Affiliation:
1. School of Electronic and Optical Engineering, Nanjing University of Science and Technology, Nanjing 210094, China
Abstract
A pulse-Doppler (PD) radar has the advantage of strong anti-interference ability, and it is often used as a solution for maneuvering target tracking. In the application of target monitoring and tracking in PD radars, the interacting multiple model algorithm (IMM) has become the main and preferred choice due to its flexibility and high accuracy. However, the probability transfer matrix in classical IMM algorithms generally depends on constant prior knowledge, and if a PD radar is tracking a strong maneuvering target, it is inevitable to encounter some limitations, such as the possibility of target tracking trajectory deviation, and even a loss of the target. The Markov probability transfer matrix is proposed with an adaptive modification ability in real time to overcome the above problems in this paper. Additionally, for improving the speed of switching between the models, the fuzzy control system for secondary updating of model probability is adopted. By this means, the tracking accuracy of maneuvering targets is enhanced. Compared with the classical IMM algorithm, the corresponding simulation results for the PD radar indicate that the overall tracking accuracy of the proposed adaptive IMM algorithm is improved by 19.6%. In conclusion, the continuity and accuracy of the target trajectory can be effectively improved with the proposed adaptive IMM algorithm in PD radar cases.
Reference33 articles.
1. Research on adaptive Markov matrix IMM tracking algorithm;Syst. Eng. Electron.,2013
2. Hong, T., Liang, H., Yang, Q., Fang, L., Kadoch, M., and Cheriet, M. (2023). A Real-Time Tracking Algorithm for Multi-Target UAV Based on Deep Learning. Remote Sens., 15.
3. Adaptive Transition Probability Matrix-Based Parallel IMM Algorithm;Xie;IEEE Trans. Syst. Man Cybern. Syst.,2021
4. Bao, T., Zhang, Z., and Sabahi, M.F. (2019, January 9–11). An Improved Radar and Infrared Sensor Tracking Fusion Algorithm Based on IMM-UKF. Proceedings of the 16th IEEE International Conference on Networking, Sensing and Control (ICNSC), Banff, AL, Canada.
5. De-correlated unbiased sequential filtering based on best unbiased linear estimation for target tracking in Doppler radar;Peng;J. Syst. Eng. Electron.,2020
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