Relevant bibliographies by topics / Active sonar tracking

Academic literature on the topic 'Active sonar tracking'

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Published: 10 December 2022
Last updated: 28 January 2023

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Journal articles on the topic "Active sonar tracking"

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Varadarajan, V., and J. Krolik. "Array shape estimation and tracking using active sonar reverberation." IEEE Transactions on Aerospace and Electronic Systems 40, no. 3 (July 2004): 1073–86. http://dx.doi.org/10.1109/taes.2004.1337475.

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Yao, Yu, Junhui Zhao, and Lenan Wu. "Doppler Data Association Scheme for Multi-Target Tracking in an Active Sonar System." Sensors 19, no. 9 (April 29, 2019): 2003. http://dx.doi.org/10.3390/s19092003.

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In many wireless sensors, the target kinematic states include location and Doppler information that can be observed from a time series of range and velocity measurements. In this work, we present a tracking strategy for comprising target velocity components as part of the measurement supplement procedure and evaluate the advantages of the proposed scheme. Data association capability can be considered as the key performance for multi-target tracking in an active sonar system. Then, we proposed an enhanced Doppler data association (DDA) scheme which exploits target range and target velocity components for linear multi-target tracking. If the target velocity measurements are not incorporated into target kinematic state tracking, the linear filter bank for the combination of target velocity components can be implemented. Finally, a significant enhancement in the multi-target tracking capability provided by the proposed DDA scheme with the linear multi-target combined probabilistic data association method is demonstrated in a sonar underwater scenario.
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Chen, Xiao, Yaan Li, Yuxing Li, and Jing Yu. "Active Sonar Target Tracking Based on the GM-CPHD Filter Algorithm." Xibei Gongye Daxue Xuebao/Journal of Northwestern Polytechnical University 36, no. 4 (August 2018): 656–63. http://dx.doi.org/10.1051/jnwpu/20183640656.

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The estimation of underwater multi-target state has always been the difficult problem of active sonar target tracking.In order to get the variable number of target and their state, the random finite set theory is applied to multi-target tracking system.This theory not only effectively avoids the problem of multi-target tracking data association, and also realizes the estimation of time-varying number of targets and their states.Due to Probability Hypothesis Density(PHD) recursion propagates cardnality distribution with only a single parameter, a new generalization of the PHD recursion called Cardinalized Probability Hypothesis Density(CPHD) recursion, which jointly propagates the intensity function and the cardnality distribution, while have a big computation than PHD.Also there did not have closed-form solution for PHD recursion and CPHD recursion, so for linear Gaussian multi-target tracking system, the Gaussian Mixture Probability Hypothesis Density and Gaussian Mixture Cardinalized Probability Hypothesis Density(GM-CPHD) filter algorithm is put forward.GM-CPHD is more accurate than GM-PHD in estimation of the time-varying number of targets.In this paper, we use the ellipse gate tracking strategy to reduce computation in GM-CPHD filtering algorithm.At the same time, according to the characteristics of underwater target tracking, using active sonar equation, we get the relationship between detection probability, distance and false alarm, when fixed false alarm, analytic formula of the relationship between adaptive detection probability and distance is obtained, we puts forward the adaptive detection probability GM-CPHD filtering algorithm.Simulation shows that the combination of ellipse tracking gate strategy and adaptive detection probability GM-CPHD filtering algorithm can realize the estimation of the time-varying number of targets and their state more accuracy in dense clutter environment.
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Rouseff, Daniel, Scott Schecklman, and Jorge Quijano. "Lisa Zurk’s contributions to striation-based signal processing for active sonar." Journal of the Acoustical Society of America 152, no. 4 (October 2022): A242. http://dx.doi.org/10.1121/10.0016145.

