Maneuvering Target Tracking Algorithm Based on IMM-Ultimate Iterative UFIR

WU Qinghai; QU Zhaoyang

doi:10.3969/j.issn.1671-637x.2018.06.008

[1] KIM J W, LEE M S, LEE S S.Vehicular pitch estimation algorithm with ACF/IMMKF based on GPS/IMU/OBD data fusion［J］.The Journal of Korean Institute of Communications and Information Sciences, 2015, 40(9):1837-1845.

[3] YANG F, PAN Q, LIANG Y, et al.Interacting multiple model unscented Kalman filter［C］//The 24th Chinese Control Conference, 2005：314-317.

[5] SU X H, WANG S, PECHT M, et al. Interacting multiple model particle filter for prognostics of lithium-ion batteries［J］.Microelectronics Reliability, 2017, 70:59-69.

[6] CHOI I H, PAK J M, AHN C K, et al. New preceding vehicle tracking algorithm based on optimal unbiased finite memory filter［J］.Measurement, 2015，73：262-274.

[7] PAK J M, AHN C K, SHMALIY Y S, et al.Switching extensible FIR filter bank for adaptive horizon state estimation with applications［J］.IEEE Transactions on Control Systems Technology, 2016, 24(3)：1052-1058.

[8] SHMALIY Y S, SIMON D. Iterative unbiased FIR state estimation:a review of algorithms［J］.EURASIP Journal on Advances in Signal Processing, 2013, 113(1)：1-16.

[9] SHMALIY Y S. An iterative Kalman-like algorithm ignoring noise and initial conditions［J］.IEEE Transactions on Signal Processing, 2011, 59(6)：2465-2473.

[10] KIM P S, LEE M E. A new FIR filter for state estimation and its applications［J］.Journal of Computer Science and Technology, 2007, 22(5)：779-784.

[11] SHMALIY Y S, KHAN S, ZHAO S Y. Ultimate iterative UFIR filtering algorithm［J］.Measurement, 2016, 92:236-242.