Gotowa bibliografia na temat „RADAR recognition process”
Utwórz poprawne odniesienie w stylach APA, MLA, Chicago, Harvard i wielu innych
Zobacz listy aktualnych artykułów, książek, rozpraw, streszczeń i innych źródeł naukowych na temat „RADAR recognition process”.
Przycisk „Dodaj do bibliografii” jest dostępny obok każdej pracy w bibliografii. Użyj go – a my automatycznie utworzymy odniesienie bibliograficzne do wybranej pracy w stylu cytowania, którego potrzebujesz: APA, MLA, Harvard, Chicago, Vancouver itp.
Możesz również pobrać pełny tekst publikacji naukowej w formacie „.pdf” i przeczytać adnotację do pracy online, jeśli odpowiednie parametry są dostępne w metadanych.
Artykuły w czasopismach na temat "RADAR recognition process"
1
Dudczyk, Janusz, i Łukasz Rybak. "Application of Data Particle Geometrical Divide Algorithms in the Process of Radar Signal Recognition". Sensors 23, nr 19 (30.09.2023): 8183. http://dx.doi.org/10.3390/s23198183.
Pełny tekst źródłaStreszczenie:
The process of recognising and classifying radar signals and their radiation sources is currently a key element of operational activities in the electromagnetic environment. Systems of this type, called ELINT class systems, are passive solutions that detect, process, and analyse radio-electronic signals, providing distinctive information on the identified emission source in the final stage of data processing. The data processing in the mentioned types of systems is a very sophisticated issue and is based on advanced machine learning algorithms, artificial neural networks, fractal analysis, intra-pulse analysis, unintentional out-of-band emission analysis, and hybrids of these methods. Currently, there is no optimal method that would allow for the unambiguous identification of particular copies of the same type of radar emission source. This article constitutes an attempt to analyse radar signals generated by six radars of the same type under comparable measurement conditions for all six cases. The concept of the SEI module for the ELINT system was proposed in this paper. The main aim was to perform an advanced analysis, the purpose of which was to identify particular copies of those radars. Pioneering in this research is the application of the author’s algorithm for the data particle geometrical divide, which at the moment has no reference in international publication reports. The research revealed that applying the data particle geometrical divide algorithms to the SEI process concerning six copies of the same radar type allows for almost three times better accuracy than a random labelling strategy within approximately one second.
2
Xing, Huaixi, Qinghua Xing i Kun Wang. "Radar Anti-Jamming Countermeasures Intelligent Decision-Making: A Partially Observable Markov Decision Process Approach". Aerospace 10, nr 3 (27.02.2023): 236. http://dx.doi.org/10.3390/aerospace10030236.
Pełny tekst źródłaStreszczenie:
Current electronic warfare jammers and radar countermeasures are characterized by dynamism and uncertainty. This paper focuses on a decision-making framework of radar anti-jamming countermeasures. The characteristics and implementation process of radar intelligent anti-jamming systems are analyzed, and a scheduling method for radar anti-jamming action based on the Partially Observable Markov Process (POMDP) is proposed. The sample-based belief distribution is used to reflect the radar’s cognition of the environment and describes the uncertainty of the recognition of jamming patterns in the belief state space. The belief state of jamming patterns is updated with Bayesian rules. The reward function is used as the evaluation criterion to select the best anti-jamming strategy, so that the radar is in a low threat state as often as possible. Numerical simulation combines the behavioral prior knowledge base of radars and jammers and obtains the behavioral confrontation benefit matrix from the past experience of experts. The radar controls the output according to the POMDP policy, and dynamically performs the best anti-jamming action according to the change of jamming state. The results show that the POMDP anti-jamming policy is better than the conventional policy. The POMDP approach improves the adaptive anti-jamming capability of the radar and can quickly realize the anti-jamming decision to jammers. This work provides some design ideas for the subsequent development of an intelligent radar.
3
Sun, Jingming, Qiang Zhang, Jingbei Yang i Yuhao Yang. "Automatic Sample Labeling Method for Radar Target Recognition". Journal of Physics: Conference Series 2356, nr 1 (1.10.2022): 012029. http://dx.doi.org/10.1088/1742-6596/2356/1/012029.
Pełny tekst źródłaStreszczenie:
Rapid and accurate recognition of target types is one of the key problems that must be solved to improve radar detection and perception performance. However, the existing radar target recognition technology faces the problems of low efficiency and low quality of sample labeling in practical application. Aiming at the urgent need of automatic sample labeling in radar target recognition, this paper proposes an automatic sample labeling method based on the matching of auxiliary source information and radar track information, which can effectively improve the efficiency and quality of sample labeling in radar target recognition. The experimental results show that the proposed method can effectively label the wide and narrow band data samples required for radar target recognition, and has the advantages of automatic process and high labeling accuracy.
4
Bartsch, A., F. Fitzek i R. H. Rasshofer. "Pedestrian recognition using automotive radar sensors". Advances in Radio Science 10 (18.09.2012): 45–55. http://dx.doi.org/10.5194/ars-10-45-2012.
