IMM-UGHF-NJ for continuous wave bistatic sonar tracking with propagation delay

Acoustic propagation delay has not been investigated for a continuous wave multistatic sonar tracking system except for the recent study conducted by Jauffret et al. [4], which estimates the trajectory of a constant velocity target. The results showed that the estimate bias caused by the propagation delay is not negligible, especially for a bistatic system. This paper develops an interacting multiple model unscented Gauss-Helmert filter with numerical Jacobian (IMM-UGHF-NJ) to track a maneuvering target with propagation delay using a bistatic sonar system. The IMM-UGHF-NJ can overcome the two tracking challenges introduced by the delay, namely, implicit state transition model and lack of analytical expression of the Doppler shifted frequency in the measurement model. Simulation tests have been conducted, and the results show that the IMM-UGHF-NJ can reduce the estimation error significantly, especially for fast moving targets.

[1]  Claude Jauffret,et al.  Doppler-only target motion analysis in a high duty cycle sonar system , 2016, 2016 19th International Conference on Information Fusion (FUSION).

[2]  Xionghu Zhong,et al.  Linear fitting Kalman filter , 2016, IET Signal Process..

[3]  Cherry Wakayama,et al.  Multistatic tracking for continous active sonar using Doppler-bearing measurements , 2013, Proceedings of the 16th International Conference on Information Fusion.

[4]  Rong Yang,et al.  Interacting multiple model unscented Gauss-Helmert filter for bearings-only tracking with state-dependent propagation delay , 2014, 17th International Conference on Information Fusion (FUSION).

[5]  Ting Yuan,et al.  A Multiple IMM Estimation Approach with Unbiased Mixing for Thrusting Projectiles , 2012, IEEE Transactions on Aerospace and Electronic Systems.

[6]  Yaakov Bar-Shalom,et al.  Comparison of altitude estimation using 2D and 3D radars over spherical earth , 2016, 2016 IEEE Aerospace Conference.

[7]  Rong Yang,et al.  UGHF for acoustic tracking with state-dependent propagation delay , 2015, IEEE Transactions on Aerospace and Electronic Systems.

[8]  Rong Yang,et al.  The linear fitting Kalman filter for nonlinear tracking , 2015, 2015 IEEE 5th Asia-Pacific Conference on Synthetic Aperture Radar (APSAR).

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

[10]  Gee Wah Ng,et al.  Maneuvering Target Tracking Using Continuous Wave Bistatic Sonar with Propagation Delay , 2018 .

[11]  Yaakov Bar-Shalom,et al.  A note on "book review tracking and data fusion: A handbook of algorithms" [Authors' reply] , 2013 .

[12]  T.C. Yang Acoustic Dopplergram for Intruder Defense , 2007, OCEANS 2007.