Application of Strong Tracking Cubature Kalman Filter in Air-to-Air Missile Guidance
Year: 2024
Type: article
Abstract: A strong tracking cubature Kalman filter(STCKF) method is proposed to overcome the challenges of insufficient nonlinear approximation capability and decreased tracking accuracy of traditional filtering algorithms in dealing with complex maneuvering targets. Firstly, models for snake maneuver and barrel roll maneuver are developed based on the maneuvering characteristics of fighter aircraft evading air-to-air missiles. Secondly, strong tracking filter(STF) is introduced to enhance the ability of cubature Kalman filter(CKF) to handle sudden changes in system states and other uncertainties. Then, STCKF is applied to estimate the motion parameters of missile terminal guidance target, and its effectiveness is validated through comparative simulation analysis with CKF, unscented Kalman filter(UKF), and particle filter(PF). Simulation results indicate that STCKF has enhanced robustness and adaptive capabilities, especially when the target maneuver suddenly changes, its tracking error is reduced by about 10% compared to CKF, which can meet the high precision and rapid response requirements of air-to-air missile terminal guidance.
Author: Liang Jinxin, Tang Qi, Cui Hao, Zhang Gongping
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W6922425544
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