Pełny tekst źródłaStreszczenie:
Abstract. The application of modern series production automotive radar sensors to pedestrian recognition is an important topic in research on future driver assistance systems. The aim of this paper is to understand the potential and limits of such sensors in pedestrian recognition. This knowledge could be used to develop next generation radar sensors with improved pedestrian recognition capabilities. A new raw radar data signal processing algorithm is proposed that allows deep insights into the object classification process. The impact of raw radar data properties can be directly observed in every layer of the classification system by avoiding machine learning and tracking. This gives information on the limiting factors of raw radar data in terms of classification decision making. To accomplish the very challenging distinction between pedestrians and static objects, five significant and stable object features from the spatial distribution and Doppler information are found. Experimental results with data from a 77 GHz automotive radar sensor show that over 95% of pedestrians can be classified correctly under optimal conditions, which is compareable to modern machine learning systems. The impact of the pedestrian's direction of movement, occlusion, antenna beam elevation angle, linear vehicle movement, and other factors are investigated and discussed. The results show that under real life conditions, radar only based pedestrian recognition is limited due to insufficient Doppler frequency and spatial resolution as well as antenna side lobe effects.
5
Vinogradova, N. S., i L. G. Dorosinsky. "Recognition of radar images generated by synthetic aperture radar systems". Ural Radio Engineering Journal 5, nr 3 (2021): 258–71. http://dx.doi.org/10.15826/urej.2021.5.3.004.
Pełny tekst źródłaStreszczenie:
In the field of radar remote sensing of the Earth, the problem of detecting and / or identifying spatially distributed targets against the background of a homogeneous surface is becoming increasingly important, for example, the tasks of the coast guard, monitoring of unauthorized forest logging, assessing the consequences of natural disasters, and others. This study is devoted to solving the problem of developing the optimal algorithm for making a decision on the class of a spatially distributed target based on data from side-scan radar systems with a synthetic aperture. A detailed description of the signal formation process in the fixed range channel is given, taking into account possible interference factors. Based on the statistical criterion by the method of maximum likelihood, the recognition algorithm is proposed, expressions for the formation of a feature vector are obtained, and the nonparametric decision rule is proposed. The algorithm has been tested on the example of recognizing three classes of spatially distributed targets that differ in size.
6
Lee, Gawon, i Jihie Kim. "Improving Human Activity Recognition for Sparse Radar Point Clouds: A Graph Neural Network Model with Pre-Trained 3D Human-Joint Coordinates". Applied Sciences 12, nr 4 (18.02.2022): 2168. http://dx.doi.org/10.3390/app12042168.
Pełny tekst źródłaStreszczenie:
Many devices have been used to detect human action, including wearable devices, cameras, lidars, and radars. However, some people, such as the elderly and young children, may not know how to use wearable devices effectively. Cameras have the disadvantage of invading privacy, and lidar is rather expensive. In contrast, radar, which is widely used commercially, is easily accessible and relatively cheap. However, due to the limitations of radio waves, radar data are sparse and not easy to use for human activity recognition. In this study, we present a novel human activity recognition model that consists of a pre-trained model and graph neural networks (GNNs). First, we overcome the sparsity of the radar data. To achieve that, we use a model pre-trained with the 3D coordinates of radar data and Kinect data that represents the ground truth. With this pre-trained model, we extract reliable features as 3D human joint coordinate estimates from sparse radar data. Then, a GNN model is used to extract additional information in the spatio-temporal domain from these joint coordinate estimates. Our approach was evaluated using the MMActivity dataset, which includes five different human activities. Our system achieved an accuracy of 96%. The experimental result demonstrates that our algorithm is more effective than five other baseline models.
7
Dong, Xiaoxuan, i Siyi Cheng. "Radar Working Modes Recognition Based on Discrete Process Neural Network". IOP Conference Series: Materials Science and Engineering 394 (8.08.2018): 042088. http://dx.doi.org/10.1088/1757-899x/394/4/042088.
Pełny tekst źródła
8
Yang, Rui, Yingbo Zhao i Yuan Shi. "RPREC: A Radar Plot Recognition Algorithm Based on Adaptive Evidence Classification". Applied Sciences 13, nr 22 (20.11.2023): 12511. http://dx.doi.org/10.3390/app132212511.
Pełny tekst źródłaStreszczenie:
When radar receives target echoes to form plots, it is inevitably affected by clutter, which brings a lot of imprecise and uncertain information to target recognition. Traditional radar plot recognition algorithms often have poor performance in dealing with imprecise and uncertain information. To solve this problem, a radar plot recognition algorithm based on adaptive evidence classification (RPREC) is proposed in this paper. The RPREC can be considered as the evidence classification version under the belief functions. First, the recognition framework based on the belief functions for target, clutter, and uncertainty is created, and a deep neural network model classifier that can give the class of radar plots is also designed. Secondly, according to the classification results of each iteration round, the decision pieces of evidence are constructed and fused. Before being fused, evidence will be corrected based on the distribution of radar plots. Finally, based on the global fusion results, the class labels of all radar plots are updated, and the classifier is retrained and updated so as to iterate until all the class labels of radar plots are no longer changed. The performance of the RPREC is verified and analyzed based on the real radar plot datasets by comparison with other related methods.
