北京航空航天大学学报2026，Vol.52Issue(4)：1139-1147,9.DOI:10.13700/j.bh.1001-5965.2024.0013
基于轻量化BiLSTM的多源雷达多目标跟踪点航数据关联算法
Light-weight BiLSTM-based data association algorithm between echoes and tracks for multi-radar multi-target tracking
摘要
Abstract
This paper proposes a data-driven algorithm,i.e.,a light-weight bi-directional long short-term memory(BiLSTM)network-based intelligent data association between echoes and tracks for multi-radar multi-target tracking,in light of the issue that data association is prone to error and that exact modeling-based algorithms have enormous computational costs for multi-radar multi-target tracking in dense clutter environments.The first step is to build the multi-radar association matrix,whose constituent is the association result between target tracks and radar echoes.Based on multi-radar echoes and predicted measurements,the distance tensor is designed based on max-min normalization.The light-weight BiLSTM networks-based multi-radar multi-target data association network is put forward,by taking the above normalized distance tensor and multi-radar association matrix as the input and output.And the measurement corresponding to the maximum probability is treated as the associated one to update every track through implementing a Kalman filter for each radar.The simulation results of multi-radar tracking multi-target in dense clutter environment show that the association accuracy and tracking precision of the proposed algorithm are similar with those of the centralized joint probability data association filter,which are much better than those of probability data association filter,nearest neighbor data association filter,fully connected layer-based data association filter and long short-term memory(LSTM)networks-based data association filter.Furthermore,compared to the centralized joint probability data association filter,which is nearly equal to the nearest neighbor data association filter,the proposed algrithm's average running time is significantly shorter.关键词
数据关联/多目标跟踪/多源雷达/双向长短期记忆网络/轻量化神经网络Key words
data association/multi-target tracking/multi-radar/bi-directional long short-term memory networks/light-weight neural networks分类
信息技术与安全科学引用本文复制引用
代睿,李洁,何立火,高新波..基于轻量化BiLSTM的多源雷达多目标跟踪点航数据关联算法[J].北京航空航天大学学报,2026,52(4):1139-1147,9.基金项目
国家自然科学基金(62036007,62276203) National Natural Science Foundation of China(62036007,62276203) （62036007,62276203）
