journal article·2021-03-01Open access

Drag coefficient identification of high-spinning projectile using cubature Kalman filter

Yucheng Zheng, Jun Guan, Wenjun Yi

AIP Advances· Volume 11· Issue 3

Abstract

In order to obtain the aerodynamic parameters of a high-spinning projectile, a new parameter identification method is proposed based on the Cubature Kalman Filter (CKF). First of all, the motion equation of the spinning stabilized projectile is established by the 4D trajectory model. Second, unknown parameters are added to the state vector to obtain the augmented state vector. Next, a new filter is designed for the identification of the unknown parameters based on the basic theory of the CKF. Finally, the simulation results of the CKF are compared with those of the Extended Kalman Filter (EKF) and the Unscented Kalman Filter (UKF). The results of comparison show that the CKF method can effectively identify the aerodynamic parameters and the identification error is less than 1.2%. The CKF method has greater accuracy than the EKF and the UKF.
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Research context

OpenAlex topics: Target Tracking and Data Fusion in Sensor Networks · Guidance and Control Systems · Inertial Sensor and Navigation

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

National Key Laboratory of Transient Physics, Nanjing University of Science and Technology 1 , Nanjing 210094, China

School of Electronics and Information, JiangSu University of Science and Technology 2 , Zhenjiang 212100, China

Funding

National Natural Science Foundation of China · China Postdoctoral Science Foundation

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