Download or read book Data Association Techniques for Bearings only Multi target Tracking Using Simulated Annealing and Implemented with Boltzmann Machines written by Pei-yih Ting and published by . This book was released on 1992 with total page 340 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Dissertation Abstracts International written by and published by . This book was released on 1992 with total page 860 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Group target Tracking written by Wen-dong Geng and published by Springer. This book was released on 2016-10-01 with total page 175 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book describes grouping detection and initiation; group initiation algorithm based on geometry center; data association and track continuity; as well as separate-detection and situation cognition for group-target. It specifies the tracking of the target in different quantities and densities. At the same time, it integrates cognition into the application. Group-target Tracking is designed as a book for advanced-level students and researchers in the area of radar systems, information fusion of multi-sensors and electronic countermeasures. It is also a valuable reference resource for professionals working in this field.

Download or read book Advanced Data Association Techniques in Multi target Tracking System written by Negm Eldin Mohamed Shawky and published by LAP Lambert Academic Publishing. This book was released on 2012 with total page 212 pages. Available in PDF, EPUB and Kindle. Book excerpt: In multi-target tracking system, data association and tracking filter are two basic parts of tracking objects. The choosing of data association technique to associate the track to the true target in noisy received measurements is an important key to overcome the issues of the tracking process. Many data association algorithms have been developed to be the most powerful techniques for these issues, but still there are disadvantages in their restricting assumptions, complexity and in the resulting performance. For these reasons, some of data association algorithms that are widely used have been studied. These algorithms have some issues during tracking in dense clutter environment, tracking a highly maneuvering targets and swapping in the presence of more background clutter and false signal. Then, these algorithms have been updated to overcome the issues, improve the performance, decrease the burden of the computational cost, decrease the probability of error and to give the targets the ability to continue tracking without failing.

Download or read book Multi sensor Target Tracking written by Jun Ye Yu and published by . This book was released on 2019 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: "Target tracking is a well-studied research topic with a vast array of applications. The basic idea is to track one or more targets of interest using data collected by one or more sensors. While a single sensor may provide enough data, it is more beneficial to establish a network of sensors that collaborate with each other. In this thesis, we study multi-sensor target tracking and present three manuscripts.In the first manuscript, we present a distributed bearings-only single-target particle filter. Unlike the existing literature, the proposed filter incorporates the Earth's curvature in the measurement model to provide more accurate bearing computation. Furthermore, we derive an approximate joint log-likelihood function to reduce the total communication overhead. In the second manuscript, we extend our work in the first manuscript and present two compression algorithms for distributed particle filters. The proposed algorithms construct a graph over the particles and exploit the resulting graph Laplacian matrix to encode the particle log-likelihoods. The proposed algorithms are not limited to any measurement models and can be incorporated in any generic particle filter. We also derive theoretical results showing that the proposed algorithms outperform existing methods at low communication overhead. In the third manuscript, we study data assignment in multi-target tracking. We propose two heuristic but computationally efficient algorithms for multi-sensor multi-target data assignment that can generate a number of likely target-measurement associations. We also implement these algorithms in a generalized labeled multi-Bernoulli filter to validate their performance." --

Download or read book Generalized Data Association for Multitarget Tracking in Clutter written by A. Tchamova and published by Infinite Study. This book was released on with total page 23 pages. Available in PDF, EPUB and Kindle. Book excerpt: The objective of this chapter is to present an approach for target track ing in cluttered environment, which incorporates the advanced concept of generalized data (kinematics and attribute) association (GDA) to improve track maintenance performance in complicated situations (closely spaced and/or crossing targets), when kinematics data are insufficient for correct decision making.

Download or read book American Doctoral Dissertations written by and published by . This book was released on 1991 with total page 724 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Multitarget Tracking in Clutter based on Generalized Data Association Performance Evaluation of Fusion Rules written by J. Dezert and published by Infinite Study. This book was released on with total page 18 pages. Available in PDF, EPUB and Kindle. Book excerpt: The objective of this chapter is to present and compare different fusion rules which can be used for Generalized Data Association (GDA) for multitarget tracking (MTT) in clutter.

Download or read book On Computationally Efficient Frameworks for Data Association in Multi target Tracking written by Sriram Krishnaswamy (Ph. D. in mechanical engineering) and published by . This book was released on 2019 with total page 159 pages. Available in PDF, EPUB and Kindle. Book excerpt: The aim of this dissertation is to examine ways of improving the computational efficiency of data association algorithms in tracking and to do so with better methods to handle data. Data association algorithms are employed in tracking problems in conjunction with an estimation algorithm to determine the optimal state estimate of multiple objects of interest given a set of measurements. This work primarily deals with Bayesian or pseudo-Bayesian paradigms for data association and reduces the computational cost by reducing the exponential growth or the so-called "curse of dimensionality'' in these problems. This increase in the number of hypotheses is exacerbated in dense environments with low signal-to-noise ratio (SNR). This research employs tensor decomposition to reduce the number of incoming measurements into a core tensor or a low-dimensional summary and use it as a substitute for the complete set of measurements.

