Moving Target Detection in Reverberation Background with Iterative Reweighted Least Squares Scheme
Cheng Wang, Guangping Zhu, Jingwei Yin · 2024
In this study, to address the issue of detecting moving targets in a reverberation environment, reducing reverberation by extracting the low-rank structure of multiframe data using the low-rank sparse decomposition theory is focused. Subsequently, successful detection of moving targets underwater was attained. To address the problem of low-rank matrix restoration, this study proposes a robust principal component analysis method using the Geman-McClure function and employs iterative reweighted least squares to it implement numerically. Experimental results verify that this method can accurately detect moving targets in a strong reverberation environment, which demonstrates clear advantages over traditional methods.