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Abstract: The trajectory of a shipborne radar target has a certain complexity, randomness, and diversity. Tracking a strong maneuvering target timely, accurately, and effectively is a key technology for a shipborne radar tracking system. Combining a variable structure interacting multiple model with an adaptive grid algorithm, we present a variable structure adaptive grid interacting multiple model maneuvering target tracking method. Tracking experiments are performed using the proposed method for five maneuvering targets, including a uniform motion - uniform acceleration motion target, a uniform acceleration motion - uniform motion target, a serpentine locomotion target, and two variable acceleration motion targets. Experimental results show that the target position, velocity, and acceleration tracking errors for the five typical target trajectories are small. The method has high tracking precision, good stability, and flexible adaptability.

[1]Blom, H.A.P., Bar-Shalom, Y., 1988. Interacting multiple model algorithm for systems with Markovian switching coefficients. IEEE Trans. Autom. Control, 33(8):780-783.

[2]Foo, P.H., Ng, G.W., 2011. Combining the interacting multiple model method with particle filters for maneuvering target tracking. IET Radar Sonar Navig., 5(3):234-255.

[3]Ge, Q.B., Li, W.B., Wen, C.L., 2011. SCKF-STF-CN: a universal nonlinear filter for maneuver target tracking. J. Zhejiang Univ.-Sci. C (Comput. & Electron.), 12(8):678-686.

[4]Li, H., Shen, Y., Zhang, A., Cheng, C., 2006. The status quo and trend of target tracking based on interactive multiple model. Fire Control Command Control, 31(11):1-4 (in Chinese).

[5]Li, X.R., Bar-Shalom, Y., 1993. Design of an interacting multiple model algorithm for air traffic control tracking. IEEE Trans. Control Syst. Technol., 1(3):186-194.

[6]Liu, G.F., Gu, X.F., Wang, H.N., 2009. Design and comparison of two MM algorithms for strong maneuvering target tracking. J. Syst. Simul., 21(4):965-968 (in Chinese).

[7]Magill, D.T., 1965. Optimal adaptive estimation of sampled stochastic processes. IEEE Trans. Autom. Control, 10(4):434-439.

[8]Messaoudi, Z., Ouldali, A., Oussalah, M., 2010. Comparison of Interactive Multiple Model Particle Filter and Interactive Multiple Model Unscented Particle Filter for Tracking Multiple Manoeuvring Targets in Sensors Array. IEEE 9th Int. Conf. on Cybernetic Intelligent Systems, p.1-6.

[9]Munir, A., Atherton, D.P., 1995. Adaptive interacting multiple model algorithm for tracking a maneuvering target. IEEE Proc. Radar Sonar Navig., 142(1):11-17.

[10]Peng, L., 2007. Research on Maneuvering Target Tracking Algorithm. PhD Thesis, Northwestern Polytechnical University, Xi’an, China (in Chinese).

[11]Xu, J.H., Ji, C.X., Zhang, Y.S., Chen, K., 2003. Digraph switching IMM algorithm based current statistical model. Fire Control Command Control, 28(2):52-56 (in Chinese).

[12]Yuan, D.P., Zheng, J.Y., 2011. Interacting Multiple Model Target Tracking Algorithm Based on Particle Filtering. IEEE CIE Int. Conf. on Radar, p.1907-1910.

[13]Zhang, H.J., Gong, J.W., Jiang, Y., Xiong, G.M., Chen, H.Y., 2012. An iterative linear quadratic regulator based trajectory tracking controller for wheeled mobile robot. J. Zhejiang Univ.-Sci. C (Comput. & Electron.), 13(8):593-600.

[14]Zhang, M., Chen, W.D., 2010. Variable Structure Multiple Model Particle Filter for Maneuvering Radar Target Tracking. Int. Conf. on Microwave and Millimeter Wave Technology, p.1754-1757.

[15]Zhu, Z.Y., 2008. Adaptive IMM tracking algorithm based on fuzzy inference. J. Project. Rock. Missiles Guid., 28(1):29-32, 36 (in Chinese).