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Time Reversal Imaging Algorithm Based on Signal-subspace Vectors from the Spatial-frequency Decomposition |
ZHONG Xuanming LI Junye LIAO Cheng |
(Electromagnetics Institute, Southwest Jiaotong University, Chengdu 610031, China) |
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Abstract Basing on the signal-subspace vectors from the spatial-frequency decomposition, a novel time-reversal imaging algorithm is proposed. Using the backscattered data recorded by the antenna array, a spatial-frequency multistatic matrix is set up. Singular value decomposition is applied to the matrix to obtain the signal-subspace vectors, which are employed to focus the targets imaging selectively. The imaging pseudo-spectrum based on the full backscattered data includes the contributions of multiple sub-vectors and can be viewed as the superposition of multiple images. The algorithm is statistically stable. The random phases, generated by the conventional time-reversal imaging method based on the spatial-spatial decomposition, do not arise in the algorithm. It has excellent capability to resist the noise interference and can accurately focus the multi-targets even when noise with 10 dB SNR is added to the measured data.
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Received: 21 March 2016
Published: 09 October 2016
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Fund: The United Fund of National Natural Science Foundation of China and China Academy of Engineering Physics (U1330109) |
Corresponding Authors:
ZHONG Xuanming
E-mail: xm_zhong@163.com
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