9
Feng, Xiang, Zhengliang Shan, Zhanfeng Zhao, Zirui Xu, Tianpeng Zhang, Zihe Zhou, Bo Deng i Zirui Guan. "Millimeter-Wave Radar Monitoring for Elder’s Fall Based on Multi-View Parameter Fusion Estimation and Recognition". Remote Sensing 15, nr 8 (16.04.2023): 2101. http://dx.doi.org/10.3390/rs15082101.
Pełny tekst źródłaStreszczenie:
Human activity recognition plays a vital role in many applications, such as body falling surveillance and healthcare for elder’s in-home monitoring. Instead of using traditional micro-Doppler signals based on time-frequency distribution, we turn to another way and use the Relax algorithm to process the radar echo so as to obtain the required parameters. In this paper, we aim at the multi-view idea in which two radars at different views work synchronously and fuse the features extracted from each radar, respectively. Furthermore, we discuss the common estimated time-frequency features and time-varying spatial features of multi-view radar-echo and then formulate the parameters matrix via principal component analysis, and finally transform them into the machine learning classifiers to make further comparisons. Simulations and results show that our proposed multi-view parameter fusion idea could lead to relative-high accuracy and robust recognition performance, which would provide a feasible application for future human–computer monitoring scenarios.
10
Zhyrnov, V., i S. Solonska. "Intelligent model of radar object images for surveillance radars". Radiotekhnika, nr 212 (28.03.2023): 148–54. http://dx.doi.org/10.30837/rt.2023.1.212.14.
Pełny tekst źródłaStreszczenie:
The results of developing an intelligent model of radar object images for surveillance radars are presented. The relevance of this work deals with the development of algorithm for automatic processing images of radar objects that provide effective detection of weak true signals due to the accumulation of signal and logical information in the analyzed cell and in its surroundings under interferences. The improvement of air safety tools and the automation of air traffic management processes require effective procedures to process signal information. The issues of more complete use and qualitative improvement of the information-processing capabilities of control systems are also topical, especially in difficult conditions of interfering signals. The basis of this study is the idea of using an intellectual model of radar object images for automatic decision-making on detection and recognition of radar objects, built on the space of semantic features. The main result is optical object recognition, similar to how an expert can easily recognize aerial objects and their types when viewing radar object images. Based on semantic features intelligent model of radar object images has been developed, which makes it possible to effectively detect and classify aerial objects. It is worth noting that the characteristic description of intelligent model of radar object images for point, extended, moving and stationary radar objects is the mathematical description of procedures and relationships at perception and analysis of signals in the form of distinguishing features or properties. As a result, various virtual images of radar object are generated in the form of spatial-semantic and spectral-semantic models. The main features and structural elements of the model are given. It is shown that the advantages of this model are related to the possibility of characteristic description of the radar object images using the algebra of finite predicates.
Rozprawy doktorskie na temat "RADAR recognition process"
1
Mottier, Manon. "Optimal Transport : an application to the RADAR Recognition Process for deinterleaving RADAR pulses and identifying emitter". Electronic Thesis or Diss., université Paris-Saclay, 2024. https://theses.hal.science/tel-04653381.
Pełny tekst źródłaStreszczenie:
Le renseignement militaire est un aspect essentiel pour la sécurité et la défense d'un pays, notamment le renseignement d'origine électromagnétique (ROEM). L'émergence des systèmes passif a permis de donner un avantage considérable aux acteurs capables de les maitriser en permettant une surveillance discrète et à moindre coût. Néanmoins, l'interception et le traitement des signaux par un RADAR passif nécéssitent la mise en place d'une chaine de traitement algorithmique dédiée, capable de comprendre la diversité des spectres électromagmétiques ainsi que les phénomènes physiques sous-jacents. Au fil des années, les enjeux se sont complexifiés et diversifiés notamment à cause de nombreuses innovations technologiques qui ont conduit à la complexification et de la sophistication des équipements électroniques; les RADARs ont des spectres électromagnétiques plus similaires rendant leur différenciation complexe. Ces travaux proposent un Processus de Reconnaissance RADAR permettant dans un premier temps de désentrelacer un signal puis d'identifier les RADARs. Tout d'abord deux nouvelles approches de désentrelacement non supervisées sont proposées, basées sur une combinaison d'algorithmes de clustering intégrant des distances de transport optimal afin de séparer les impulsions en plusieurs clusters avant de les regrouper les clusters appartenant à un même RADAR. Enfin, lorsque la phase de désentrelacement est terminée, l'identification des RADARs est faite à partir de l'élaboration d'une distance de transport optimal entre une base de données de référence et les ensembles d'impulsions précédemment désentrelacés tout en modélisant le phénomène d'impulsions manquantesMilitary intelligence is essential to a country's security and defense, particularly signals intelligence (ROEM). The emergence of passive systems has given a considerable advantage to those capable of controlling them by allowing discreet surveillance at a lower cost. However, the interception and processing of signals by a passive RADAR require establishing a dedicated algorithmic processing chain capable of understanding the diversity of electromagnetic spectra and the underlying physical phenomena. Over the years, the issues have become more complex and diversified, mainly because of numerous technological innovations that have led to the complexity and sophistication of electronic equipment; RADARs have more similar electromagnetic spectra, making their differentiation complex. This work proposes a RADAR Recognition Process first to deinterleave a signal and then to identify the RADARs. First, two new unsupervised deinterleaving approaches are proposed based on a combination of clustering algorithms integrating optimal transport distances to separate the pulses into several clusters before grouping the clusters belonging to the same RADAR. Finally, when the deinterleaving phase is completed, the RADARs are identified by developing an optimal transport distance between a reference database and the sets of previously deinterleaved pulses while modeling the phenomenon of missing pulses
2
Menon, K. Rajalakshmi. "Application Of High Frequency Natural Resonances Extracted From Electromagnetic Scattering Response For Discrimination Of Radar Targets With Minor Variations". Thesis, Indian Institute of Science, 2001. https://etd.iisc.ac.in/handle/2005/159.
