Estimation of the Target State with Passive Measurements and Prior Range Information

This work demonstrates a simple but effective method by which prior information on the target range can be included in the likelihood function for bearings-only as well as Doppler-bearings target motion analysis. The prior information is treated as a pseudomeasurement with a Gaussian distribution. An estimator is derived as an extension to the well-known maximum likelihood estimator. The performance bounds naturally follow as an extension to the Cramer-Rao lower bound. Utilization of the range pseudomeasurement adds new design parameters to the estimator, for which practical methodology and illustrative examples are provided. The estimation efficiency is confirmed via the use of Monte-Carlo simulations.