Radar target recognition based on complex compressive sensing of stepped-frequency returns

Ismail Jouny

doi:10.1117/12.3007475

7 June 2024 Radar target recognition based on complex compressive sensing of stepped-frequency returns

Ismail Jouny

Proceedings Volume 13057, Signal Processing, Sensor/Information Fusion, and Target Recognition XXXIII; 130570H (2024) https://doi.org/10.1117/12.3007475
Event: SPIE Defense + Commercial Sensing, 2024, National Harbor, Maryland, United States

Abstract

Compressive sensing of complex stepped frequency radar returns is explored in this paper. The goal is to classify targets after reconstructing their sparse high range resolution profile from complex frequency compressive measurements. Given the limited number of scatterers along an aircraft, the target range profile (or impulse response) is considered sparse in the range or time domains. The paper focuses on 1) comparing different methods (or strategies) for compressive sensing of complex signals, 2) exploring feature selection algorithms as compressive sensing tools, and 3) exploring the benefits of denoising compressively sensed radar returns corrupted with additive noise. A synthetic radar target of five different scatterers is first used to assess the performance of different sensing strategies. Real radar returns of commercial aircraft models are used to assess the performance of a target recognition system that utilizes compressive sensing with or without denoising, and with or without feature selection.

Conference Presentation

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Ismail Jouny "Radar target recognition based on complex compressive sensing of stepped-frequency returns", Proc. SPIE 13057, Signal Processing, Sensor/Information Fusion, and Target Recognition XXXIII, 130570H (7 June 2024); https://doi.org/10.1117/12.3007475

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