Pełny tekst źródłaStreszczenie:
Radars, as the name suggests, were traditionally used for Radio Detection and Ranging. Nevertheless, advances in high resolution electromagnetic simulations, Ultra Wide-Band sources, signal processing and computer technologies have resulted in a possible perception of radars as sensors for target discrimination. In this thesis, the feasibility of discrimination between targets even with minor variations in structure and material composition on the basis of radar echoes is effectively demonstrated.
It is well-known that the echoes from any target are affected by its natural frequencies which are dependent only on the shape and material composition of the target, and independent of the aspect angle or the incident waveform. The E-pulse technique is based on the fact that incident waveforms can be designed that uniquely annihilate the echoes from chosen regions of a target, and forms the basis of the method of discrimination proposed in this thesis.
Earlier methods reported in the literature, effectively discriminated only between different classes of targets with substantial variations in the overall dimensions of the body. Discrimination of targets of the same class with a minor structural modification or with a material coating on specific areas was rather difficult. This thesis attempts and successfully validates a method which comprehensively addresses this problem. The key idea of this method is to use the higher frequency resonances (which characterise the finer details of a target) in the E-pulse technique.
An obviously important aspect of target discrimination is therefore that of precisely estimating the natural frequencies for each target and understanding the changes in these frequencies, and their associations with the changes in structure and material composition. Current approaches to determine these frequencies are either based In the time or frequency
domains. While the latter approach comprises the computation of the roots of a related determinantal equation, in the time domain, the natural frequencies are extracted from the
response of a target to an impulse. Such a response can either be generated from actual experiments or by simulating the scattering response using Computational Electromagnetic (CEM) techniques. In this work, the impulse response is obtained from the frequency response of the scatterers in the frequency range of interest. Since no single CEM technique can effectively cover the entire range of frequencies needed for the E-Pulse synthesis. The Method of Moments and Physical Optics have been used for low and high frequency scattering respectively. The results obtained using the latter technique are validated by comparing with those obtained using Method of Moments at the transition frequencies and Geometrical Theory of Diffraction (GTD).
The natural frequencies (i.e., poles of a corresponding transfer function) are extracted from the impulse response using Prony's algorithm. One of the parameters in this method is the number of such poles (i.e.. the order of the transfer function) present in the response, and the accuracy of the computed pole values depends on this assumed order. Here, the Hankel singular values of a transfer function is used to estimate the number of poles. This in turn implies that a specific norm of the error between a transfer function corresponding to the frequency response generated earlier, and a transfer function with an assumed order obtained using Prony's method is minimised.
In the thesis, a wide range of target shapes are considered for purposes of illustration: wires, cylinders, spheres, plates and complex bodies such as aircraft, and the discrimination capability is demonstrated by introducing minor perturbations in their shape and/or material composition. .The following cases are considered here: (a) Wires: Conducting wires with a protrusion in one segment; conducting wire from another coated with a dielectric in a segment, (b) Cylinders: Conducting cylinders with one perturbed; conducting cylinders with a portion scrapped off in the middle, (c) Plates: Conducting plates with a elongation on one comer; conducting plate with another one with a hole in the centre, (d) Spheres: Conducting spheres with different radii; conducting spheres with Radar Absorbing Material coated spheres with different coating thickness; conducting spheres with chiral coated spheres with varying coating thickness, (e) Aircraft: Canonical model of MiG-29 aircraft from a similar one with stores placed under the wing.
3
Menon, K. Rajalakshmi. "Application Of High Frequency Natural Resonances Extracted From Electromagnetic Scattering Response For Discrimination Of Radar Targets With Minor Variations". Thesis, Indian Institute of Science, 2001. http://hdl.handle.net/2005/159.
Pełny tekst źródłaStreszczenie:
Radars, as the name suggests, were traditionally used for Radio Detection and Ranging. Nevertheless, advances in high resolution electromagnetic simulations, Ultra Wide-Band sources, signal processing and computer technologies have resulted in a possible perception of radars as sensors for target discrimination. In this thesis, the feasibility of discrimination between targets even with minor variations in structure and material composition on the basis of radar echoes is effectively demonstrated.
It is well-known that the echoes from any target are affected by its natural frequencies which are dependent only on the shape and material composition of the target, and independent of the aspect angle or the incident waveform. The E-pulse technique is based on the fact that incident waveforms can be designed that uniquely annihilate the echoes from chosen regions of a target, and forms the basis of the method of discrimination proposed in this thesis.
