Joint Design of Waveforms and Mismatched Filters Considering Correlation and RSM Optimization

Radar agile waveforms and mismatched filters exhibiting good correlation properties can effectively mitigate masking the weak adjacent targets and distinguish different signals from echoes through (mis)matched filtering. However, the Range Sidelobe Modulation (RSM) for agile waveforms stands as a significant factor that leads to performance degradation in radar detection after Pulse-Doppler (PD) processing. To address the sidelobes of auto-correlation, suppress cross correlation and counteract RSM, we jointly design waveforms and mismatched filters, formulating a cost function integrating sidelobes of auto-correlation, cross-correlation and the discrepancy of auto-correlation. Subsequently, we present an algorithm to tackle this issue via Majorization Minimization (MM). Through numerical analysis, our proposed algorithm strikes a better balance in mitigating correlation sidelobes and suppressing RSM compared to previous methods.

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Publication Details

Published
2024-11-22
DOI
https://doi.org/10.1109/icsidp62679.2024.10868451
Primary Topic
Image and Signal Denoising Methods
Type
article
Field-Weighted Citation Impact
0.00

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article

Joint Design of Waveforms and Mismatched Filters Considering Correlation and RSM Optimization

Hao Zhang, Huayu Fan, Quanhua Liu, Keyi Li et al.
Image and Signal Denoising Methods
article

Joint Design of Waveforms and Mismatched Filters Considering Correlation and RSM Optimization

Hao Zhang, Huayu Fan, Quanhua Liu, Keyi Li, Lixiang Ren
article en

Abstract

Radar agile waveforms and mismatched filters exhibiting good correlation properties can effectively mitigate masking the weak adjacent targets and distinguish different signals from echoes through (mis)matched filtering. However, the Range Sidelobe Modulation (RSM) for agile waveforms stands as a significant factor that leads to performance degradation in radar detection after Pulse-Doppler (PD) processing. To address the sidelobes of auto-correlation, suppress cross correlation and counteract RSM, we jointly design waveforms and mismatched filters, formulating a cost function integrating sidelobes of auto-correlation, cross-correlation and the discrepancy of auto-correlation. Subsequently, we present an algorithm to tackle this issue via Majorization Minimization (MM). Through numerical analysis, our proposed algorithm strikes a better balance in mitigating correlation sidelobes and suppressing RSM compared to previous methods.

Beijing Institute of Technology (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 73%
Image and Signal Denoising Methods
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Joint Design of Waveforms and Mismatched Filters Considering Correlation and RSM Optimization — Hao Zhang, Huayu Fan, et al. · (2024) | TGRS Research Map | TGRS