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Multitarget-tracking Method for Airborne Radar Based on a Transformer Network

Authors :
Wenna LI
Shunsheng ZHANG
Wenqin WANG
Source :
Leida xuebao, Vol 11, Iss 3, Pp 469-478 (2022)
Publication Year :
2022
Publisher :
China Science Publishing & Media Ltd. (CSPM), 2022.

Abstract

Conventional multitarget-tracking data association algorithms must have prior information, such as the target motion model and clutter density. However, such prior information cannot be obtained timely and accurately before tracking. To address this issue, a data association algorithm for multitarget tracking based on a transformer network is proposed. First, considering that the radar may not perform accurate detected the target, virtual measurements are performed to re-establish the data association model. Thus, a data association method based on the transformer network is proposed to solve the matching problem of multitargets and multimeasurements. Moreover, a loss function combining Masked Cross entropy loss and Dice (MCD) loss is designed to optimize the network parameters. Simulation data and real measurement data results show that the proposed algorithm outperforms classic data association algorithms and algorithms based on bidirectional long short-term memory network under varying detection probability conditions.

Details

Language :
English, Chinese
ISSN :
2095283X
Volume :
11
Issue :
3
Database :
Directory of Open Access Journals
Journal :
Leida xuebao
Publication Type :
Academic Journal
Accession number :
edsdoj.492a4c4f4f6e4da0949caad0a736ef1e
Document Type :
article
Full Text :
https://doi.org/10.12000/JR22009