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1-Bit Radar Imaging Based on Adversarial Samples

Han, Jianghong ; Li, Gang ; Wang, Kunpeng ; Duan, Meiya ; Zhang, Xiao-Ping

IEEE transactions on geoscience and remote sensing, 2022, Vol.60, p.1-13 [Periódico revisado por pares]

New York: IEEE

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Título:
1-Bit Radar Imaging Based on Adversarial Samples
Autor: Han, Jianghong ; Li, Gang ; Wang, Kunpeng ; Duan, Meiya ; Zhang, Xiao-Ping
Assuntos: 1-bit compressive sensing ; 1-bit radar imaging ; adversarial sample ; Algorithms ; Data models ; Echoes ; Imaging ; Imaging techniques ; Iterative methods ; Mathematical models ; Measurement ; Noise ; Noise pollution ; Parameters ; parametric model ; Parametric statistics ; Quantization (signal) ; Radar ; Radar antennas ; Radar data ; Radar imaging ; Storage ; Synthetic aperture radar
É parte de: IEEE transactions on geoscience and remote sensing, 2022, Vol.60, p.1-13
Descrição: Radar imaging with 1-bit data is attractive thanks to its low storage and transmission burden. Existing 1-bit radar imaging methods cannot satisfactorily suppress the artifacts in the imaging result induced by 1-bit quantization error and noise. In this article, we propose a new 1-bit compressive sensing (CS) based algorithm, i.e., the adversarial-sample-based binary iterative hard thresholding (AS-BIHT) algorithm, to improve the 1-bit radar imaging performance. First, we formulate a parametric model for 1-bit radar imaging with a new adjustable quantization level parameter. The parametric 1-bit radar imaging model updates the imaging scene and the quantization level parameter in an iterative fashion based on adversarial samples. Then, we design a mechanism to generate adversarial samples by attacking the 1-bit radar imaging model to resist the quantization consistency condition, such that forcing quantization consistent reconstruction on adversarial samples mitigates the quantization error and noise. The quantization level parameter is then tuned based on the adversarial samples. In this way, the ability of the model to adapt to echo data contaminated by noise and quantization error is enhanced, and the artifacts are well suppressed. Simulation and experimental results on real radar data demonstrate the effectiveness of the proposed AS-BIHT algorithm in 1-bit radar imaging.
Editor: New York: IEEE
Idioma: Inglês

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1-Bit Radar Imaging Based on Adversarial Samples

Han, Jianghong ; Li, Gang ; Wang, Kunpeng ; Duan, Meiya ; Zhang, Xiao-Ping

New York: IEEE

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