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Strong multipath propagation adds considerable complication to acoustic signal processing in the ocean. When mapped in range-frequency space, the acoustic field exhibits striations, alternating bands of high and low intensity due to constructive and destructive interference between the paths. Nearly forty years ago, Russian scientists showed how this striation pattern could be described by a single scalar parameter, the so-called waveguide invariant that subsequently became a staple of their passive sonar signal processing methods. Lisa Zurk’s contribution was to show how a striation-based approach could be adapted to active sonar processing. Together with her students, she did tank experiments and analysis for monostatic and bistatic configurations. For a horizontal array, she developed a beamformer featuring a linear frequency shift across the array designed to align with high-intensity striations. The result was improved performance in noisy environments. She showed how the waveguide invariant can improve tracking accuracy by providing a constraint on possible tracks. She and her students demonstrated the improved tracking with continuous active sonar data. Lisa Zurk’s innovative work on these topics continues to inspire present day research.
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Mellema, Garfield R. "Improved Active Sonar Tracking in Clutter Using Integrated Feature Data." IEEE Journal of Oceanic Engineering 45, no. 1 (January 2020): 304–18. http://dx.doi.org/10.1109/joe.2018.2870234.

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Blanding, W. R., P. K. Willett, Y. Bar-Shalom, and R. Lynch. "Directed subspace search ML-PDA with application to active sonar tracking." IEEE Transactions on Aerospace and Electronic Systems 44, no. 1 (January 2008): 201–16. http://dx.doi.org/10.1109/taes.2008.4516999.

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Hedgepeth, John B., and Gary E. Johnson. "An active fish tracking split‐beam sonar to study salmon smolt behavior." Journal of the Acoustical Society of America 108, no. 5 (November 2000): 2459. http://dx.doi.org/10.1121/1.4743060.

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Wijesinghe, Lakshitha P., Melville J. Wohlgemuth, Richard H. Y. So, Jochen Triesch, Cynthia F. Moss, and Bertram E. Shi. "Active head rolls enhance sonar-based auditory localization performance." PLOS Computational Biology 17, no. 5 (May 10, 2021): e1008973. http://dx.doi.org/10.1371/journal.pcbi.1008973.

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Animals utilize a variety of active sensing mechanisms to perceive the world around them. Echolocating bats are an excellent model for the study of active auditory localization. The big brown bat (Eptesicus fuscus), for instance, employs active head roll movements during sonar prey tracking. The function of head rolls in sound source localization is not well understood. Here, we propose an echolocation model with multi-axis head rotation to investigate the effect of active head roll movements on sound localization performance. The model autonomously learns to align the bat’s head direction towards the target. We show that a model with active head roll movements better localizes targets than a model without head rolls. Furthermore, we demonstrate that active head rolls also reduce the time required for localization in elevation. Finally, our model offers key insights to sound localization cues used by echolocating bats employing active head movements during echolocation.
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Michalopoulou, Zoi-Heleni. "Tracking in ocean acoustics: Insights from the work of Lisa Zurk." Journal of the Acoustical Society of America 152, no. 4 (October 2022): A243. http://dx.doi.org/10.1121/10.0016148.

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Tracking is of paramount importance in ocean acoustics. One of the goals is the continuous location estimation of moving sources. Tracking needs also arise in identifying the structure of dispersion curves for long-range sound propagation and multipath arrival time identification across vertically separated hydrophones. Zurk’s work has shown that tracking can play a significant role in invariance estimation from striation patterns in spectrograms. We investigated ideas from tracking across the spectrum of ocean acoustics and looked into this latter problem. We found novel approaches for the estimation of the passive and active waveguide invariants, building on a seminal contribution of Lisa Zurk in the field of sonar signal processing.
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Wang, Maofa, Baochun Qiu, Zeifei Zhu, Huanhuan Xue, and Chuanping Zhou. "Study on Active Tracking of Underwater Acoustic Target Based on Deep Convolution Neural Network." Applied Sciences 11, no. 16 (August 17, 2021): 7530. http://dx.doi.org/10.3390/app11167530.

