Bayesian Cramer-Rao bounds for multistatic radar
Harry L. Van Trees, Kristine L. Bell, Yige Wang · 2006
The Bayesian Cramer-Rao bound (BCRB) on the mean square error in tracking the position and velocity of a moving target in a multistatic radar system is formulated and a recursive bound on the state variables as a function of time is derived based on the nonlinear filtering bound developed by Tichavsky et al (1998). The result is an error bound ellipse in the xy-plane that evolves as the target moves along its trajectory. The recursive BCRB provides an efficient technique to analyze various system design trade-offs including the effect of transmitter-receiver geometry, the contribution of each transmitter to tracking accuracy, the effect of angular estimation accuracy.