Fusion Detection for Networked Radar Aided by Doppler Information

Autor: Chang GAO, Fengdeng GU, Junkun YAN, Tianyi JIA, Hongwei LIU
Jazyk: English<br />Chinese
Rok vydání: 2023
Předmět:
Zdroj: Leida xuebao, Vol 12, Iss 3, Pp 500-515 (2023)
Druh dokumentu: article
ISSN: 2095-283X
DOI: 10.12000/JR22220
Popis: Compared with single-radar systems, spatially separated networked radar usually has better detection performance due to its advantages of spatial and frequency diversities. Most of the current fusion detection methods based on networked radar systems only rely on the echo amplitude information of the target without considering the Doppler information that a coherent radar system can obtain to assist detection of targets. Intuitively, the spatial position and radial velocity of a target observed by different radar devices in the networked radar systems should meet certain physical constraints under which the target and false target can be substantially distinguished. Based on this consideration, fusion detection for the networked radar aided by a Doppler information algorithm is proposed in this paper. First, a set of inequalities is constructed based on the coupling between the observation of the same target’s azimuth and Doppler velocity by multiple radar stations. Then, a two-phase method, an algorithm in operational research, is used to judge whether the inequalities have a feasible solution, based on which a judgment is made on whether the target exists. Finally, some simulations are conducted, which show that the proposed algorithm can effectively improve the detection performance of the networked radar system fusion detection. Additionally, the influence of radar station location and target position on the fusion detection performance of the proposed algorithm is analyzed.
Databáze: Directory of Open Access Journals