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The active tracking technology of underwater acoustic targets is an important research direction in the field of underwater acoustic signal processing and sonar, and it has always been issued that draws researchers’ attention. The commonly used Kalman filter active tracking (KFAT) method is an effective tracking method, however, it is difficult to detect weak SNR signals, and it is easy to lose the target after the azimuth of different targets overlaps. This paper proposes a KFAT based on deep convolutional neural network (DCNN) method, which can effectively solve the problem of target loss. First, we use Kalman filtering to predict the azimuth and distance of the target, and then use the trained model to identify the azimuth-weighted time-frequency image to obtain the azimuth and label of the target and obtain the target distance by the time the target appears in the time-frequency image. Finally, we associate the data according to the target category, and update the target azimuth and distance information for this cycle. In this paper, two methods, KFAT and DCNN-KFAT, are simulated and tested, and the results are obtained for two cases of tracking weak signal-to-noise signals and tracking different targets with overlapping azimuths. The simulation results show that the DCNN-KFAT method can solve the problem that the KFAT method is difficult to track the target under the weak SNR and the problem that the target is easily lost when two different targets overlap in azimuth. It reduces the deviation range of the active tracking to within 200 m, which is 500~700 m less than the KFAT method.
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Dissertations / Theses on the topic "Active sonar tracking"

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Ljung, Johnny. "Track Before Detect in Active Sonar Systems." Thesis, Uppsala universitet, Signaler och system, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-447314.

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Detection of an underwater target with active sonar in shallow waters such as the Baltic sea is a big challenge. This since the sound beams from the sonar will be reflected on the surfaces, sea surface and sea bottom, and the water volume itself which generates reverberation. Reverberation which will be reflected back to the receiver, is strong in intensity which give rise to many false targets in terms of classifying a target in a surveillance area. These false targets are unwanted and a real target might benefit from these miss-classifications in terms of remaining undetected. It is especially hard if the signal-to-noise ratio (SNR) is approaching zero, i.e. the target strength and the reverberation strength are equal in magnitude. The classical approach to a target detection problem is to assign a threshold value to the measurement, and the data point exceeding the threshold is classified as a target. This approach does not hold for low levels of SNR, since a threshold would not have a statistical significance and could lead to neglecting important data. Track-before-detect (TrBD) is a proposed method for low-SNR situations which tracks and detects a target based on unthresholded data. TrBD enables tracking and detecting of weak and/or stealthy targets. Due to the issues with target detection in shallow waters, the hypothesis of this thesis is to investigate the possibility to implement TrBD, and evaluate the performance of it, when applied on a low-SNR target. The TrBD is implemented with a particle filter which is a recursive Bayesian solution to the problem of integrated tracking and detection. The reverberation data was generated by filtering white noise with an Autoregressive filter of order 1. The target is assigned to propagate according to a constant velocity state space model. Two types of TrBD algorithms are implemented, one which is trained on the background and one which is not. The untrained TrBD is able to track and detect the target but only for levels of SNR down to 4dB. Lower SNR leads to the algorithm not being able to distinguish the target signal from the reverberation. The trained TrBD on the other hand, is able to perform very well for levels of SNR down to 0dB, it is able to track and detect the target and neglect the reverberation. For trajectories passing through areas with high reverberation, the target was lost for a short period of time until it could be retracked again. Overall, the TrBD was successfully implemented on the self-generated data and has a good performance for various target trajectories.
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Westman, Peter, and Mikael Andersson. "Design of behavior classifying and tracking system with sonar." Thesis, Linköping University, Department of Electrical Engineering, 2008. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-11495.

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The domain below the surface in maritime security is hard to monitor with conventional methods, due to the often very noisy environment. In conventional methods the measurements are thresholded in order to distinguish potential targets. This is not always a feasible way of treating measurements. In this thesis a system based on raw measurements, that are not thresholded, is presented in order to track and classify divers with an active sonar. With this system it is possible to detect and track weak targets, even with a signal to noise ratio that often goes below 0 dB.

