Joint Design of Doppler-Resilient Unimodular Discrete-Phase Waveforms and Receiving Filters for MIMO Radars
Junpeng Ma, Yuke Li, Junbo Wang, Yongxing Zhou

TL;DR
This paper introduces SQNGD, a novel joint optimization framework for Doppler-resilient unimodular waveforms and filters in MIMO radar, achieving improved sidelobe suppression and reduced computation time.
Contribution
It proposes a differentiable, joint transmit-receive design method with FFT acceleration, outperforming existing algorithms in Doppler-resilient waveform optimization.
Findings
Achieves approximately -43 dB peak sidelobe level over Doppler range [-0.5,0.5].
Reduces optimization time by up to 11 times compared to SOTA methods.
Outperforms MMCD by 5.85 dB in sidelobe level while maintaining SNRL of 0.5 dB.
Abstract
Designing Doppler-resilient unimodular discrete phase-coded waveforms (DPWs) with low delay-Doppler sidelobes is critical for multiple-input multiple-output (MIMO) radar. Existing block coordinate descent (BCD) methods suffer from high computational cost for designing long sequences or large waveform sets. Meanwhile, learning-based alternatives such as the soft-quantization network (SQN) only address correlation optimization in the delay domain, without considering ambiguity function (AF) optimization in the joint delay-Doppler domain. To address these issues, this paper proposes a novel Doppler-resilient DPW design framework, termed SQNGD, for joint transmit-receive optimization that simultaneously optimizes the auto-AF, cross-AF (CAF), and signal-to-noise ratio loss (SNRL) under unimodular constraints. To solve the multi-objective optimization problem (MOOP), a joint transmit-receive…
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