Ballistic Range Correction Algorithm Based on an Improved Unscented Kalman Filter

doi:10.3969/j.issn.1000-1093.2018.09.005

Abstract

Abstract: For the ballistic range correction projectiles utilizing GPS as the projectile-borne detection system, the received dynamic data is susceptible to contamination from measurement noise and system noise, and data loss and exception happen in the high-overload environment. An improved unscented Kalman filter (UKF) based on Newton interpolation method is proposed to reduce the measurement error, thereby decreasing the predicted error during range correction. Data sets with abnormal errors are distinguished and reestimated. The improved UKF algorithm is used to reduce the influence of abnormal measurements and data loss on filtering effect, and more sensitive to measurement error. The improved unscented Kalman filter is designed to be adopted in an ballistic range correction algorithm. The simulated and test results indicate that the preprocessing effect could be maximized if the step size of system discretization is equal to the GPS update interval; the improved correction algorithm is able to reduce the correction errors induced by GPS data. The sample size of GPS data in preprocessing is related to the correction moment and GPS update interval, and it is not restricted by the algorithm effect.Key

Key words: ballisticrangecorrection, preprocessing, unscentedKalmanfilter, rangecorrection, globalpositioningsystem

CLC Number:

TJ413⁺.6

LEI Xiao-yun, ZHANG Zhi-an, DU Zhong-hua. Ballistic Range Correction Algorithm Based on an Improved Unscented Kalman Filter[J]. Acta Armamentarii, 2018, 39(9): 1701-1710.

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第39卷
第9期2018 年9月兵工学报ACTA
ARMAMENTARIIVol.39No.9Sep.2018

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