Title :
A novel application of the unscented transformation to the debiased CMKF
Author :
Spitzmiller, John N.
Author_Institution :
Nat. Security Bus. Unit, Cobham Anal. Solutions, Huntsville, AL, USA
Abstract :
This paper presents a modification to the original debiased converted-measurement Kalman filter (CMKF), a modern estimation algorithm used for long-range radar and sonar target tracking. The modification improves the original debiased CMKF by approximating the Cartesian-prediction-conditioned means of the converted-measurement error´s true bias and covariance using a novel application of the unscented transformation (UT). Simulations show the improved performance of the modified debiased CMKF over that of the original debiased CMKF.
Keywords :
Kalman filters; estimation theory; sonar tracking; target tracking; UT; cartesian-prediction-conditioned; debiased CMKF; debiased converted-measurement Kalman filter; estimation algorithm; long-range radar; sonar target tracking; unscented transformation; Approximation methods; Coordinate measuring machines; Kalman filters; Measurement uncertainty; Position measurement; Prediction algorithms; Radar tracking;
Conference_Titel :
Southeastcon, 2011 Proceedings of IEEE
Conference_Location :
Nashville, TN
Print_ISBN :
978-1-61284-739-9
DOI :
10.1109/SECON.2011.5752956
