Intention recognition based on Hidden Markov Model for aerial target

Huimin Chai; Yong Zhang; Yanan Song

doi:10.1117/12.2631555

1 May 2022 Intention recognition based on Hidden Markov Model for aerial target

Huimin Chai, Yong Zhang, Yanan Song

Proceedings Volume 12171, Thirteenth International Conference on Signal Processing Systems (ICSPS 2021); 1217110 (2022) https://doi.org/10.1117/12.2631555
Event: Thirteenth International Conference on Signal Processing Systems (ICSPS 2021), 2021, Shanghai, China

Abstract

The method of intention recognition based on HMM for aerial target is provided in the paper. The three HMMs are constructed in order to recognize the attack intention, evasion intention and escape intention respectively. The “left-right” structure is chosen to establish the HMMs. The target sensor data: target speed、approach angle and distance from enemy target to our side , is utilized as the observation sequence of the HMMs. Here, the discretization results of target sensor data are the input to the HMMs. The accuracy of target intention recognition is over 80.0% in simulation experiments, which show that the method is available and effective.

Citation Download Citation

Huimin Chai, Yong Zhang, and Yanan Song "Intention recognition based on Hidden Markov Model for aerial target", Proc. SPIE 12171, Thirteenth International Conference on Signal Processing Systems (ICSPS 2021), 1217110 (1 May 2022); https://doi.org/10.1117/12.2631555

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