Unscented Kalman Filters for Multiple Target Tracking With Symmetric Measurement Equations

The symmetric measurement equation approach to multiple target tracking is revisited using the unscented Kalman filter. The performance of this filter is compared to the original symmetric measurement equation implementation using an extended Kalman filter. Counterintuitive results are presented and explained for two sets of symmetric measurement equations. We find that the performance of the SME approach is dependent on the interaction of the SME equations and filter used. Furthermore, an SME/unscented Kalman filter pairing is shown to have improved performance versus previous approaches while possessing simpler implementation and equivalent computational complexity.

[1]  Nando de Freitas,et al.  Sequential Monte Carlo Methods in Practice , 2001, Statistics for Engineering and Information Science.

[2]  E. Kamen,et al.  Introduction to Optimal Estimation , 1999 .

[3]  E. Kamen,et al.  SME filter approach to multiple target tracking with radar measurements , 1993 .

[4]  Bahram Shafai,et al.  Improving stability of EKF filter used by the symmetrical measurement equation approach to multiple-target tracking , 1999, Optics & Photonics.

[5]  S. Haykin Kalman Filtering and Neural Networks , 2001 .

[6]  E. Kamen,et al.  Multiple Target Tracking based on Symmetric Measurement Equations , 1989, 1989 American Control Conference.

[7]  Jeffrey K. Uhlmann,et al.  New extension of the Kalman filter to nonlinear systems , 1997, Defense, Security, and Sensing.

[8]  Fred Daum,et al.  A Cramér-Rao Bound for Multiple Target Tracking , 1991 .

[9]  Douglas J. Muder,et al.  Multidimensional SME filter for multitarget tracking , 1993, Defense, Security, and Sensing.

[10]  K. Kastella,et al.  Event-averaged maximum likelihood estimation and mean-field theory in multitarget tracking , 1995, IEEE Trans. Autom. Control..

[11]  T. Singh,et al.  The higher order unscented filter , 2003, Proceedings of the 2003 American Control Conference, 2003..

[12]  Edward W. Kamen,et al.  SME filter approach to multiple target tracking with false and missing measurements , 1993, Defense, Security, and Sensing.

[13]  Jeffrey K. Uhlmann,et al.  Unscented filtering and nonlinear estimation , 2004, Proceedings of the IEEE.

[14]  Jeffrey K. Uhlmann,et al.  Comment on "A new method for the nonlinear transformation of means and covariances in filters and estimators" [with authors' reply] , 2002, IEEE Transactions on Automatic Control.

[15]  Hugh F. Durrant-Whyte,et al.  A new method for the nonlinear transformation of means and covariances in filters and estimators , 2000, IEEE Trans. Autom. Control..

[16]  Edward W. Kamen,et al.  Multiple target tracking using products of position measurements , 1993 .

[17]  Simon J. Julier,et al.  The scaled unscented transformation , 2002, Proceedings of the 2002 American Control Conference (IEEE Cat. No.CH37301).

[18]  Herman Bruyninckx,et al.  Comment on "A new method for the nonlinear transformation of means and covariances in filters and estimators" [with authors' reply] , 2002, IEEE Trans. Autom. Control..