Compensation method of cloud infrared radiation interference based on a spinning projectile’s attitude measurement

Miaomiao Xu; Xiongzhu Bu; Jing Yu; Zilu He

doi:10.1117/1.JRS.12.016031

5 March 2018 Compensation method of cloud infrared radiation interference based on a spinning projectile’s attitude measurement

Miaomiao Xu, Xiongzhu Bu, Jing Yu, Zilu He

Author Affiliations +

Journal of Applied Remote Sensing, Vol. 12, Issue 1, 016031 (March 2018). https://doi.org/10.1117/1.JRS.12.016031

Abstract

Based on the study of earth infrared radiation and further requirement of anticloud interference ability for a spinning projectile’s infrared attitude measurement, a compensation method of cloud infrared radiation interference is proposed. First, the theoretical model of infrared radiation interference is established by analyzing the generation mechanism and interference characteristics of cloud infrared radiation. Then, the influence of cloud infrared radiation on attitude angle is calculated in the following two situations. The first situation is the projectile in cloud, and the maximum of roll angle error can reach ± 20 deg. The second situation is the projectile outside of cloud, and it results in the inability to measure the projectile’s attitude angle. Finally, a multisensor weighted fusion algorithm is proposed based on trust function method to reduce the influence of cloud infrared radiation. The results of semiphysical experiments show that the error of roll angle with a weighted fusion algorithm can be kept within ± 0.5 deg in the presence of cloud infrared radiation interference. This proposed method improves the accuracy of roll angle by nearly four times in attitude measurement and also solves the problem of low accuracy of infrared radiation attitude measurement in navigation and guidance field.

Citation Download Citation

Miaomiao Xu, Xiongzhu Bu, Jing Yu, and Zilu He "Compensation method of cloud infrared radiation interference based on a spinning projectile’s attitude measurement," Journal of Applied Remote Sensing 12(1), 016031 (5 March 2018). https://doi.org/10.1117/1.JRS.12.016031

Received: 26 August 2017; Accepted: 9 February 2018; Published: 5 March 2018

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