Micro-Doppler Effect Removal in ISAR Imaging by Promoting Joint Sparsity in Time-Frequency Domain.

Lin Sun,Weidong Chen

doi:10.3390/s18040951

Abstract

For micromotion scatterers with small rotating radii, the micro-Doppler (m-D) effect interferes with cross-range compression in inverse synthetic aperture radar (ISAR) imaging and leads to a blurred main body image. In this paper, a novel method is proposed to remove the m-D effect by promoting the joint sparsity in the time-frequency domain. Firstly, to obtain the time-frequency representations of the limited measurements, the short-time Fourier transform (STFT) was modelled by an underdetermined equation. Then, a new objective function was used to measure the joint sparsity of the STFT entries so that the joint sparse recovery problem could be formulated as a constrained minimization problem. Similar to the smoothed (SL0) algorithm, a steepest descend approach was used to minimize the new objective function, where the projection step was tailored to make it suitable for m-D effect removal. Finally, we utilized the recovered STFT entries to obtain the main body echoes, based on which cross-range compression could be realized without m-D interference. After all contaminated range cells were processed by the proposed method, a clear main body image could be achieved. Experiments using both the point-scattering model and electromagnetic (EM) computation validated the performance of the proposed method.

Highlights

In inverse synthetic aperture radar (ISAR) imaging, mechanical rotations or vibrations of structures on a target may introduce additional frequency modulations on the returned signal, known as the micro-Doppler (m-D) effect [1,2,3]
Based on the distinct patterns in the time-frequency domain, this paper proposes a joint sparsity-based ISAR imaging method to remove the m-D effect generated by the micromotion scatterers with small rotating radii
In ISAR imaging, the m-D effect generated by the micromotion scatterers with small rotating radii leads to a blurred main body image

Summary

Introduction

In inverse synthetic aperture radar (ISAR) imaging, mechanical rotations or vibrations of structures on a target may introduce additional frequency modulations on the returned signal, known as the micro-Doppler (m-D) effect [1,2,3]. The main body image is usually blurred because of the interference of the rotating or vibrating scatterers, which are called micromotion scatterers [3]. The main body signal in the spectrogram has the shape of straight lines [5]. The main body signal and the micromotion signal subsequently are separated according to their distinct chirp rates. This algorithm has high computation cost because of the large chirplet dictionary. Zhang et al [6] extracts the straight lines in the spectrogram using the Hough transform

Methods

Results

Conclusion