Search - kalman pda

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[Special Effects] pdaf-demo DL : 0: Probabilistic Data Association Filter跟踪算法示例-Probabilistic Data Association Filter Tracking Algorithm example
Update : 2025-04-26 Size : 3kb Publisher : liushan
[Graph Recognize] PDA DL : 0: 一种用于多目标跟踪的改进PDA算法，北京理工大学学报上面的文章，、概率数据关联滤波(p robab ility data associat ion f ilter, PDA )-A multi-target tracking algorithm improvements PDA, Beijing Institute of Technology Journal of the above articles, probabilistic data association filter (p robab ility data associat ion f ilter, PDA)
Update : 2025-04-26 Size : 132kb Publisher : 孟钢
[AI-NN-PR] AnalgorithmSTFPDAforManeuveringTargetTracking DL : 0: 一种实现机动目标跟踪的STF动态模型PDA算法我存的一篇论文，拿来与大家共享-An algorithmSTF-PDAhas been presented based on the strongtracking filterwith dynamicallymodifying structure of model.The performance of probability data association (PDA) can be improved by this algorithm.The theoretic analysis shows the al- gorithm is superiortothe PDAwithKalman or extented Kalman filter.Comparedwiththe latter one on simulations the simulations show that this new algorithm is more effective.
Update : 2025-04-26 Size : 38kb Publisher : dailu
[Other] ekfekfPDA DL : 1: Bearing Only Tracking在多场景下的仿真程序是本人在国外读书时研究项目中的导师和同事等共同开发使用EKF(扩展KALMAN Filter)与PDA联合算法对target进行定位追踪-Bearing Only Tracking in a multi-scenario is the simulation program to study abroad when I research projects, such as mentors and colleagues to develop the use of EKF (extended KALMAN Filter) algorithm combined with the PDA to locate target tracking
Update : 2025-04-26 Size : 9kb Publisher : chris
[matlab] GM-PHD1 DL : 1: Over-the-horizon radar (OTHR) exploits skywave propagation of high-frequency signals to detect and track targets, which are different from the conventional radar. It has received wide attention because of its wide area surveillance, long detection range, strong anti-stealth ability, the capability of the long early warning time, and so on. In OTHR, a significant problem is the effect of multipath propagation, which causes multiple detections via different propagation paths for a target with missed detections and false alarms at the receiver [1–6]. Nevertheless, the conventional tracking algorithms, such as probabilistic data association (PDA) [7–9], presume that a single-measurement per target, it may consider the other measurements of the same target as clutter, and multiple tracks are produced when a single target is present. Therefore, these methods cannot effectively solve the multipath propagation problem.(Conventional multitarget tracking systems presume that each target can produce at most one measurement per scan. Due to the multiple ionospheric propagation paths in over-the-horizon radar (OTHR), this assumption is not valid. To solve this problem, this paper proposes a novel tracking algorithm based on the theory of finite set statistics (FISST) called the multipath probability hypothesis density (MP-PHD) filter in cluttered environments. First, the FISST is used to derive the update equation, and then Gaussian mixture (GM) is introduced to derive the closed-form solution of the MP-PHD filter. Moreover, the extended Kalman filter (EKF) is presented to deal with the nonlinear problem of the measurement model in OTHR. Eventually, the simulation results are provided to demonstrate the effectiveness of the proposed filter.)
Update : 2025-04-26 Size : 18kb Publisher : ioeyoyo