Adaptive filtering for single target tracking

Maria Scalzo; Gregory Horvath; Eric Jones; Adnan Bubalo; Mark Alford; Ruixin Niu; Pramod K. Varshney

doi:10.1117/12.819451

11 May 2009 Adaptive filtering for single target tracking

Maria Scalzo, Gregory Horvath, Eric Jones, Adnan Bubalo, Mark Alford, Ruixin Niu, Pramod K. Varshney

Proceedings Volume 7336, Signal Processing, Sensor Fusion, and Target Recognition XVIII; 73360C (2009) https://doi.org/10.1117/12.819451
Event: SPIE Defense, Security, and Sensing, 2009, Orlando, Florida, United States

Abstract

Many algorithms may be applied to solve the target tracking problem, including the Kalman Filter and different types of nonlinear filters, such as the Extended Kalman Filter (EKF), Unscented Kalman Filter (UKF) and Particle Filter (PF). This paper describes an intelligent algorithm that was developed to elegantly select the appropriate filtering technique depending on the problem and the scenario, based upon a sliding window of the Normalized Innovation Squared (NIS). This technique shows promise for the single target, single radar tracking problem domain. Future work is planned to expand the use of this technique to multiple targets and multiple sensors.

Citation Download Citation

Maria Scalzo, Gregory Horvath, Eric Jones, Adnan Bubalo, Mark Alford, Ruixin Niu, and Pramod K. Varshney "Adaptive filtering for single target tracking", Proc. SPIE 7336, Signal Processing, Sensor Fusion, and Target Recognition XVIII, 73360C (11 May 2009); https://doi.org/10.1117/12.819451

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