Multistatic Target and Sensor Field Tracking

Multistatic active target tracking in GPS-denied scenarios is complicated by the fact that the emitter and receiver locations are unknown and must be estimated jointly with the target track. Maximum a posteriori algorithms for solving this joint estimation problem are complicated by the nonlinearities in the likelihood function of the bistatic range measurement. A new integral representation of this likelihood function is presented for small measurement error variances. Remarkably, target state appears linearly in this integral. This paper presents a new approach to the basic problem of target state estimation for known sensor locations. The optimal estimator derived from the integral representation is an iteratively re-weighted linear Kalman smoother. Joint estimators for target and emitter-receiver field tracking will be reported elsewhere.