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多源传感器箱粒子LMB滤波算法

张永权 李志彬 张文博 苏镇镇

西安电子科技大学学报(自然科学版)2024,Vol.51Issue(4):51-66,16.
西安电子科技大学学报(自然科学版)2024,Vol.51Issue(4):51-66,16.DOI:10.19665/j.issn1001-2400.20240104

多源传感器箱粒子LMB滤波算法

Multi-source sensor box particle LMB filtering algorithm

张永权 1李志彬 1张文博 1苏镇镇2

作者信息

  • 1. 西安电子科技大学 电子工程学院,陕西 西安 710071
  • 2. 西安电子科技大学 计算机科学与技术学院,陕西 西安 710071
  • 折叠

摘要

Abstract

With the emergence of a large number of complex tracking scenarios,conventional multi-source sensor multi-target tracking algorithms have shortcomings of high computational complexity,low tracking accuracy,and inability to estimate target trajectories,making them unable to meet the needs of modern warfare.In this paper,we focus on the implementation of the multi-source sensor tracking problem with the background of the multi-source sensor system composed of active and passive sensors.For the problem of a"multi-active+multi-passive"multi-source sensor system that the measurement cannot be fully integrated and the overall algorithm complexity is high,a multi-source sensor box particle labeled multi-Bernoulli(MS-BPF-LMB)filtering algorithm is proposed.First,the sensors are grouped according to different active sensors,i.e.,all sensors are divided into several"single active+multiple passive"sensor groups;and then,through parallel operations,a multi-sensor information fusion method based on angle correlation is applied to each sensor group to obtain the effective measurements required for tracking.Finally,in the tracking filtering stage,the obtained measurement points are divided into several box particles by introducing the box particle filtering numerical calculation method,and the update coefficients of multi-sensor measurements under box particle filtering are redefined to achieve LMB filtering with a low computational complexity.Simulation results show that the proposed method can effectively deal with the problem of multi-source information fusion of heterogeneous data by significantly reducing the error and decreasing the complexity of the algorithm by about 40% on the basis of maintaining the tracking accuracy of the target.

关键词

目标跟踪/传感器数据融合/信息融合/箱粒子滤波/标签多伯努利滤波

Key words

target tracking/sensor data fusion/information fusion/box particle filtering/labeled multi-Bernoulli filtering

分类

航空航天

引用本文复制引用

张永权,李志彬,张文博,苏镇镇..多源传感器箱粒子LMB滤波算法[J].西安电子科技大学学报(自然科学版),2024,51(4):51-66,16.

基金项目

国家自然科学基金(62276204,62306222) (62276204,62306222)

博士后特别资助(2020T130494) (2020T130494)

陕西省自然科学基金(2022JM-340,2023-JC-QN-0710) (2022JM-340,2023-JC-QN-0710)

西安电子科技大学学报(自然科学版)

OA北大核心CSTPCD

1001-2400

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