Enhanced sequential nonlinear tracking filter with denoised pseudo measurements

Sequential nonlinear tracking filter using pseudo measurements has been proposed to solve the tracking problem with range-rate measurements. Replacing the range-rate measurement by pseudo measurement constructed by the product of range and range-rate measurements can reduce nonlinearity, but large covariance of the error of pseudo measurements may be introduced. A denoising method based on a debiased Kalman filter is proposed in this paper to reduce the error of pseudo measurements. Then the denoised pseudo measurements are processed sequentially with position measurements to establish a new tracking filter with range-rate measurements. The proposed filtering method can reduce not only the nonlinearity but also the error of pseudo measurements. Monte Carlo simulations show that the performance of the new tracking filter is better than the sequential filter using pseudo measurement without denoising.

[1]  P. Suchomski.  Explicit expressions for debiased statistics of 3D converted measurements , 1999 .

[2]  Alfred O. Hero,et al.  Radar data processing: Vol. I-Introduction and tracking , 1986, IEEE Trans. Acoust. Speech Signal Process..

[3]  Chongzhao Han,et al.  Sequential unscented Kalman filter for radar target tracking with range rate measurements , 2005, 2005 7th International Conference on Information Fusion.

[4]  Yoshio Kosuge,et al.  Target tracking under dense environments using range rate measurements , 1998, Proceedings of the 37th SICE Annual Conference. International Session Papers.

[5]  Zhansheng Duan.  Sequential Nonlinear Tracking Filter with Range-rate Measurements in Spherical Coordinates , 2004 .

[6]  Branko Ristic,et al.  On polar and versus Cartesian coordinates for target tracking , 1999, ISSPA '99. Proceedings of the Fifth International Symposium on Signal Processing and its Applications (IEEE Cat. No.99EX359).

[7]  Yaping Dai,et al.  A target tracking algorithm with range rate under the color measurement environment , 1999, SICE '99. Proceedings of the 38th SICE Annual Conference. International Session Papers (IEEE Cat. No.99TH8456).

[8]  Peikun He,et al.  Use of the radial velocity measurement in target tracking , 2003 .

[9]  Chongzhao Han,et al.  Sequential nonlinear tracking using UKF and raw range-rate measurements , 2007, IEEE Transactions on Aerospace and Electronic Systems.

[10]  Y. Bar-Shalom,et al.  Unbiased converted measurements for tracking , 1998 .

[11]  X. R. Li,et al.  A Survey of Maneuvering Target Tracking—Part III: Measurement Models , 2001 .

[12]  Yunmin Zhu,et al.  Optimal linear unbiased filtering with polar measurements for target tracking , 2002, Proceedings of the Fifth International Conference on Information Fusion. FUSION 2002. (IEEE Cat.No.02EX5997).

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

[14]  Jang Gyu Lee,et al.  Improved Kalman filter design for three-dimensional radar tracking , 2001 .

[15]  Jeffrey K. Uhlmann,et al.  A consistent, debiased method for converting between polar and Cartesian coordinate systems , 1997 .

[16]  Han Chong-zhao.  Radar Target Tracking with Doppler Measurements in Polar Coordinates , 2004 .