The system in this thesis can be divided into three parts: the processing of measurements, the association of measurements to targets and the classification of targets. The processing of measurements is based on a particle filter using Track Before Detect (TBD). Two algorithms for association of measurements, Joint Probabilistic Data Association (JPDA) and Highest Probability Data Association (HPDA), have been implemented. The classification of targets is done using an assumed novel approach. The system is evaluated by doing simulations with approximately 8 hours of recorded data, where divers are present at nine different times. The simulations are done a number of times to catch The classification rate is high and the false alarm rate is low.


Undervattensdomänen är svår att övervaka i marina säkerhetssystem med sedvanliga metoder, på grund av den brusiga miljön. I traditionella metoder trösklas mätningarna för att urskilja potentiella mål. Detta är inte alltid ett godtagbart sätt att behandla mätningar på. I den här rapporten presenteras ett system baserat på behandling av rå mätdata, som inte trösklas, för att spåra och klassificera dykare med en aktiv sonar. Med detta system är det möjligt att detektera och spåra svaga mål, trots att signal till brus förhållandet ofta går under 0 dB.

Systemet i den här rapporten kan delas upp i tre delar: behandling av mätningar, association av mätningar till mål samt klassificering av mål. Behandlingen av mätningarna görs med ett partikelfilter som använder Track Before Detect (TBD). Två algoritmer för associering av mätningar, Joint Probabilistic Data Association (JPDA) och Highest Probability Data Association (HPDA), har implementerats. Klassificeringen av mål görs med en egenutvecklad metod som inte har hittats i existerande dokumentation. Systemet utvärderas genom att simuleringar görs på ungefär 8 timmar inspelad data, där dykare är närvarande vid nio olika tillfällen. Simuleringarna görs ett antal gånger för att fånga upp stokastiska beteenden. Andelen lyckade klassificeringar är hög och andelen falsklarm är låg.

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Vu, Han Xuan. "Track-before-detect for active sonar." Thesis, 2015. http://hdl.handle.net/2440/96821.

