BACKGROUND OF THE INVENTION

This invention introduces additional details regarding calibration and geolocation techniques first introduced in the prior referenced applications. This application focuses on simplified channel models and techniques that can exploit those models for geolocation and object classification.

SUMMARY OF THE INVENTION

In one embodiment, there is provided a method of parameter estimation in a multi-channel signal environment where a plurality of receive antennas and/or a plurality of transmitters transmit a signal that is known or estimated, that is processed over multiple frequencies or channels, by a digital receiver and one or more processors whose processing includes the following steps. First, an analytic or table driven channel model is used for comparing received voltages vs a calibrated template, without only relying on information lossy intermediate steps such as delay or angle measurements. A statistical likelihood function is used to model the receiver noise, channel parameters, or prior channel uncertainty. Then a Bayesian detection or other Statistical Signal Processing Techniques is used for the estimation of channel parameters such as location parameters, shape parameters, and reflector electromagnetic parameters. A saving target reflector/emitter parameters is reused for dynamic tracking. Finally, Bayesian particle filtering or Maximum Likelihood Methods is used to update mixture models for the unknown parameters.

Numerous other advantages and features of the invention will become readily apparent from the following detailed description of the invention and the embodiments thereof, from the claims, and from the accompanying drawings.

