-Striebel Smoothing Structure (RTS-IUPF) applied to Li-ion battery SOC and SOH joint estimation is proposed. The algorithm is based on the identification of battery parameters, the controller reads the sensor data and predicts the state results. RTS smoothing structure can do posterior estimation, and a significant probability density function is generated to select the optimal particle, and unscented Kalman algorithm regularized particles. The algorithm reduces the effect of the process noise covariance matrix and the measured noise covariance matrix on the filter accuracy and response time in traditional unselected Kalman filters. The algorithm proposed in the paper improves particle degradation and increases the estimation accuracy. Finally, the RTS-IUPF algorithm performs simulation analysis in Pulse current discharge condition and dynamic current condition (NEDC) respectively. The pulse current experimental results show that the mean absolute value error of UKF and PF (Number of particles N is 300) are 1.26% and 1.24%, respectively, while the error of the RTS-IUPF is 0.748%. The RMSE of the RTS-IUPF is reduced by 66.5% and 77.8% compared with UKF and PF. Furthermore, The error of joint estimation using this algorithm is smaller than that of single estimation. The RMSE of the RTS-IUPF Joint is reduced by 27.4% compared with RTS-IUPF. The feasibility and effectiveness of the algorithm for the joint estimation of SOC and SOH of lithium batteries were verified.
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Del Core, L., D. Pellin, E. C. Wit, and M. A. Grzegorczyk. "Scalable inference of cell differentiation networks in gene therapy clonal tracking studies of haematopoiesis." Bioinformatics, September 29, 2023. http://dx.doi.org/10.1093/bioinformatics/btad605.
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Abstract Motivation Investigating cell differentiation under a genetic disorder offers the potential for improving current gene therapy strategies. Clonal tracking provides a basis for mathematical modelling of population stem cell dynamics that sustain the blood cell formation, a process known as haematopoiesis. However, many clonal tracking protocols rely on a subset of cell types for the characterisation of the stem cell output, and the data generated are subject to measurement errors and noise. Results We propose a stochastic framework to infer dynamic models of cell differentiation from clonal tracking data. A state-space formulation combines a stochastic quasi-reaction network, describing cell differentiation, with a Gaussian measurement model accounting for data errors and noise. We developed an inference algorithm based on an extended Kalman filter, a nonlinear optimization, and a Rauch-Tung-Striebel smoother. Simulations show that our proposed method outperforms the state-of-the-art and scales to complex structures of cell differentiations in terms of nodes size and network depth. The application of our method to five in-vivo gene therapy studies reveals different dynamics of cell differentiation. Our tool can provide statistical support to biologists and clinicians to better understand cell differentiation and haematopoietic reconstitution after a gene therapy treatment. The equations of the state-space model can be modified to infer other dynamics besides cell differentiation. Availability The stochastic framework is implemented in the R package Karen which is available for download at https://cran.r-project.org/package=Karen. The code that supports the findings of this study is openly available at https://github.com/delcore-luca/CellDifferentiationNetworks. Supplementary information Supplementary data are available at Bioinformatics online.