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The detection and tracking of underwater targets with active sonar is a challenging problem because of high acoustic clutter, fluctuating target returns and a relatively low measurement update rate. In this thesis, a Bayesian framework for the detection and tracking of underwater targets using active sonar is formulated. In general, Bayesian tracking algorithms are built on two statistical models: the target dynamics model and the measurement model. The target dynamics model describes the evolution of the target state with time and is almost always assumed to be a Markov process. The typical measurement model approximates the sensor image with a collection of discrete points at each frame and allows point measurement tracking to be performed. This thesis investigates alternative target and measurement models and considers their application to active sonar tracking. The Markov process commonly used for target modelling assumes that the state evolves without knowledge of its future destination. Random realisations of a Markov process can also display a large amount of variability and do not, in general, resemble realistic target trajectories. An alternative is the reciprocal process, which assumes conditioning on a known destination state. The first key contribution is the derivation and implementation of a Maximum Likelihood Sequence Estimator (MLSE) for a Hidden Reciprocal Process (HRP). The performance of the proposed algorithm is demonstrated in simulated scenarios and shown to give improved state estimation performance over Markov processes for scenarios featuring reciprocal targets. In point measurement tracking, reducing the sensor data to point detections results in the loss of valuable information. This method is generally sufficient for tracking high Signal-to-Noise Ratio (SNR) targets but can fail in the case of low SNR targets. The alternative to point measurement tracking is to provide the sensor intensity map, an image, as an input into the tracker. This paradigm is referred to as Track-Before-Detect (TkBD). This thesis will focus on a particular TkBD algorithm based on Expectation-Maximisation (EM) data association called the Histogram-Probabilistic Multi-Hypothesis Tracker (H-PMHT) as it handles multiple targets with low complexity. In the second key contribution, we demonstrate a Viterbi implementation of the H-PMHT algorithm, and show that it outperforms the Kalman Filter in the linear non-Gaussian case. A problem with H-PMHT is that it fails to model fluctuating target amplitude, which can degrade performance in realistic sensing conditions. The third key contribution addresses this by replacing the multinomial measurement model with a Poisson mixture process. The new Poisson mixture is shown to be consistent with the original H-PMHT modelling assumptions but it now allows for a randomly evolving mean target amplitude state with instantaneous fluctuations. This new TkBD algorithm is referred to as the Poisson H-PMHT. The Bayesian prior on the target state is also modified to ensure more robust performance. The fourth contribution is a novel TkBD algorithm based on the application of EM data association to a new measurement model that directly describes continuous valued intensity maps and avoids using an intermediate quantisation stage like the H-PMHT. This model is referred to as the Interpolated Poisson measurement model and is integrated into the Probabilistic Multi-Hypothesis Tracker (PMHT) framework to derive a TkBD algorithm for continuous data called the Interpolated Poisson-PMHT (IP-PMHT). The performance of the Poisson H-PMHT and IP-PMHT algorithms are verified through simulations and are shown to outperform the standard H-PMHT in terms of SNR estimation, particularly for scenarios featuring targets with highly fluctuating amplitude. The final key contribution is the application of several TkBD algorithms based on EM data association to the active sonar problem through a comparative study using trial data from an active towed array sonar. The TkBD algorithms are modified to incorporate changes in target appearance with received array bearing, and are shown to give improved SNR and state estimation performance compared with a conventional point measurement tracking algorithm. The thesis concludes by discussing the limitations of the proposed algorithms and possible avenues for future work.
Thesis (Ph.D.) -- University of Adelaide, School of Electrical and Electronic Engineering, 2015
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Yocom, Bryan Alan. "Bayesian passive sonar tracking in the context of active-passive data fusion." Thesis, 2009. http://hdl.handle.net/2152/ETD-UT-2009-08-278.

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This thesis investigates the improvements that can be made to Bayesian passive sonar tracking in the context of active-passive sonar data fusion. Performance improvements are achieved by exploiting the prior information available within a typical Bayesian data fusion framework. The algorithms developed are tested against both simulated data and data measured during the SEABAR 07 sea trial. Results show that the proposed approaches achieve improved detection, decreased estimation error, and the ability to track quiet targets in the presence of loud interferers.
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El-Jaber, MOHAMMAD. "Target Tracking in Multi-Static Active Sonar Systems Using Dynamic Programming and Hough Transform." Thesis, 2009. http://hdl.handle.net/1974/2590.

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Tracking multiple targets in a high cluttered environment where multiple receivers are used is a challenging task due to the high level of false alarms and uncertainty in the track hypothesis. The multi-static active sonar scenario is an example for such systems where multiple source-receiver combinations are deployed. Due to the nature of the underwater environment and sound propagation characteristics, tracking targets in the underwater environment becomes a complex operation. Conventional tracking approaches (such as the Kalman and particle filter) require a predetermined kinematic model of the target. Moreover, tracking an unknown and changing number of targets within a certain search area requires complex mathematical association filters to identify the number of targets and associate measurements to different target tracks. As the number of false detections increases, the computational complexity of conventional tracking system grows introducing further challenges for real-time target tracking situations. The methodology presented in this thesis provides a rapid and reliable tracking system capable of tracking multiple targets without depending on a kinematic model of the target movement. In this algorithm, Self Organizing Maps, Dynamic Programming and the Hough transform are combined to produce tracks of possible targets’ paths and estimate of targets’ locations. Evaluation of the performance of the tracking algorithm is performed using three types of simulations and a set of real data obtained from a sea trial. This research documents the results of experimental testing and analysis of the tracking system.
Thesis (Master, Electrical & Computer Engineering) -- Queen's University, 2009-08-07 13:21:06.869
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Chung-Chuan, Huang, and 黃崇鵑. "The Active Tracking Control System Design Of Solar Collector." Thesis, 2010. http://ndltd.ncl.edu.tw/handle/57675547834584586948.