Earlier methods reported in the literature, effectively discriminated only between different classes of targets with substantial variations in the overall dimensions of the body. Discrimination of targets of the same class with a minor structural modification or with a material coating on specific areas was rather difficult. This thesis attempts and successfully validates a method which comprehensively addresses this problem. The key idea of this method is to use the higher frequency resonances (which characterise the finer details of a target) in the E-pulse technique.
An obviously important aspect of target discrimination is therefore that of precisely estimating the natural frequencies for each target and understanding the changes in these frequencies, and their associations with the changes in structure and material composition. Current approaches to determine these frequencies are either based In the time or frequency
domains. While the latter approach comprises the computation of the roots of a related determinantal equation, in the time domain, the natural frequencies are extracted from the
response of a target to an impulse. Such a response can either be generated from actual experiments or by simulating the scattering response using Computational Electromagnetic (CEM) techniques. In this work, the impulse response is obtained from the frequency response of the scatterers in the frequency range of interest. Since no single CEM technique can effectively cover the entire range of frequencies needed for the E-Pulse synthesis. The Method of Moments and Physical Optics have been used for low and high frequency scattering respectively. The results obtained using the latter technique are validated by comparing with those obtained using Method of Moments at the transition frequencies and Geometrical Theory of Diffraction (GTD).
The natural frequencies (i.e., poles of a corresponding transfer function) are extracted from the impulse response using Prony's algorithm. One of the parameters in this method is the number of such poles (i.e.. the order of the transfer function) present in the response, and the accuracy of the computed pole values depends on this assumed order. Here, the Hankel singular values of a transfer function is used to estimate the number of poles. This in turn implies that a specific norm of the error between a transfer function corresponding to the frequency response generated earlier, and a transfer function with an assumed order obtained using Prony's method is minimised.
In the thesis, a wide range of target shapes are considered for purposes of illustration: wires, cylinders, spheres, plates and complex bodies such as aircraft, and the discrimination capability is demonstrated by introducing minor perturbations in their shape and/or material composition. .The following cases are considered here: (a) Wires: Conducting wires with a protrusion in one segment; conducting wire from another coated with a dielectric in a segment, (b) Cylinders: Conducting cylinders with one perturbed; conducting cylinders with a portion scrapped off in the middle, (c) Plates: Conducting plates with a elongation on one comer; conducting plate with another one with a hole in the centre, (d) Spheres: Conducting spheres with different radii; conducting spheres with Radar Absorbing Material coated spheres with different coating thickness; conducting spheres with chiral coated spheres with varying coating thickness, (e) Aircraft: Canonical model of MiG-29 aircraft from a similar one with stores placed under the wing.
Części książek na temat "RADAR recognition process"
1
Mahmoudi, Elham, Jan Düllmann, Lukas Heußner, Raoul Hölter, Andre Lamert, Shorash Miro, Thomas Möller i in. "Advance Reconnaissance and Optimal Monitoring". W Interaction Modeling in Mechanized Tunneling, 9–91. Cham: Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-24066-9_2.
Pełny tekst źródłaStreszczenie:
AbstractEffective exploration techniques during mechanized tunneling are of high importance in order to prevent severe surface settlements as well as a damage of the tunnel boring machine, which in turn would lead to additional costs and a standstill in the construction process. A seismic methodology called full waveform inversion can bring a considerable improvement compared to state-of-the-art seismic methods in terms of precision. Another method of exploration during mechanized tunneling is to continuously monitor subsurface behavior and then use this data to identify disturbances through pattern recognition and machine learning techniques. Various probabilistic methods for conducting system identification and proposing an appropriate monitoring plan are developed in this regard. Furthermore, ground conditions can be determined by studying boring machine data collected during the excavation. The active and passive obtained data during performance of a shield driven machine were used to estimate soil parameters. The monitoring campaign can be extended to include above-ground structural surveillance as well as terrestrial and satellite data to track displacements of existing infrastructure caused by tunneling. The available radar data for the Wehrhahn-line project are displayed and were utilized to precisely monitor the process of anticipated uplift by injections and any subsequent ground building settlements.
2
Estrada, Jheanel, Gil Opina Jr i Anshuman Tripathi. "Object and Traffic Light Recognition Model Development Using Multi-GPU Architecture for Autonomous Bus". W Frontiers in Artificial Intelligence and Applications. IOS Press, 2021. http://dx.doi.org/10.3233/faia210286.
Pełny tekst źródłaStreszczenie:
The autonomous vehicle is both an exciting yet complex field to dig in these past few years. Many have ventured out to develop Level 4 Autonomous Vehicle but up to this point, many issues were still arising about its safety, perception and sensing capabilities, tracking, and localization. This paper aims to address the struggles of developing an acceptable model for object detection in real-time. Object detection is one of the challenging areas of autonomous vehicles due to the limitations of the camera, lidar, radar, and other sensors, especially during night-time. There were various datasets and models available, but the number of samples, the labels, the occlusions, and other factors may affect the performance of the dataset. To address the mentioned problem, this study has undergone a rigorous process of scene selection and imitation to deal with the imbalance dataset, applied the state-of-the-art YOLO architecture for the model development. After the development process, the model was deployed in a multi-GPU architecture that lessens the computational load on a single GPU structure and was tested on a 12-meter fully electric autonomous bus. This study will lead to the development of a usable and safe autonomous bus that will lead the future of public transportation.
