Angle-only Maneuvering Target Tracking Using Primal-dual Gaussian Particle Filtering

被引：0

作者：

Zhang H. ^{[1
]}

机构：

[1] School of Aeronautics and Astronautics, Sun Yat-sen University, Shenzhen

来源：

Dianzi Yu Xinxi Xuebao/Journal of Electronics and Information Technology | 2024年 / 46卷 / 04期

关键词：

Angle-only; Causal invariant; Maneuvering target tracking; Primal-dual; Spatiotemporal inconsistency;

D O I：

10.11999/JEIT230413

中图分类号：

学科分类号：

摘要：

To reduce the mapping basepoint offset and Gaussian truncation errors caused by spatiotemporal inconsistency in angle-only maneuvering target tracking systems, mapping representation and ℓ1 -ℓ2,1 sparse regularization to represent spatiotemporal causal consistency constraints are used, the fuzzy comprehensive closeness is introduced to establish the suboptimal proposal distribution, the particle set in a causal invariant structure to approximate the Gaussian integration for target posterior is propagated, and the Primal-Dual Gaussian Particle Filtering (PDGPF) algorithm is derived. Simulation results show that, compared to the intersection measurement method with least squares, the accuracy for the PDGPF to locate a rotor Unmanned Aerial Vehicle (UAV) has improved by 18.4%～69.6%. Compared to the Soft Constrained Auxiliary Particle Filtering (SCAPF) algorithm, the PDGPF algorithm can adaptively correct the particle weights under the spatiotemporal mapping consistent constraints, obtaining more accurate and stable state estimation for tracking a maneuvering point target, reducing the overall computational burden by 12.9%. © 2024 Science Press. All rights reserved.

引用

页码：1408 / 1417

页数：9

共 32 条

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