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碩士
中華科技大學
電子工程研究所碩士班
98
In this paper, solar tracking device to control the sun azimuth and elevation control formula and use Matlab/Simulink simulation software to control the directionality of solar panels. Body in a simulated experiment to track the sun position of celestial bodies accuracy and controller design, as the direction of the study. The solar tracker to accurately track the sun, running, generally divided into two kinds of active and passive: passive relying on optical sensor (light-sensitive resistor) is used for sensing the location of the sun the moment, such as sunflower-like plant phototropism of to move, depending on the precision of optical sensors; active path is calculated after the sun by built-in database to track the sun's position, its accuracy depends on the body. The tracking control system programming with Matlab / Simulink simulation written by Matlab / Simulink simulation platform control interface controller, making the overall operation of an organization, and finally man-machine interface with software written to display relevant of time, azimuth and elevation, and tracking platform to control the attitude angles, the simulated and actual tracking error.
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Wang, Hong-Zhou, and 王宏州. "Development of Daylight Catching System for Illumination by Active Solar Tracking." Thesis, 2012. http://ndltd.ncl.edu.tw/handle/6p9746.

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碩士
國立臺北科技大學
冷凍空調工程系所
100
With the increasing awareness of sustainable and green building, more and more people are concerned with the efficiency of energy use at home and at work. A solar tracking skylight illumination system, which enables us to conserve energy by producing increased interior light levels for a longer duration than normally possible, can fit to the above need and have widen been used in the indoor illumination gradually. Tracking sunlight and guide the light indoor as a source of illumination is also a way of energy saving. Daylight catching system, simply put, the light is sunlight, a part of interior when the illumination used; another part of the light is converted to electricity for use. In the self-sufficiency is no need for other power supply, to achieve zero CO2 emissions, a green energy product. Purpose of this study to implement is a way to develop a daylight catching system for illumination. An experimentally investigation is conducted to explore the dynamic illuminative performance of daylight catching system. The daylight catching system drives the sun tracking mechanism by the database of sun-path which is burned in microcontroller. The system will keep working without weather condition. The results show that (1) the triple reflected sunlight can provide sufficient 400~700 Lux to the room from AM 7:00 to PM17:00 without artificial light. (2) The system can be installed not only on the roof of the building, but also on other floors. Mirrors with high reflectivity are used to guide sunlight into the room. So the system can decrease the power consumption of indoor illumination in daytime. (3) With active tracking system, the mechanism can have the best accuracy immediately. The error angle of the mechanism can be less than 2∘. (4)The performance of the system can be seemed as a 27W lamp. The sunshine duration in Taipei (1999~2008) is 1431 hours per year. It means that the system can save 38 kWh per year.
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Liu, Wan-Chi, and 劉琬琪. "ACTIVE SOLAR PANEL DUAL-AXIS SUN TRACKING SYSTEM WITH MAXIMUM POWER POINT TRACKING FUZZY CONTROLLER DESIGN." Thesis, 2009. http://ndltd.ncl.edu.tw/handle/82540205600391715207.

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碩士
大同大學
電機工程學系(所)
97
The purpose of this thesis is to design an active solar panel dual-axis suntracking system with maximum power point tracking fuzzy controller. The tracking system tracks the maximum solar power point no matter what the environmental condition it is and orients the solar panel toward the Sun to enhance the efficiency of thephotovoltaic generation system. First, the operating points of the PV panel are adjusted by a boost converter. The PV voltage and current are measured in real time, and used to estimate the system parameters in the power-voltage polynomial equation and to identify the maximum power. Meanwhile, four light sensors sense one current respectively, which represent the illumination at the time. Inputting the maximum power and four currents to the two fuzzy controllers for dual-axis tracking system, the rotated angles will be got to make the mechanism rotate to the appropriate position. Through the sun tracking method, the PV panel will face the Sun directly at all time. Finally, the simulation results using Matlab verify the effectiveness of the proposed controller.
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YANG, CHI-WEN, and 楊啓文. "Active Push Pull Solar Tracking System Hardware and Software Design and Realization." Thesis, 2011. http://ndltd.ncl.edu.tw/handle/17319172052841560868.

