Journal
SENSORS
Volume 16, Issue 6, Pages -Publisher
MDPI
DOI: 10.3390/s16060805
Keywords
target tracking; cubature Kalman filter; unscented Kalman filter; interacting multiple models
Funding
- National Natural Science Foundation [61571148]
- China Postdoctoral Science Foundation Grant [2014M550182]
- Heilongjiang Postdoctoral Special Fund [LBH-TZ0410]
- Innovation of Science and Technology Talents in Harbin [2013RFXXJ016]
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In order to improve the tracking accuracy, model estimation accuracy and quick response of multiple model maneuvering target tracking, the interacting multiple models five degree cubature Kalman filter (IMM5CKF) is proposed in this paper. In the proposed algorithm, the interacting multiple models (IMM) algorithm processes all the models through a Markov Chain to simultaneously enhance the model tracking accuracy of target tracking. Then a five degree cubature Kalman filter (5CKF) evaluates the surface integral by a higher but deterministic odd ordered spherical cubature rule to improve the tracking accuracy and the model switch sensitivity of the IMM algorithm. Finally, the simulation results demonstrate that the proposed algorithm exhibits quick and smooth switching when disposing different maneuver models, and it also performs better than the interacting multiple models cubature Kalman filter (IMMCKF), interacting multiple models unscented Kalman filter (IMMUKF), 5CKF and the optimal mode transition matrix IMM (OMTM-IMM).
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