Removal of Micro-Doppler Effects in ISAR Imaging Based on the Joint Processing of Singular Value Decomposition and Complex Variational Mode Extraction

Abstract

For inverse synthetic aperture radar (ISAR) imaging of targets with micromotion parts, the removal of micro-Doppler (m-D) effects is the key procedure. However, under the condition of a sparse aperture, the echo pulse is limited or incomplete, giving rise to the difficulty of eliminating m-D effects. Thus, a novel m-D effects removal algorithm is proposed, which can effectively eliminate m-D effects, as well as the interference introduced by noise and sparse aperture in the ISAR image of the main body. The proposed algorithm mainly includes two processing steps. First, combined with the cut-off point determined by the normalized singular value difference spectrum, the rough estimation of the main body is achieved by singular value decomposition (SVD). Then, the variational mode extraction (VME) is extended to complex variational mode extraction (CVME). The constrained variational problem constructed by bandwidth and spectral overlap constraints is solved by the alternating direction method of multipliers (ADMM), and the precise estimation of the main body is obtained. Experimental results based on both simulated and measured data demonstrate that the proposed algorithm can acquire the high-resolution ISAR image of the main body under noisy and sparse conditions.

Research on Bi–ISAR Sparse Aperture High Resolution Imaging Algorithm under Low SNR

“…The signal decomposition noise reduction method is to decompose the signal into different components in different forms and analyze the obtained components to achieve the purpose of noise reduction. The main decomposition methods mainly include sparse decomposition, singular value decomposition, empirical mode decomposition (EMD) and other methods [21][22][23][24]. Among them, EMD algorithm is widely used because of its adaptability to non-stationary signals.…”

Study on the micro-Doppler separation method of bistatic inverse synthetic aperture radar targets with rotating parts based on complex variational mode decomposition

“…The echo spectrum generated by the main part of the target is relatively concentrated, whereas that of the micromotion part is relatively dispersed, resulting in higher energy of the mode function in the low-frequency part. By selecting a reasonable energy threshold, the mode function of the echo generated by the main part can be separated from the micromotion part 28 , 29 . The flow of the algorithm is summarized as follows.…”

“…By selecting a reasonable energy threshold, the mode function of the echo generated by the main part can be separated from the micromotion part. 28,29 The flow of the algorithm is summarized as follows.…”