3
Peralta, Dan-el Padilla. "Pilgrimage to Mid-Republican Rome". W Divine Institutions, 178–229. Princeton University Press, 2020. http://dx.doi.org/10.23943/princeton/9780691168678.003.0005.
Pełny tekst źródłaStreszczenie:
This chapter examines the relationship between religiously motivated mobility and the exchange of knowledge and information, using quantitative models and social network analysis. It argues that pilgrimage to participate in cult at Rome was yet another lever by which the mid-Republican res publica bootstrapped itself into statehood. The burnishing of Rome's credentials as a destination for pilgrimage followed closely on the heels of the cresting popularity of a specific brand of religious observance in mid-Republican central Italy, the healing cults that “formed a religious infrastructure that transcended political boundaries.” Although the interaction between premodern state formation and intercultural pilgrimage has surfaced on the radar of scholars working in other periods and regions, few studies of the middle Republic grant much space or recognition to this cultural process. However, mid-Republican Rome was not unlike other imperial cities in its reliance on monumentality to elicit and sustain waves of pilgrimage. The chapter then identifies where in the material record these waves can be detected and their impact gauged.
4
Zhang, Suyu, Wenlong Zhao, Liang Guo, Ruijun Liu i Jun Liu. "Autonomous Driving System for Mining UGVs". W Advances in Transdisciplinary Engineering. IOS Press, 2024. http://dx.doi.org/10.3233/atde231117.
Pełny tekst źródłaStreszczenie:
Addressing the challenge of autonomous navigation for mining Unmanned Ground Vehicles (UGVs) in mining environments, this paper introduces a comprehensive navigation framework tailored to bumpy terrains, integrating improved obstacle recognition with localized obstacle avoidance techniques. The algorithmic realization of this framework involves four key stages. The first stage involves 3D mapping and localization of the environment. It is achieved through the fusion of a radar LiDAR-Visual Inertial SLAM System (LVI-SAM) and Monte Carlo Localization (MCL) algorithms. In the next stage, dense global paths are generated using Plane Fitting Rapidly Expanded Random Tree (PF-RRT*) and Gaussian Process Regression (GPR). In the third stage, an improved Density-Based Spatial Clustering of Applications with Noise (DBSCAN*) is employed to address the obstacles around the UGV, and these obstacles are encapsulated using adaptive cylindrical envelopment. In the final stage, an Adaptive Control Barrier Function (A-CBF) is proposed to be used in combination with Model Predictive Control (MPC) to aid in dynamic obstacle avoidance and global trajectory tracking. The algorithmic framework’s effectiveness is confirmed through simulation experiments in the Gazebo software and real-world navigation tests conducted in mining environments, with the results exhibiting the UGV’s precise target-reaching abilities.
Streszczenia konferencji na temat "RADAR recognition process"
1
Dankert, Heiko, Jochen Horstmann i Wolfgang Rosenthal. "Detection of Extreme Waves in SAR Images and Radar-Image Sequences". W ASME 2002 21st International Conference on Offshore Mechanics and Arctic Engineering. ASMEDC, 2002. http://dx.doi.org/10.1115/omae2002-28160.
Pełny tekst źródłaStreszczenie:
Extreme waves are often enclosed by other waves which are also higher than the average. These wave groups have to be taken into account for instance for the design of offshore platforms, breakwaters or ships, because successive high waves can cause more damage on those structures than the same waves separated by smaller waves. Further they can excite the resonance frequencies of moored structures like platforms due to non-linear effects or cause capsize. They are therefore of interest for engineers and scientists (e.g. Goda 1983). A method is presented to localize wave groups spatial and spatio-temporal utilizing synthetic aperture radar (SAR) images and nautical radar-image sequences. The approach to detect wave groups is based on the detection of the wave envelope. It is assumed that the sea surface elevation can be treated as a Gaussian process. The method is applied to SAR images acquired by the European satellite ERS-1 and to radar-image sequences recorded by tower-based nautical radars. In contrast to 1D sensors like buoys the SAR records an image and gives therefore a 2D description of the sea surface by measuring the radar backscatter from the sea surface. The measurements taken by a nautical radar provide the possibility to record time series of images and therefore to get a 3D description of the sea surface. Radar-image sequences are acquired by recording the spatial and temporal evolution of the sea surface backscatter, which is modulated through the surface wave field. Nautical radar-image sequences allow to detect wave groups within a time span that makes it possible to start safety programs before the group reaches a platform. The existing data sets are exploited with respect to the recognition of extreme wave events.
2
Mattei, F. "Enhanced radar detection of small remotely piloted aircraft in U-space scenario". W Aerospace Science and Engineering. Materials Research Forum LLC, 2023. http://dx.doi.org/10.21741/9781644902677-3.
