Application of a Recursive Method for Registration Error Correction in Tracking with Multiple Sensors

This paper addresses the issue of the correction of registration errors due to the presence of biases in the measurements when multiple sensors are used for tracking targets. The problem is formulated as one of recursively estimating biases, and is addressed by an application of the technique, using an augmented Kalman filter, of simultaneously estimating the sensor biases and the state vector (of track parameters), the latter assuming that no biases are present. Simulation results are presented comparing the performance of the recursive algorithm with that of a generalized least squares method, which is applicable when targets with known positions are available for measurement by the sensors. Results are also presented for a two-sensor case when the extended Kalman filter is used as the tracking filter.