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碩士
中華科技大學
電子工程研究所碩士班
99
Abstract This article is to design, through NI LabVIEW software, the controlling dual-axis solar tracking platform, to enable the platform to automatically track the sun so as to obtain the utmost sunlight energy. Based on the earth orbiting from the sun formula, it will automatically calculate the sun rays to the local horizontal elevation and azimuth information, feed into the tracking platform for control systems, and command the control systems to present the required elevation and azimuth patterns. In the research project, we will design a dual-axis to the push-pull control tracking platform and use the linear actuator (Linear Actuator) to push solar panels, which will result in angle change. The Data Acquisition (DAQ) interface will collect displacement volume; through the LabVIEW control program, it will calculate the driving command, send from the DAQ interface to the linear actuator driver (Driver), impel the platform mechanism, and form an automatic control device in order to achieve the purpose of automatic tracking. This system has been verified through actual operation. The overall structure of hardware and software is feasible. Before the tracking system going to work, we implement a set of 2 axis Accelerometer Module (ADXL 203EB) to control and monitor the solar panel leveling in order to establish the platform initial conditions. Key Words: LabVIEW, ON-OFF Driver, Linear Actuator, Data Acquisition, Solar Tracker, Push-Pull Control Tracking Platform, 2 Axis Accelerometer
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LI, CHIA-HUNG, and 李家宏. "Development of Active Solar Tracking System and Electric Energy Conversion System with MPPT." Thesis, 2018. http://ndltd.ncl.edu.tw/handle/725rx3.

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碩士
聖約翰科技大學
電機工程系碩士班
106
This paper is to develop a real-time sun tracking system with MPPT to improve the electrical efficiency of PV. In the system, the time driven biaxial tracking system is made with PIC16F883 single-chip. The main purpose of the time driven biaxial tracking system is to increase the electrical efficiency of the traditional fixed PV. The core reason why PIC single chip is used as the time driven biaxial tracking system is that the position and angle of the solar light can be calculated quickly and accurately. It is for the purpose of PV can get gabundant sunshine. At the same time, the MPPT controller is used to match the internal resistance of PV to adjust the terminal voltage, so that PV can get good electrical efficiency under different accumulative insolation and temperature conditions. The results of the experiments in this paper will be compared and analyzed.
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Book chapters on the topic "Active sonar tracking"

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Shao, Pengfei, Lei Wang, and Yihui Pan. "Bistatic Active Sonar Bayesian Sequential Automatic Detection and Tracking." In Lecture Notes in Electrical Engineering, 89–99. Singapore: Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-19-3927-3_9.

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Sayeduzzaman, Md, Ashik Mahmud, Keith Chamberlain, and Akashdeep Negi. "Design and Implementation of an Automated Solar Tracking System to Run Utility Systems at Minimal Loads During Load-Shedding by Charging Solar Batteries." In Advances in Transdisciplinary Engineering. IOS Press, 2022. http://dx.doi.org/10.3233/atde221224.

