Cramér–Rao Lower Bound Analysis for Stochastic Model Based Target Parameter Estimation in Multistatic Passive Radar With Direct-Path Interference

This paper addresses the problem of Cramér-Rao lower bound (CRLB) analysis for joint target location and velocity estimation in a multistatic passive radar system comprised of multiple noncooperative illuminators of opportunity (IOs) and multiple geographically separated receivers. Unlike other existing studies, special attention in this paper is paid to a more ubiquitous scenario, in which no reference channel exists in receiver networks. Besides, the situation where the measurements collected at the receivers are contaminated by the interference directly illuminated from the IOs is taken into account. Namely, each receive station simultaneously obtains direct-path interference (DPI) from all the IOs and echo signals reflected by the target. Furthermore, the IO waveform is modeled as a stochastic process in which samples of the unknown IO waveform are treated as a complex Gaussian sequence. Finally, the effects of multipath clutter on the signal model and CRLB are well analyzed. The numerical results are provided to prove that the joint CRLB is not only a function of the signal-to-noise ratio (SNR), DPI-to-noise ratio (DNR), and clutter-to-noise ratio (CNR) but also associated with both IO waveform parameters and relative geographical distribution of the system.