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Article

Spatial–Temporal Joint Design and Optimization of Phase-Coded Waveform for MIMO Radar

by
Wei Lei
1,2,
Yue Zhang
1,2,*,
Zengping Chen
1,2,
Xiaolong Chen
3 and
Qiang Song
1,2
1
School of Electronics and Communication Engineering, Shenzhen Campus, Sun Yat-sen University, No. 66, Gongchang Road, Guangming District, Shenzhen 518107, China
2
School of Electronics and Communication Engineering, Sun Yat-sen University, Guangzhou 510275, China
3
Department of Electronic Information Engineering, Naval Aviation University, Yantai 246000, China
*
Author to whom correspondence should be addressed.
Remote Sens. 2024, 16(14), 2647; https://doi.org/10.3390/rs16142647 (registering DOI)
Submission received: 9 May 2024 / Revised: 3 July 2024 / Accepted: 17 July 2024 / Published: 19 July 2024
(This article belongs to the Special Issue Technical Developments in Radar—Processing and Application)

Abstract

By simultaneously transmitting multiple different waveform signals, a multiple-input multiple-output (MIMO) radar possesses higher degrees of freedom and potential in many aspects compared to a traditional phased-array radar. The spatial–temporal characteristics of waveforms are the key to determining their performance. In this paper, a transmitting waveform design method based on spatial–temporal joint (STJ) optimization for a MIMO radar is proposed, where waveforms are designed not only for beam-pattern matching (BPM) but also for minimizing the autocorrelation sidelobes (ACSLs) of the spatial synthesis signals (SSSs) in the directions of interest. Firstly, the STJ model is established, where the two-step strategy and least squares method are utilized for BPM, and the L2p-Norm of the ACSL is constructed as the criterion for temporal characteristics optimization. Secondly, by transforming it into an unconstrained optimization problem about the waveform phase and using the gradient descent (GD) algorithm, the hard, non-convex, high-dimensional, nonlinear optimization problem is solved efficiently. Finally, the method’s effectiveness is verified through numerical simulation. The results show that our method is suitable for both orthogonal and partial-correlation MIMO waveform designs and efficiently achieves better spatial–temporal characteristic performances simultaneously in comparison with existing methods.
Keywords: MIMO radar; waveform design; spatial–temporal joint optimization; beam-pattern matching; L2p-Norm; spatial synthesis signals; gradient descent MIMO radar; waveform design; spatial–temporal joint optimization; beam-pattern matching; L2p-Norm; spatial synthesis signals; gradient descent

Share and Cite

MDPI and ACS Style

Lei, W.; Zhang, Y.; Chen, Z.; Chen, X.; Song, Q. Spatial–Temporal Joint Design and Optimization of Phase-Coded Waveform for MIMO Radar. Remote Sens. 2024, 16, 2647. https://doi.org/10.3390/rs16142647

AMA Style

Lei W, Zhang Y, Chen Z, Chen X, Song Q. Spatial–Temporal Joint Design and Optimization of Phase-Coded Waveform for MIMO Radar. Remote Sensing. 2024; 16(14):2647. https://doi.org/10.3390/rs16142647

Chicago/Turabian Style

Lei, Wei, Yue Zhang, Zengping Chen, Xiaolong Chen, and Qiang Song. 2024. "Spatial–Temporal Joint Design and Optimization of Phase-Coded Waveform for MIMO Radar" Remote Sensing 16, no. 14: 2647. https://doi.org/10.3390/rs16142647

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