Matrix rearrangement for ISAR echo completion with undersampled data

Abstract

Matrix completion (MC) is a technique of recovering a low rank matrix from partial observed elements and their corresponding subset of the entries, which has been applied in synthetic aperture radar (SAR) and inverse synthetic aperture radar (ISAR) imaging for compressing the sampling data. It is effective for undersampled data with random echo elements missing, but will not work well for situation that there are some random rows and columns with none of entries observed because the echo matrix will not satisfy the required condition of MC. However, it is easier to operate in practical application for the latter way and it needs to store limited number of corresponding subset. Thus, a novel way of matrix rearrangement is proposed for ISAR data based on the characteristics of ISAR echo. The new matrix satisfies the condition of MC, and it has better low rank property while reduces the computational time compared with the existing methods of matrix rearrangement. The effectiveness of the proposed method can be demonstrated by the simulation and experimental results.