Fast 3D Parameters Estimation of Targets in Bistatic MIMO Radar Based on Sparse Signal Reconstruction

Abstract

In this paper, three parameters of targets in bistatic multiple-input multiple-output (MIMO) radar are estimated based on sparse signal reconstruction. First, 2D scanning space in bistatic MIMO radar is divided into dense meshes, and a sparse signal model of multiple measurement vectors is constructed. Second, a constrained objective optimization function is established by using traditional $l2$ norm and is converted to an unconstrained objective optimization function. A conjugate gradient method is utilized to solve the inverse operation of a large-scale matrix and to avoid singular problems during sparse iterations. Even in 2D dense meshes of $90\times 90$ , the speed of convergence can be accelerated. The direction of arrival, the direction of departure, and the reflection coefficient of multiple targets in bistatic MIMO radar are estimated, and the 3D parameters of each target automatically match. Simulation results verify the validity and fast convergence of the proposed method.