The Significant Gains From Optimally Processed Multiple Signals of Opportunity and Multiple Receive Stations in Passive Radar

Target position and velocity estimation using a passive radar with multiple signals of opportunity and multiple receive stations is investigated. The maximum likelihood (ML) estimate of the unknown position and velocity vector of a target is presented. Formulas bounding the best possible mean square error are provided, via the Cramer-Rao lower bound, for any unbiased estimator of target position and velocity. The model assumes a single target, a single receive antenna at each receive station, spatially and temporally white Gaussian clutter-plus-noise, and uncorrelated reflection coefficients. To describe the best possible performance, it is assumed that the signals of opportunity are estimated perfectly from the direct path reception. For a specific example where the signals of opportunity come from the Global System for Mobile (GSM) communication system, the optimum possible estimation performance is presented using numerical examples. It is shown that it is possible to obtain large performance gains through using multiple signals of opportunity and multiple receive stations.