Download or read book Multitarget Tracking Performance based on the Quality Assessment of Data Association written by Jean Dezert and published by Infinite Study. This book was released on with total page 8 pages. Available in PDF, EPUB and Kindle. Book excerpt: The main objective of this paper is to present, to apply, and to test the effectiveness of the new method, based on belief functions, proposed by Dezert et al. in order to evaluate the quality of the individual association pairings provided in the classical optimal data association solution for improving the performances of multitarget tracking systems in clutter, when some of the association decisions given in the optimal assignment solution are unreliable and doubtful and lead to potentially critical mistake. This evaluation is based on a Monte Carlo simulation for particular difficult maneuvering and nonmaneuvering MTT problems in clutter. A comparison with the results obtained on the base of Kinematic only Data Association and Generalized Data Association is made.

Download or read book Multisensor multitarget Bearing only Sensor Registration written by and published by . This book was released on 2016 with total page 22 pages. Available in PDF, EPUB and Kindle. Book excerpt: Bearing-only estimation is one of the fundamental and challenging problems in target tracking. As in the case of radar tracking, the presence of offset or position biases can exacerbate the challenges in bearing-only estimation. Modeling various sensor biases is not a trivial task and not much has been done in the literature specifically for bearing-only tracking. This paper addresses the modeling of offset biases in bearing-only sensors and the ensuing multitarget tracking with bias compensation. Bias estimation is handled at the fusion node to which individual sensors report their local tracks in the form of associated measurement reports (AMR) or angle-only tracks. The modeling is based on a multisensor approach that can effectively handle a time-varying number of targets in the surveillance region. The proposed algorithm leads to a maximum likelihood bias estimator. The corresponding Cramer-Rao Lower Bound to quantify the theoretical accuracy that can be achieved by the proposed method or any other algorithm is also derived. Finally, simulation results on different distributed tracking scenarios are presented to demonstrate the capabilities of the proposed approach. In order to show that the proposed method can work even with false alarms and missed detections, simulation results on a centralized tracking scenario where the local sensors send all their measurements (not AMRs or local tracks) are also presented.

Download or read book Data Association Algorithms for Multiple Target Tracking written by J. C. McMillan and published by . This book was released on 1990 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Non Cooperative Target Tracking Fusion and Control written by Zhongliang Jing and published by Springer. This book was released on 2018-06-25 with total page 346 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book gives a concise and comprehensive overview of non-cooperative target tracking, fusion and control. Focusing on algorithms rather than theories for non-cooperative targets including air and space-borne targets, this work explores a number of advanced techniques, including Gaussian mixture cardinalized probability hypothesis density (CPHD) filter, optimization on manifold, construction of filter banks and tight frames, structured sparse representation, and others. Containing a variety of illustrative and computational examples, Non-cooperative Target Tracking, Fusion and Control will be useful for students as well as engineers with an interest in information fusion, aerospace applications, radar data processing and remote sensing.

Download or read book Multiple Target Tracking Fast Algorithm for Data Association and State Estimation written by and published by . This book was released on 1995 with total page 75 pages. Available in PDF, EPUB and Kindle. Book excerpt: A unified framework is proposed for providing a systematic scheme for generating the data association hypotheses efficiently in the target- oriented, measurement-oriented, and track-oriented approaches to multitarget tracking. A fast recursive algorithm for computing the a posteriori probabilities, suitable for implementation in a distributed multiprocessor system is developed and its links to the theory of permanents is established. An analysis of this algorithm reveals its superiority over existing ones in the average case. In the related problem of direction-of-arrival estimation, a new non-search-type subspace method, called the PESS method, is proposed. This method exploits the structure of the steering matrix more thoroughly to yield a residual-error theoretically shown to be either less than or equal to that obtained by LS-ESPRIT. Furthermore, simulation conducted on several sets of data showed that the PESS method outperforms the TLS-ESPRIT method. Constraints for forcing all roots of a polynomial to the unit circle are obtained for more reliable estimation especially in the low SNR case. Finally, for improved pre-processing to facilitate tracking, a theoretical analysis is proposed to evaluate the robustness of a TLS algorithm, developed earlier, for image reconstruction from a sequence of undersampled noisy and blurred frames.

Download or read book A Faster Data Assignment Algorithm for Ml Based Multitarget Motion Tracking with Bearings Only Measurements written by Naoyuki Tokuda and published by . This book was released on 2018 with total page 18 pages. Available in PDF, EPUB and Kindle. Book excerpt: We have proved a new rotational sorting algorithm capable of reducing the complexity of data assignment process embedded in the maximum likelihood (ML)-based solution of a multitarget tracking problem from () of the conventional Hungarian type routines to () provided that the bearings-only measurements from an array of passive sensors are free from cluttering and missing data.

Download or read book Multitarget Tracking Using a Neural Network for Data Association written by Ron Abelson and published by . This book was released on 1994 with total page 80 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book The Impact of the Quality Assessment of Optimal Assignment for Data Association in a Multitarget Tracking Context written by J. Dezert and published by Infinite Study. This book was released on with total page 11 pages. Available in PDF, EPUB and Kindle. Book excerpt: The main purpose of this paper is to apply and to test the performance of a new method, based on belief functions, proposed by Dezert et al. in order to evaluate the quality of the individual association pairings provided in the optimal data association solution for improving the performances of multisensormultitarget tracking systems.