Covariance-Free TDOA/FDOA-Based Moving Target Localization for Multi-Static Radar

In this paper, we consider the problem of estimating the location and velocity of a non-cooperative moving target using a multi-static radar, which consists of a set of spatially distributed sensors in listening mode. The moving target may be transmitting, or reflecting, a source signal that is assumed to be unknown and modeled as a deterministic process. We develop a computationally efficient two-step approach to solve the localization problem. The first step finds the time difference of arrival (TDOA) and frequency difference of arrival (FDOA) estimates for each sensor with respect to a reference sensor by using a 2-dimensional Fast Fourier transform, and the second step employs an iterative reweighted least square (IRLS) approach with a varying weighting matrix to determine the target location and velocity. While most existing TDOA/FDOA-based methods require knowledge of the covariance matrix of the TDOA and FDOA estimates, which is usually unknown in practice, our proposed IRLS approach is covariance matrix-free. Numerical results show that the IRLS approach has a lower signal-to-noise ratio (SNR) threshold compared with a recent TDOA/FDOA-based method, especially when the target is considerably farther away from some sensors than others.