@inproceedings{66583661f32c40099a6e2c2973f5699c,
title = "Adaptive filtering for single target tracking",
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.",
keywords = "Consistency checks, Extended kalman filter, Filter suite, Particle filter, Tracking, Unscented kalman filter",
author = "Maria Scalzo and Gregory Horvath and Eric Jones and Adnan Bubalo and Mark Alford and Ruixin Niu and Varshney, {Pramod K.}",
year = "2009",
doi = "10.1117/12.819451",
language = "English (US)",
isbn = "9780819476029",
series = "Proceedings of SPIE - The International Society for Optical Engineering",
booktitle = "Signal Processing, Sensor Fusion, and Target Recognition XVIII",
note = "Signal Processing, Sensor Fusion, and Target Recognition XVIII ; Conference date: 13-04-2009 Through 15-04-2009",
}