Information-based sensor management and IMMKF

This paper describes an algorithm using a discrimination- based sensor effectiveness metric for sensor assignment in multisensor multitarget tracking applications. The algorithm uses interacting multiple model Kalman filters to track airborne targets with measurements obtained from two or more agile-beam radar systems. Each radar has capacity constraints on the number of targets it can observe on each scan. For each scan the expected discrimination gain is computed for the sensor target pairings. The constrained globally optimum assignment of sensor to targets is then computed and applied. This is compared to a fixed assignment schedule in simulation testing. We find that discrimination based assignment improves track accuracy as measured by both the root-mean-square position error and a measure of the total covariance.