TY - JOUR
T1 - Maneuvering target tracking with modified unbiased FIR filter
AU - Fu, Jinbin
AU - Sun, Jinping
AU - Lu, Songtao
AU - Zhang, Yaotian
PY - 2015/1/1
Y1 - 2015/1/1
N2 - In the field of maneuvering target tracking, the performance of Kalman filter(KF)and its variants is dependeds on the accuracy of the assumed process noise statistics. If the assumed process noise is not accurate, the performance of the KF and its improved algorithms will be degraded significantly. In some cases, the filters might even cannot be converged. Unbiased finite impulse response (UFIR) filter does not need the prior knowledge of the process noise statistics during filtering. Hence, it can be utilized to overcome the problem of the inaccurate assumed process noise statistics to realize the maneuvering target tracking. Since the generalized noise power gain (GNPG) of the existing UFIR filter cannot be adapted to the measurements innovation, an improved UFIR filter was proposed. The proposed UFIR dynamically adjusts GNPG according to the ratio of measurements innovations between the adjacent time such that it can improve the detecting ability of the UFIR filter for target maneuver. The simulation results illustrate that if assumed process noise is accurate, the performance of the existing UFIR filter and the proposed FIR filter is similar to KF; but if assumed process noise is not accurate, the performance of the proposed UFIR shows better than the other ones.
AB - In the field of maneuvering target tracking, the performance of Kalman filter(KF)and its variants is dependeds on the accuracy of the assumed process noise statistics. If the assumed process noise is not accurate, the performance of the KF and its improved algorithms will be degraded significantly. In some cases, the filters might even cannot be converged. Unbiased finite impulse response (UFIR) filter does not need the prior knowledge of the process noise statistics during filtering. Hence, it can be utilized to overcome the problem of the inaccurate assumed process noise statistics to realize the maneuvering target tracking. Since the generalized noise power gain (GNPG) of the existing UFIR filter cannot be adapted to the measurements innovation, an improved UFIR filter was proposed. The proposed UFIR dynamically adjusts GNPG according to the ratio of measurements innovations between the adjacent time such that it can improve the detecting ability of the UFIR filter for target maneuver. The simulation results illustrate that if assumed process noise is accurate, the performance of the existing UFIR filter and the proposed FIR filter is similar to KF; but if assumed process noise is not accurate, the performance of the proposed UFIR shows better than the other ones.
KW - Adaptation
KW - Generalized noise power gain
KW - Kalman filter
KW - Maneuvering target tracking
KW - Unbiased finite impulse response filter
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U2 - 10.13700/j.bh.1001-5965.2014.0068
DO - 10.13700/j.bh.1001-5965.2014.0068
M3 - Article
AN - SCOPUS:84924733481
SN - 1001-5965
VL - 41
SP - 77
EP - 82
JO - Beijing Hangkong Hangtian Daxue Xuebao/Journal of Beijing University of Aeronautics and Astronautics
JF - Beijing Hangkong Hangtian Daxue Xuebao/Journal of Beijing University of Aeronautics and Astronautics
IS - 1
ER -