Paper
27 February 2023 Study on the trajectory measurement filter algorithm for an adaptive IMM aerial vehicle
Jian Li, Kewang Zheng, Kun Zhao
Author Affiliations +
Proceedings Volume 12585, International Conference on Precision Instruments and Optical Engineering (PIOE 2022); 125851G (2023) https://doi.org/10.1117/12.2667886
Event: International Conference on Precision Instruments and Optical Engineering (PIOE 2022), 2022, Guangzhou, China
Abstract
A motion state model set for maneuvering target has been established to solve the problem of the increased trajectory measurement error in the maneuvering process of aerial vehicle. The low accuracy of filter caused by the incomplete description of motion state for the single model has been solved by utilizing the interacting multiple model (IMM) algorithm. The adaptive factor has been introduced to the Unscented Kalman Filter (UFK) to resolve the inaccurate observation error prior by adjusting the process noise covariance matrix in real time. The adaptive probability conversion factor based on compression ratio has been added to the IMM algorithm, enhancing its convergence rate. At last, a new AIMM-AUKF trajectory measurement filter algorithm has been formed so that the high accuracy measurement for the trajectory of random maneuvering target has been achieved and the validity the proposed algorithm has been verified through simulation.
© (2023) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Jian Li, Kewang Zheng, and Kun Zhao "Study on the trajectory measurement filter algorithm for an adaptive IMM aerial vehicle", Proc. SPIE 12585, International Conference on Precision Instruments and Optical Engineering (PIOE 2022), 125851G (27 February 2023); https://doi.org/10.1117/12.2667886
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KEYWORDS
Tunable filters

Motion models

Covariance matrices

Detection and tracking algorithms

Electro optical modeling

Covariance

Matrices

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