A Modified EM Algorithm for ISAR Scatterer Trajectory Matrix Completion

Abstract

The anisotropy of radar cross section of scatterers makes the scatterer trajectory matrix incomplete in sequential inverse synthetic aperture radar images. As a result, factorization methods cannot be directly applied to reconstruct the 3-D geometry of scatterers without additional consideration. We propose a modified expectation-maximization (EM) algorithm to retrieve the complete scatterer trajectory matrix. First, we derive the motion dynamics of the projected scatterer, which approximates an ellipse. Then, based on the estimated ellipse parameters using the known data of each scatterer trajectory, we use the Kalman filter to initialize the missing data. To address the limitations of a traditional EM, which only considers the rank-deficient characteristics of the scatterer trajectory matrix, we propose to augment EM by using both the known rank-deficient and elliptical motion characteristics. Experimental results on simulated data verify the effectiveness of the proposed method.