Pełny tekst źródłaStreszczenie:
Abstract. Efficient and safe integration of Unmanned Aerial Systems, both civil and military ones, must be guaranteed in the airspace, which is expected to be threated by problems of collisions, loss of communications and congestion of the air traffic environment. One of the main issues is how to improve the identification of unmanned aircrafts in the low altitude airspace. The identification process, that includes detection, verification, and recognition phases, is affected by different problems such as the difficulty of distinguishing Unmanned Aircraft Vehicles from other small flying objects as birds, because of their similar Radar Cross Section (RCS). To improve this process, an enhancement of the RCS can be a solution. The purpose of my PhD is to find the best passive and active solution for the following assignment.
3
Jinzhu Wang, Jinzhu Wang, Jie Bai Jie Bai, Libo Huang Libo Huang i Huanlei Chen Huanlei Chen. "Autonomous Driving Decision-making Based on the Combination of Deep Reinforcement Learning and Rule-based Controller". W FISITA World Congress 2021. FISITA, 2021. http://dx.doi.org/10.46720/f2021-acm-108.
Pełny tekst źródłaStreszczenie:
As autonomous vehicles begin to drive on the road, rational decision making is essential for driving safety and efficiency. The decision-making of autonomous vehicles is a difficult problem since it depends on the surrounding dynamic environment constraints and its own motion constraints. As the result of the combination of deep learning (DL) and reinforcement learning (RL), deep reinforcement learning (DRL) integrates DL's strong understanding of perception problems such as visual and semantic text, as well as the decision-making ability of RL. Hence, DRL can be used to solve complex problems in real scenarios. However, as an end-to-end method, DRL is inefficient and the final result tend to be poorly robust. Considering the usefulness of existing domain knowledge for autonomous vehicle decision-making, this paper uses domain knowledge to establish behavioral rules and combine rule-based behavior strategies with DRL methods, so that we can achieve efficient training of autonomous vehicle decision-making models and ensure the vehicle to chooses safe actions under unknown circumstances. First, the continuous decision-making problem of autonomous vehicles is modeled as a Markov decision process (MDP). Taking into account the influence of unknown intentions of other road vehicles on self-driving decisions, a recognition model of the behavioral intentions of other vehicles was established. Then, the linear dynamic model of the conventional vehicle is used to establish the relationship between the vehicle decision-making behavior and the motion trajectory. Finally, by designing the reward function of the MDP, we use a combination of RL and behavior rules-based controller, the expected driving behavior of the autonomous vehicle is obtained. In this paper, the simulation environment of scenes of intersections in urban roads and highways is established, and each situation is formalized as an RL problem. Meanwhile, a large number of numerical simulations were carried out, and the comparison of our method and the end-to-end form of DRL technology were discussed. "Due to its robust operation and high performance during bad weather conditions and overnight as well as the ability of using the Doppler Effect to measure directly the velocity of objects, the radar sensor is used in many application fields. Especially in automotive many radar sensors are used for the perception of the environment to increase the safety of the traffic. To increase the security level especially for vulnerable road users (VRU’s) like pedestrians or cyclists, radar sensors are used in driver assistance systems. Radar sensors are also used in the infrastructure, e.g. a commercial application is the detection of cars and pedestrians to manage traffic lights. Furthermore, radar sensors installed in the infrastructure are used in research projects for safeguarding future autonomous traffic. The object recognition and accuracy of radar-based sensing in the infrastructure can be increased by cooperating radar systems, which consist out of several sensors. This paper focus on the data fusion method of two radar sensors to increase the performance of detection and localization. For data fusion the high level cluster data of the two radar sensors are used as input data in a neuronal net (NN) structure. The results are compared to the localization obtained by using only a single radar sensor operating with an ordinary tracking algorithm. First, different models for chosen region of interests (ROI) and operating mode of cooperative sensors are developed and the data structure is discussed. In addition, the data are preprocessed with a coordinate transformation and time synchronization for both sensors, as well as the noise filtering to reduce the amount of clusters for the algorithm. Furthermore, three NN structures (CNN, DNN and LSTM) for static + dynamic objects and only dynamic objects are created, trained and discussed. Also, based on the results further improvements for the NN performance will be discussed."
4
Khadr, N., D. O. Pederson, G. J. Salamo i B. A. Weber. "Symmetry perception by optical transformation". W OSA Annual Meeting. Washington, D.C.: Optica Publishing Group, 1987. http://dx.doi.org/10.1364/oam.1987.mm5.
Pełny tekst źródłaStreszczenie:
Real-time optical processors have long been recognized for such potential applications as optical computing, robotic vision, radar signal processing, and pattern recognition. In particular, optical processors offer a powerful alternative to electronic processors due to their ability to process in parallel a large amount of spatial information and to perform at extremely high speeds a large number of spatial operations. One example of a real-time optical processor is a simple modification of an early optical correlator proposed by VanderLugt. In a modern version of the VanderLugt processor film is replaced by a photorefractive nonlinear optical medium. The advantage of the crystal approach over traditional wet-chemical processing is that the correlation between different scenes is carried out in real time and not limited by the time needed for development or film replacement. Despite the success of modern correlators, however, they are hampered by an old but severe limitation for practical application. Even the modern correlator has not overcome the inability of traditional correlators to recognize an object independent of its size or the viewed perspective.
