Space-Time Adaptive Processing Algorithm for EPC-MIMO radar via 3D Atomic Norm Minimization

The issue of suppressing range-ambiguous clutter is explored with Element-Pulse Coding (EPC)-Multiple-Input Multiple-Output (MIMO) radar in this paper. In general, by incorporating a tunable coding coefficient in both slow-time pulses and transmitted elements, the range-ambiguous clutter can be distinguished from different range ambiguity regions in transmit spatial frequency dimension, and further suppressed through Space-Time Adaptive Processing (STAP)-based method. In specific, to tackle the problem of insufficient Independent Identical Distribution (IID) training samples, a STAP-based method utilizing Three-Dimensional Atomic Norm Minimization (3D-ANM) is proposed to reconstruct the clutter covariance matrix (CCM). Simulations are performed to confirm the efficacy of the proposed 3D-ANM algorithm.

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Publication Details

Published
2024-11-22
DOI
https://doi.org/10.1109/icsidp62679.2024.10868217
Primary Topic
Radar Systems and Signal Processing
Type
article
Field-Weighted Citation Impact
0.00

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article

Space-Time Adaptive Processing Algorithm for EPC-MIMO radar via 3D Atomic Norm Minimization

Jinxin Sui, Lei Cui, Guozhong Chen, Lan Lan et al.
Radar Systems and Signal Processing
article

Space-Time Adaptive Processing Algorithm for EPC-MIMO radar via 3D Atomic Norm Minimization

Jinxin Sui, Lei Cui, Guozhong Chen, Lan Lan, Shengqi Zhu, Jie Gao, Ximin Li
article en

Abstract

The issue of suppressing range-ambiguous clutter is explored with Element-Pulse Coding (EPC)-Multiple-Input Multiple-Output (MIMO) radar in this paper. In general, by incorporating a tunable coding coefficient in both slow-time pulses and transmitted elements, the range-ambiguous clutter can be distinguished from different range ambiguity regions in transmit spatial frequency dimension, and further suppressed through Space-Time Adaptive Processing (STAP)-based method. In specific, to tackle the problem of insufficient Independent Identical Distribution (IID) training samples, a STAP-based method utilizing Three-Dimensional Atomic Norm Minimization (3D-ANM) is proposed to reconstruct the clutter covariance matrix (CCM). Simulations are performed to confirm the efficacy of the proposed 3D-ANM algorithm.

Xidian University (CN), Shanghai Micro Satellite Engineering Center (CN)
Xidian University, Nature
Affordable and clean energy
Openalex Percentile: Top 55%
Radar Systems and Signal Processing
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