基于HMM的低空目标航迹威胁识别

doi:10.12305/j.issn.1001-506X.2023.05.16

Abstract

Abstract:

Robust low-altitude target threat identification is an important task of low-altitude security protection. The traditional multi-attribute decision-making (MADM) method requires high measurement accuracy of target motion parameters, neglects the temporal correlation information of target motion, and lacks noise robustness and dynamic analysis ability in practical applications. Therefore, the hidden Markov model is introduced on the basis of the MADM method, and a dynamic and robust method for low-altitude target threat level identification is proposed. By establishing the internal relationship between hidden state, threat level and threat value, the problem of threat identification is transformed into the problem of state decoding of the hidden Markov model. Compared with conventional algorithms, the proposed method can effectively suppress measurement noise interference and has certain threat prediction ability. Simulation experiments verify the effectiveness and robustness of the proposed method.

Key words: low-altitude target, threat identification, multi-attribute decision-making (MADM), hidden Markov model (HMM), dynamic identification

CLC Number:

TN959.1+7

Xiaojie YU, Song WEI, Jialian SHENG, Lei ZHANG. Threat identification for low-altitude target track based on HMM[J]. Systems Engineering and Electronics, 2023, 45(5): 1399-1408.

Figures/Tables 12

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Threat identification for low-altitude target track based on HMM

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