An adaptive Gaussian sum algorithm for radar tracking

Abstract In this paper, we propose a new radar tracking algorithm based on the Gaussian sum filter. To alleviate the computational burden associated with the Gaussian sum filter, we have developed a new systematic and efficient way to approximate a non-Gaussian and measurement-dependent function by a weighted sum of Gaussian density functions and we have also suggested a way to alleviate the growing memory problem inherited in the Gaussian sum filter. Our method is compared with the extended Kalman filter (EKF) and the converted measurement Kalman filter (CMKF) and it is shown to be more accurate in term of position and velocity errors.

[1]  Yaakov Bar-Shalom,et al.  Tracking with debiased consistent converted measurements versus EKF , 1993 .

[2]  A.H. Haddad,et al.  Applied optimal estimation , 1976, Proceedings of the IEEE.

[3]  A. Jazwinski.  Stochastic Processes and Filtering Theory , 1970 .

[4]  Yaakov Bar-Shalom,et al.  Estimation and Tracking: Principles, Techniques, and Software , 1993 .

[5]  Pramod K. Varshney,et al.  Measurement preprocessing for nonlinear target tracking , 1993 .

[6]  Demetrios G. Lainiotis,et al.  Adaptive deconvolution of seismic signals-performance, computational analysis, parallelism , 1988, IEEE Trans. Acoust. Speech Signal Process..

[7]  E. Cortina,et al.  Maneuvering target tracking using extended Kalman filter , 1991 .

[8]  Simon Braun,et al.  Signal processing, the model-based approach: James V. Candy, 230 pages, McGraw-Hill, New York, 1986. , 1987 .

[9]  H. Sorenson,et al.  Recursive bayesian estimation using gaussian sums , 1971 .

[10]  D. Lainiotis,et al.  Partitioning: A unifying framework for adaptive systems, I: Estimation , 1976, Proceedings of the IEEE.

[11]  Demetrios G. Lainiotis,et al.  On the parallel implementations of the linear Kalman and Lainiotis filters and their efficiency , 1991, Signal Process..

[12]  Allen R. Stubberud,et al.  Gaussian sum approximation for non-linear fixed-point prediction , 1983 .

[13]  Jason L. Speyer,et al.  The Modified Gain Extended Kalman Filter and Parameter Identification in Linear Systems , 1984, 1984 American Control Conference.

[14]  Arthur Gelb,et al.  Applied Optimal Estimation , 1974 .