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Pulse train coding and decoding matrix design based ECCM scheme for MIMO radar against interrupted sampling repeater jamming.

Authors :
Zheng, Hao
Liu, Yang
Zhang, Yinghui
Yan, Junkun
Jiu, Bo
Source :
Signal Processing. Jan2024, Vol. 214, pN.PAG-N.PAG. 1p.
Publication Year :
2024

Abstract

In this paper, we propose a pulse train coding and decoding matrix design based electronic counter-countermeasure (ECCM) scheme for multiple-input multiple-output (MIMO) radar against interrupted sampling repeater jamming (ISRJ). The ECCM scheme includes two steps: jamming pulse compression (PC) sidelobes suppression and jamming peaks identification. By joint design of coding and decoding matrix, the proposed ECCM scheme can simultaneously suppress PC sidelobes of target echoes and jamming signals. Compared with the existing methods, the proposed scheme can achieve the improvement in jamming suppression and target detection without signal-to-noise ratio loss, and the coding and decoding matrix design can be realized offline. Besides, the phase-only coding matrix can be directly applied to the MIMO radar with multi-beam transmit beampattern. After sidelobes suppression, an identification matrix is proposed to identify the jamming peaks. In specifical situation, the identification process does not require ISRJ parameter, and the ISRJ parameter estimation can be converted into a convex optimization problem in other situations. At last, simulated results corroborate the effectiveness of the anti-ISRJ performance with the proposed ECCM scheme. • An overall ECCM scheme is proposed, including ISRJ sidelobes suppression, ISRJ parameter estimation and ISRJ peaks identification. • The proposed ECCM scheme can be directly applied to the MIMO radar with multi-beam. • In a particular case, the proposed ECCM scheme can perform without ISRJ parameters. • The proposed ECCM scheme does not suffer SNR loss. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
01651684
Volume :
214
Database :
Academic Search Index
Journal :
Signal Processing
Publication Type :
Academic Journal
Accession number :
172809719
Full Text :
https://doi.org/10.1016/j.sigpro.2023.109245