Moving Targets Imaging by SVD of a Space-Velocity MIMO Radar Data Driven Matrix

Authors:
Publisher website
Google Scholar
Abstract
We introduce a method for Multiple Input Multiple Output (MIMO) radar imaging of moving targets in a strongly reflecting, complex stationary scenery (clutter). The radar system has fixed nearby antennas that play the dual role of sources and receivers. It gathers data either by emitting probing pulses from one antenna at a time, or by sending from all the antennas non-coherent, possibly orthogonal, waveforms. We show how to obtain from the measurements an imaging function that depends on search position and velocity and is approximately separable in these variables, for a single moving target. For multiple moving targets in clutter, the imaging function is a sum of separable functions. By sampling this imaging function on a position velocity grid we obtain an imaging matrix whose Singular Value Decomposition (SVD) allows the separation of the clutter and the targets moving at different velocities. The decomposition also leads directly to estimates of the locations and motion of the targets. The imaging method is designed to work in strong clutter, with unknown and possibly heterogeneous statistics. It does not require prior estimation of the covariance matrix of the clutter response or of its rank. We give an analysis of the imaging method and illustrate how it works with numerical simulations.

This publication has 49 references indexed in Scilit: