Underwater Target Tracking Algorithm Based on Improved Adaptive IMM-UKF

WANG Pingbo; LIU Yang

doi:10.11999/JEIT211128

Volume 44 Issue 6

Jun. 2022

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WANG Pingbo, LIU Yang. Underwater Target Tracking Algorithm Based on Improved Adaptive IMM-UKF[J]. Journal of Electronics & Information Technology, 2022, 44(6): 1999-2005. doi: 10.11999/JEIT211128

Citation:

WANG Pingbo, LIU Yang. Underwater Target Tracking Algorithm Based on Improved Adaptive IMM-UKF[J]. Journal of Electronics & Information Technology, 2022, 44(6): 1999-2005. doi: 10.11999/JEIT211128

WANG Pingbo, LIU Yang. Underwater Target Tracking Algorithm Based on Improved Adaptive IMM-UKF[J]. Journal of Electronics & Information Technology, 2022, 44(6): 1999-2005. doi: 10.11999/JEIT211128

Citation:

WANG Pingbo, LIU Yang. Underwater Target Tracking Algorithm Based on Improved Adaptive IMM-UKF[J]. Journal of Electronics & Information Technology, 2022, 44(6): 1999-2005. doi: 10.11999/JEIT211128

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Underwater Target Tracking Algorithm Based on Improved Adaptive IMM-UKF

doi: 10.11999/JEIT211128

WANG Pingbo,
LIU Yang^,

College of Electronic Engineering, Naval University of Engineering, Wuhan 430033, China

Received Date: 2021-10-14
Accepted Date: 2022-04-30
Rev Recd Date: 2022-04-17

Available Online: 2022-05-06

Publish Date: 2022-06-21

Abstract

Abstract

To solve the lack of model switching and tracking accuracy of the existing Adaptive Interacting Multiple Model (AIMM) in the underwater target tracking, combined with the Unscented Kalman Filter, an improved AIMM-UKF algorithm is proposed. On the basis of adaptively modifying the Markov probability transition matrix, this algorithm uses the decision window to modify it twice to increase the probability of the matching model observably and reduce the effects of the mismatch model. Simulation results show that compared with the original adaptive algorithm, the improved algorithm can make fuller use of posterior information, has a better model switching speed, and improves tracking accuracy by about 24%.
- Underwater target tracking,
- Interacting Multiple Model-Unscented Kalman Filter (IMM-UKF),
- Adaptive,
- Probability transition matrix,
- Decision window

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References(13)

References

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