5
Konopko, Mariola, i Małgorzata Ewa Wysocka. "GPR Method as a Non-Invasive Method for Investigating Organic Soils Deposited under Designed Road Construction". W Environmental Engineering. VGTU Technika, 2017. http://dx.doi.org/10.3846/enviro.2017.140.
Pełny tekst źródłaStreszczenie:
GPR method is a non-invasive technique for ground exploration which detects subsurface objects and assesses their presence, as well as provides information about the geological structure of investigation site. Ground penetrating radar method belongs to the group of geophysical methods as it uses electromagnetic waves. GPR technique takes advantage of the differences between the dielectric constants, specific for the material under analysis. One of the factors that are essential to record reliable data is a clear contrast between the dielectric constant of investigated object and its surroundings. One of the major advantages of GPR is that it does not damage ground surface as well as it is completely non-invasive and safe for the environment. Moreover, the method is particularly useful in the design and realisation process of linear objects, for among the multiple aspects of its utilization there is recognition of low-bearing organic soils. The discontinuous nature of traditional methods makes it difficult to precisely specify ground layering as well as accurately locate potential anomalies. The analysis carried out in this study shows that GPR technique can detect the boundaries of soil layers, which considerably simplifies ground assessment.
6
Bacsardi, Laszlo, i Laszlo Csurgai Horvath. "Establishment of the Space Engineering Program in Hungary". W Symposium on Space Educational Activities (SSAE). Universitat Politècnica de Catalunya, 2022. http://dx.doi.org/10.5821/conference-9788419184405.068.
Pełny tekst źródłaStreszczenie:
The Hungarian space age started in 1946 with the successful Lunar Radar experiment by Zoltán Bay. In the past 75 years, the Hungarian space sector evolved and grew dramatically, achieving international recognition in space communications, material science, picosatellites, dosimetry, and many more domains. However, there was no space engineering related higher education program in the country. After hosting the 2nd Symposium on Space Educational Activities in 2018 in Budapest, there was an emerging need for starting a space program for engineering students. A summer workshop organized by the Hungarian Astronautical Society in 2018 fostered further the process, and the Budapest University of Technology and Economics (BME) officially initialized the establishment of the space engineering master curriculum in 2019. By the end of 2020, the relevant ministry approved the national space engineering master curriculum. This means that every Hungarian university, which has the necessary competences, can start a space engineering program for their students. In early 2021, the BME Faculty of Electrical Engineering and Informatics at BME requested approval for its space engineering master program. In October 2021, the relevant body approved the program, allowing the first class of space engineering students to arrive to the university in September 2022. The Hungarian space engineering master curriculum is a 2-year-long master program for 120 credits (in the European Credit Transfer and Accumulation System, ECTS). The master's program at the Budapest University of Technology and Economics has 26 subjects and a 4-week-long industrial training. We outline the establishment process of the national space engineering curriculum and introduce the curriculum of BME
7
Li, Yixiao, Yutaka Matsubara, Daniel Olbrys, Kazuhiro Kajio, Takashi Inada i Hiroaki Takada. "Agile Software Design Verification and Validation (V&V) for Automated Driving". W FISITA World Congress 2021. FISITA, 2021. http://dx.doi.org/10.46720/f2020-ves-017.
Pełny tekst źródłaStreszczenie:
Automated Driving System (ADS) generally consists of 3 functions 1) Recognition, 2) Planning, 3) Control. Precise vehicle localization and accurate recognition of objects (vehicle, pedestrian, lane, traffic sign, etc.) are typically based on high-definition dynamic maps and data from multiple sensors (e.g. Camera, LiDAR, Radar). Planners, especially those for optimal path and trajectory, tend to be computationally intensive. Many applications in ADS use machine learning techniques such as DNN (Deep Neural Network), which further increase the demand for computing power. To parallelly process massive tasks and data in real-time, scalable software and high-performance SoC (System on Chip) with many CPUs or processing cores, and hardware accelerators (e.g. GPU, DLA) have been adopted. However, ADS software and SoC hardware architecture are so large and complex that software validation at later testing phase is inefficient and costly. Due to continuous ADS software evolution and iterations, software redesign will occur much more frequently than traditional automotive systems. The productivity of software validation must be improved to avoid the unacceptable bloat of required effort and time. This paper explores how to obtain optimal ADS software scheduling design and how to enable agile ADS software V&V (Verification and Validation) in order to release the product in short development cycle. The proposed agile software V&V framework integrates the design verification with scheduling simulator in PC and the validation with debugging and tracing tools for the hardware target, which is usually an embedded board. We developed utility tools to make the proposed framework seamless and automated. The evaluation results indicate that the proposed framework can efficiently explore the optimal scheduling design (e.g. scheduling policy, thread priority, core affinity) satisfying several non-functional requirements (e.g. response time, CPU utilization) for ADS. We also proved that the framework is practical and can be incorporated into agile ADS software development by validating it through the project. Key words: - Automated Driving System (ADS) - System on Chip (SOC) - Deep Neural Network (DNN) - Optimal Scheduling Design - Verification and Validation (V&V)