基于区间灰数的分布式多目标航迹关联算法

衣晓; 张怀巍; 曹昕莹; 何友

doi:10.7527/S1000-6893.2013.0040

航空学报 >

2013 , Vol. 34 >Issue 2: 352 - 360

DOI: https://doi.org/10.7527/S1000-6893.2013.0040

电子与控制

基于区间灰数的分布式多目标航迹关联算法

衣晓 ,
张怀巍 ,
曹昕莹 ,
何友

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海军航空工程学院信息融合技术研究所, 山东烟台 264001

衣晓,男,博士后,教授,硕士生导师。主要研究方向:信息融合,目标跟踪,无线传感器网络等。Tel:0535-6635417,E-mail:yxgx@sohu.com;张怀巍,男,硕士研究生。主要研究方向:航迹关联,信息融合等。Tel:0535-6635877,E-mail:zhanghuaiwei2008@163.com;曹昕莹,女,硕士研究生。主要研究方向:信息融合、无源定位技术等。何友,男,博士,教授,博士生导师。主要研究方向:信息融合,多目标跟踪,雷达自适应检测方法等。

收稿日期: 2012-04-17

修回日期: 2012-06-13

网络出版日期: 2012-09-11

基金资助

国家自然科学基金(61032001);新世纪优秀人才支持计划(NCET-11-0872)

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A Track Association Algorithm for Distributed Multi-target Systems Based on Gray Interval Numbers

YI Xiao ,
ZHANG Huaiwei ,
CAO Xinying ,
HE You

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Research Institute of Information Fusion, Naval Aeronautical Engineering Institute, Yantai 264001, China

Received date: 2012-04-17

Revised date: 2012-06-13

Online published: 2012-09-11

Supported by

National Natural Science Foundation of China (61032001); Program for New Century Excellent Talents in University(NCET-11-0872)

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摘要

研究了存在系统误差条件下分布式多目标航迹关联问题,以异地配置的2D组网雷达为背景,分析了时变系统误差对雷达上报航迹的影响,将误差影响下的目标定位看做一种认知不确定性,并给出两种用区间灰数描述这一不确定性的方法。由此提出了一种航迹关联算法,该算法以区间相离度作为衡量航迹间差异信息的测度,建立灰色关联分析模型,并根据灰关联度排序给出航迹关联对。通过对算法的约束条件进行深层次分析,给出了使用算法的先决条件。在常见系统误差环境下的蒙特卡罗仿真结果表明,算法具有良好的抗差性能和较广泛的适用性。

关键词： 航迹关联; 系统误差; 区间灰数; 组网雷达; 信息融合

本文引用格式

衣晓 , 张怀巍 , 曹昕莹 , 何友 . 基于区间灰数的分布式多目标航迹关联算法[J]. 航空学报, 2013 , 34(2) : 352 -360 . DOI: 10.7527/S1000-6893.2013.0040

Abstract

This paper mainly discusses the distributed multi-target track association problems with system bias. It analyzes how the time-variable bias affects the detected tracks in a remote configured 2D radar network, regards the target location as a cognitive uncertainty, and puts forward two methods, with which the uncertainty can be expressed into gray interval numbers. Starting from this, a track association algorithm is presented. This algorithm selects the interval deviation degree as a measure of the difference between tracks, establishes a gray correlation analysis model, and points out the associated pair by a gray relational degree order. Further research is done about the constraint condition of the algorithm and the prerequisites to use the algorithm are provided. Monte Carlo simulations for common system bias show that this algorithm has good robust performance and wide practicability.

Key words： track association; system bias; gray interval number; radar network; information fusion

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