Combined Kalman filter (CKF) and JVC algorithms for AEW target tracking applications
Robert W. Schutz, Richard A. McAllister, Bruce Engelberg, Vincent Maone, R. V. Helm, Val Kats, Charles Dennean, Warren Soper, L.E.L. Moran · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 1997
Tracking for airborne early warning (AEW) weapon systems present a number of formidable challenges for any tracking and data fusion algorithms. Realistic scenarios involve thousands of targets in highly cluttered environments with multiple sensors. The E-2C weapon system must detect, track and identify these targets in as small a time frame as possible. As part of ongoing E-2C advanced tracking algorithm development activities a novel approach has been developed that utilizes the debiased coordinate conversion filter developed by Bar-Shalom and Lerro (1993) for range, and azimuth angle processing from the radar and standard EKF for rdot and other angular measurements from other sensors identified as a combined Kalman filter (CKF). To solve the data association problem the JVC algorithm [Jonker-Volgenant Castanon (1988)] was chosen because of favorable results from published studies and internally conducted in-house studies that demonstrate its speed and efficiency in solving the assignment problem for sparse matrices which is typical for E-2C applications. Results shown are based on a scenario consisting of 120 straight line and maneuvering targets overlaid on a previously recorded dense radar environment. Future plans have been initiated to incorporate other sensors and consider other association algorithms such as multi-hypothesis tracking (MHT) or interactive multiple model joint probabilistic data association filter (IMMJPDAF).