多局部节点异步抗差航迹关联算法

衣晓; 杜金鹏; 张天舒

doi:10.7527/S1000-6893.2020.24494

航空学报 >

2021 , Vol. 42 >Issue 6: 324494 - 324494

DOI: https://doi.org/10.7527/S1000-6893.2020.24494

电子电气工程与控制

多局部节点异步抗差航迹关联算法

衣晓 ,
杜金鹏 ,
张天舒

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海军航空大学, 烟台 264001

收稿日期: 2020-07-06

修回日期: 2020-07-29

网络出版日期: 2020-09-02

基金资助

国防科技卓越青年人才基金（2017-JCJQ-ZQ-003）；泰山学者工程专项经费（ts201712072）

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Asynchronous anti-bias track-to-track association algorithm of multi-local nodes

YI Xiao ,
DU Jinpeng ,
ZHANG Tianshu

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Naval Aviation University, Yantai 264001, China

Received date: 2020-07-06

Revised date: 2020-07-29

Online published: 2020-09-02

Supported by

Excellent Youth Scholar of the National Defense Science and Technology Foundation of China (2017-JCJQ-ZQ-003);The Special Fund for the Taishan Scholar Project (ts201712072)

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摘要

为解决航迹异步与系统误差并存情况下的多局部节点航迹关联问题，提出一种基于区间序列离散度的多局部节点异步抗差航迹关联算法。定义区间型数据集的离散信息度量，给出系统误差下航迹序列区间化方法，通过累次积分计算离散度，结合多维分配进行关联判定。针对多局部节点上报目标不完全一致现象，设置零号航迹管理关联质量。与传统算法相比，无需时域配准，可在系统误差下对异步航迹直接关联。仿真结果表明，算法能在局部节点上报目标不完全一致场景下实现有效关联，且正确关联率随局部节点数目的增加或目标密集程度的增大而提高。

关键词： 航迹关联; 异步航迹; 系统误差; 多维分配; 离散度

本文引用格式

衣晓 , 杜金鹏 , 张天舒 . 多局部节点异步抗差航迹关联算法[J]. 航空学报, 2021 , 42(6) : 324494 -324494 . DOI: 10.7527/S1000-6893.2020.24494

Abstract

To solve the problem of asynchronous anti-bias track association, an asynchronous anti-bias track-to-track association algorithm of multi-local nodes based on the discrete degree of interval sequence is proposed. A discrete information measurement of the interval data set is defined and the interval method for track sequence with system biases is provided. The discrete degree is calculated through repeated integral, and the association determination is performed using multi-dimension assignment. Aiming at the phenomenon of different targets reported by multi-local nodes, the zero track is established to manage the association quality. Compared with the traditional algorithm, the asynchronous track can be directly correlated without time-domain registration in the presence of system errors. The simulation results show that this algorithm can achieve effective association in the presence of different targets reported by multi-local nodes and the correct association rate increases with the increase of the local nodes number or the target density.

Key words： track association; asynchronous track; system bias; multi-dimension assignment; discrete degree

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