A novel algorithm for tracking a maneuvering target in clutter

被引：7
作者：
de Souza, Marcelo Lucena [1 ]
Guimaraes, Alberto Gaspar [2 ]
Pinto, Ernesto Leite [3 ]
机构：
[1] Frequentis Comsoft GmbH, Karlsruhe, Germany
[2] Univ Fed Fluminense, Dept Telecommun Engn, Niteroi, RJ, Brazil
[3] Mil Inst Engn, Dept Elect Engn, Rio De Janeiro, Brazil
来源：
DIGITAL SIGNAL PROCESSING | 2022年 / 126卷
关键词：
Bayesian methods; Maneuvering target tracking; Clutter; Data association; IMMPDAF; MULTIPLE-HYPOTHESIS TRACKING; DATA ASSOCIATION FILTER; RADAR; BENCHMARK; SYSTEMS;
D O I：
10.1016/j.dsp.2022.103481
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
An algorithm for tracking a maneuvering target under measurement origin uncertainties is derived based on the approximation and propagation of the target state posterior distribution by combining Bayesian decision theory and suitable hypothesis merging procedures. Simulation results show that the main feature of this algorithm is its ability to significantly reduce the estimation error during non-maneuvering periods, making it quite suitable for tracking low maneuvering aircrafts. At the same time, the proposal is able to keep very low levels of track loss rate even for scenarios with high false alarm probability and trajectories with high degree of maneuverability. This proposal presents overall superiority when compared to the Interacting Multiple-Model with Probabilistic Data Filtering (IMMPDAF) solution, with an affordable increase in computational cost. (C)& nbsp;2022 Elsevier Inc. All rights reserved.
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页数：10
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