Target location of unmanned aerial vehicles based on the electro-optical stabilization and tracking platform. (December 2019)

• Record Type: Journal Article
• Authors: Xu, Cheng; Huang, Daqing; Liu, Jianye
• Is Part Of: Measurement. Volume 147(2019)
• Publication Date: 2019-12
• Subjects: UAV (unmanned aerial vehicles) -- Target location -- Electro-optical stabilization and tracking platform -- Cubature Kalman Filter; Weights and measures -- Periodicals; Measurement -- Periodicals; Measurement; Weights and measures; Periodicals; 530.8
• DOI: 10.1016/j.measurement.2019.07.076
• Languages: English
• ISSNs: 0263-2241

Abstract

Highlights: Only EOSTP is needed without installing laser rangefinder. A nonlinear 3-D location model with clear physical meaning is established. CKF and CRTS are combined to realize high precision target location of UAV. Approaching DEM by calling the target location solution model repeatedly. Abstract: Target location is a major function of unmanned aerial vehicles (UAV). In aerial photogrammetry, due to the large object distance, various slight measurement errors will be magnified, resulting in a significant decrease in target location precision. In order to improve the precision of target location, an innovative method of UAV target location is designed. This method utilizes the feature of the airborne electro-optical stabilization and tracking platform (EOSTP) which can track a ground target and keep it in the center of the camera's field of view to make multiple observations of one target point. The nonlinear system model of the target space position is built according to the geometric relationship between the line-of-sight (LOS) pointing vector and the target point, and then the Cubature Kalman Filter (CKF) algorithm is used to estimate the target position. Considering that CKF algorithm is easily affected by the initial value errors, the initial target position estimation method based on digital elevation model (DEM) approximation is proposed. The validity of the location algorithm is verified via simulation experiments and the results of actual flight test show that this algorithm can improve the location accuracy of ground target in rough terrain area obviously.