Complementary Moving Target Detection Based on Waveform-Domain Complementary Signal Sets

The complementary waveform-based moving target detection faces challenges like limited Doppler resolution and poor range sidelobe suppression. This letter proposes a Complementary-Moving Target Detection (C-MTD) method to address the coherent integration issue of Waveform-Domain Complementary Signal Sets (WDCSS), a subset of generalized complementary waveforms. C-MTD enhances Doppler resolution and extends complementary properties to the range- Doppler map by applying coherent slow-time processing to consecutive WDCSSs. Simulations demonstrate that C-MTD outperforms conventional methods in Doppler resolution, range sidelobe suppression, and detection under low input signal-to-noise ratios (SNRs) conditions.

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Publication Details

Journal
IEEE Signal Processing Letters
Published
2025-01-01
DOI
https://doi.org/10.1109/lsp.2025.3584734
Primary Topic
Neural Networks and Applications
Type
article
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article

Complementary Moving Target Detection Based on Waveform-Domain Complementary Signal Sets

Hanning Su, Fucheng Guo, Weidong Hu, Qinglong Bao
IEEE Signal Processing Letters
Neural Networks and Applications
article

Complementary Moving Target Detection Based on Waveform-Domain Complementary Signal Sets

Hanning Su, Fucheng Guo, Weidong Hu, Qinglong Bao
article en

Abstract

The complementary waveform-based moving target detection faces challenges like limited Doppler resolution and poor range sidelobe suppression. This letter proposes a Complementary-Moving Target Detection (C-MTD) method to address the coherent integration issue of Waveform-Domain Complementary Signal Sets (WDCSS), a subset of generalized complementary waveforms. C-MTD enhances Doppler resolution and extends complementary properties to the range- Doppler map by applying coherent slow-time processing to consecutive WDCSSs. Simulations demonstrate that C-MTD outperforms conventional methods in Doppler resolution, range sidelobe suppression, and detection under low input signal-to-noise ratios (SNRs) conditions.

IEEE Signal Processing LettersVol. 32
National University of Defense Technology (CN)
Openalex Percentile: Top 92%
Neural Networks and Applications
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Complementary Moving Target Detection Based on Waveform-Domain Complementary Signal Sets — Hanning Su, Fucheng Guo, et al. · IEEE Signal Processing Letters (2025) | TGRS Research Map | TGRS