Covariance Intersection for Multi-Sensor Ballistic Missile Tracking
Mack O. Pasqual, Daniel A. DeLaurentis · 2012
This paper describes the application of the covariance intersection algorithm to the multi-sensor ballistic missile tracking problem. The fusion of measurements from multiple radar or infrared sensors can signicantly improve tracking performance when compared to a sensor working in isolation. The covariance intersection algorithm is demonstrated as an eective method for extending single sensor tracking algorithms to a multiple sensor context. A sample scenario is shown to demonstrate the problems with the tracking a ballistic missile using a single infrared sensor. By using data from a second infrared sensor, these problems can be remedied eectively. It is shown that even infrequent periodic measurements from a secondary sensor can make infrared-only tracking feasible and that varying the period of these measurements provides a method for maintaining a desired covariance for a track.