Autofocusing imaging method based on alternating learning of wall parameters and sparse coefficients for through-the-wall radar

Liang Bian; Liangnian Jin; Mengbei Yuan

doi:10.1117/12.2613421

15 February 2022 Autofocusing imaging method based on alternating learning of wall parameters and sparse coefficients for through-the-wall radar

Liang Bian, Liangnian Jin, Mengbei Yuan

Author Affiliations +

Proceedings Volume 12166, Seventh Asia Pacific Conference on Optics Manufacture and 2021 International Forum of Young Scientists on Advanced Optical Manufacturing (APCOM and YSAOM 2021); 121661R (2022) https://doi.org/10.1117/12.2613421
Event: Seventh Asia Pacific Conference on Optics Manufacture and 2021 International Forum of Young Scientists on Advanced Optical Manufacturing (APCOM and YSAOM 2021), 2021, Hong Kong, Hong Kong

Abstract

Unknown wall parameters will cause the target position offset and image distortion for three-dimensional imaging of through-the-wall radar. In this paper, we propose an autofocusing imaging method of alternating learning of wall parameters and sparse coefficients based on the parametric diffraction tomography sparse model. The sparse coefficients reconstruction algorithm is unrolled a multilayer neural network for learning to update the sparse coefficients. The normalized mean square error is selected as the network loss function, and the batch gradient descent method is used to learn the network parameters. Subsequently, we still use this neural network to learn the variation of wall parameters to update the wall parameters, but the difference is to use the image quality evaluation function as the loss function. After several alternating iterations, we determine the sparse coefficients and wall parameters that minimize the loss function as the final result. The simulation results show that this proposed method can effectively eliminate the target position offset and image distortion, so that it can realize accurate estimation of wall parameters and autofocusing imaging.

Citation Download Citation

Liang Bian, Liangnian Jin, and Mengbei Yuan "Autofocusing imaging method based on alternating learning of wall parameters and sparse coefficients for through-the-wall radar", Proc. SPIE 12166, Seventh Asia Pacific Conference on Optics Manufacture and 2021 International Forum of Young Scientists on Advanced Optical Manufacturing (APCOM and YSAOM 2021), 121661R (15 February 2022); https://doi.org/10.1117/12.2613421

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KEYWORDS

Lamps

Detection and tracking algorithms

Radar

Image quality

Radar imaging

Antennas

3D image processing

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