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An Automated Solar Tracker is a piece of equipment with solar panels that automatically follow the sun’s path throughout the day. It makes sure that the panels get the most sunlight possible at all times. When a solar cell faces the sun, and the angle between its surface and its rays is 90 degrees, it makes the most power. Solar tracking makes it possible to get more energy out of the sun because the solar array can always face it. In this paper, a solar tracking system has been designed and built to collect energy from the sun, store it in a battery, and turn it into alternating current (AC) to power minimal utility systems during load-shedding. During this worldwide electricity crisis, this research aims to use as much solar energy as possible through solar panels and store it in batteries with the help of an inverter using the solar tracking system. Nearly 22% of the electricity in Bangladesh had produced by fuel oil- and diesel-powered plants, respectively. Since the price of diesel and fuel has gone up on the international market and many gas-powered power plant has limited gas, this has caused a lot of power outages. So, this research could help people in the middle class, the upper class, industries, or factories that need a backup power source. A servo motor, a pre-programmed Arduino ATMega 328, a Solar inverter, a Solar battery or Battery bank, LDR, 5V Converter, and some 10K resistors had used to build this prototype. Active LDR sensors always keep an eye on the light and move the panel to face the direction where the light is most vital. This research had done for low-power consumed types of equipment. It can use primarily in rural areas. Also, the efficiency of the power collected from the sun is improved using Automated STS (Solar Tracking System).
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Conference papers on the topic "Active sonar tracking"

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Musicki, Darko, Xuezhi Wang, Richard Ellem, and Fiona Fletcher. "Efficient Active Sonar Multitarget Tracking." In OCEANS 2006 - Asia Pacific. IEEE, 2006. http://dx.doi.org/10.1109/oceansap.2006.4393935.

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2

Coraluppi, Stefano, Craig Carthel, David Hughes, Alberto Baldacci, and Michele Micheli. "Multi-waveform active sonar tracking." In 2007 International Waveform Diversity and Design Conference. IEEE, 2007. http://dx.doi.org/10.1109/wddc.2007.4339460.

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3

Lourey, Simon James, and James Lau. "Continuous Active Sonar tracking and correlated measurements." In 6th Underwater Acoustics Conference and Exhibition. ASA, 2021. http://dx.doi.org/10.1121/2.0001465.

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4

Song, Taek, and Da Kim. "Highest Probability Data Association for Active Sonar Tracking." In 2006 9th International Conference on Information Fusion. IEEE, 2006. http://dx.doi.org/10.1109/icif.2006.301804.

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5

LeNoach, Jordan, Michael Lexa, and Stefano Coraluppi. "Feature-Aided Tracking Techniques for Active Sonar Applications." In 2021 IEEE 24th International Conference on Information Fusion (FUSION). IEEE, 2021. http://dx.doi.org/10.23919/fusion49465.2021.9627041.

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6

Wang, J., A. von Trojan, and S. Lourey. "Active sonar target tracking for anti-submarine warfare applications." In OCEANS 2010 IEEE - Sydney. IEEE, 2010. http://dx.doi.org/10.1109/oceanssyd.2010.5603790.

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7

Grimmett, Doug, Doug Abraham, and Ricki Alberto. "Cognitive Active Sonar Tracking for Optimum Performance in Clutter." In 2021 IEEE 24th International Conference on Information Fusion (FUSION). IEEE, 2021. http://dx.doi.org/10.23919/fusion49465.2021.9627029.

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8

Hempel, Christian. "Probabilistic Multi-Hypothesis Tracking for Distributed Multi-Static Active Sonar." In 2006 9th International Conference on Information Fusion. IEEE, 2006. http://dx.doi.org/10.1109/icif.2006.301760.

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9

Seget, K., A. Schulz, and U. Heute. "Multi-Hypothesis Tracking and fusion techniques for multistatic active sonar systems." In 2010 13th International Conference on Information Fusion (FUSION 2010). IEEE, 2010. http://dx.doi.org/10.1109/icif.2010.5711949.

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10

Rao, S. Koteswara. "Maneuvering Target Tracking using Pseudo Linear Estimator with Active Sonar Measurements." In 007 International Conference on Signal Processing, Communications and Networking. IEEE, 2007. http://dx.doi.org/10.1109/icscn.2007.350732.

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