Throwing Down The Gauntlet: A Discussion Of Techniques For Bounding Advanced Tracking Algorithm Performance

For many applications of radar and sensor based filtering, simulations can not represent the sole estimate of performance, provide points where threats become engagable, or determine when to use weapons' platform based sensors effectively in an engagement, etc... No significant advances have been proposed to analytically characterize performance or at least bound performance of the Kalman filter other than the use of simple two or three state constant gain filters. This paper suggests methods for characterizing filter algorithms that can be used to bound the advanced tracking algorithms that are used in a single sensor or multi-sensor environment

[1]  T. Benedict,et al.  Synthesis of an optimal set of radar track-while-scan smoothing equations , 1962 .

[2]  H. K. Kesavan,et al.  The generalized maximum entropy principle , 1989, IEEE Trans. Syst. Man Cybern..

[3]  J.E. Gray,et al.  The solution to the Lyapunov equation in constant gain filtering and some of its applications , 2004, Thirty-Sixth Southeastern Symposium on System Theory, 2004. Proceedings of the.

[4]  John Skilling,et al.  Maximum Entropy and Bayesian Methods , 1989 .

[5]  J.E. Gray,et al.  Theory of distributed estimation using multiple asynchronous sensors , 2005, IEEE Transactions on Aerospace and Electronic Systems.

[6]  Y. Bar-Shalom.  Tracking and data association , 1988 .

[7]  David Strauss.  On a general class of models for interaction , 1986 .

[8]  L. Bloomer,et al.  Are more models better?: the effect of the model transition matrix on the IMM filter , 2002, Proceedings of the Thirty-Fourth Southeastern Symposium on System Theory (Cat. No.02EX540).

[9]  Samuel S. Blackman,et al.  Multiple-Target Tracking with Radar Applications , 1986 .

[10]  John Skvoretz,et al.  Complexity theory and models for social networks , 2002 .

[11]  J. Gray,et al.  Solutions of matrix equations arising in track filter theory , 1998, Proceedings of Thirtieth Southeastern Symposium on System Theory.

[12]  What do filter coefficient relationships mean? , 2004, Thirty-Sixth Southeastern Symposium on System Theory, 2004. Proceedings of the.

[13]  J. Gray,et al.  Target tracking with explicit control of filter lag , 1997, Proceedings The Twenty-Ninth Southeastern Symposium on System Theory.

[14]  H. Simpson,et al.  Performance measures and optimization condition for a third-order sampled-data tracker , 1963 .

[15]  S. Neal,et al.  Discussion on "Parametric relations for the α-β-ν filter predictor" , 1967 .

[16]  Paul R. Kalata,et al.  α-β target tracking systems: a survey , 1992, 1992 American Control Conference.

[17]  Hua Lee,et al.  Maximum Entropy and Bayesian Methods. , 1996 .