Ground target geolocation based on digital elevation model for airborne wide-area reconnaissance system

Chuan Qiao; Yalin Ding; Yongsen Xu; Jihong Xiu

doi:10.1117/1.JRS.12.016004

4 January 2018 Ground target geolocation based on digital elevation model for airborne wide-area reconnaissance system

Chuan Qiao, Yalin Ding, Yongsen Xu, Jihong Xiu

Author Affiliations +

Journal of Applied Remote Sensing, Vol. 12, Issue 1, 016004 (January 2018). https://doi.org/10.1117/1.JRS.12.016004

Abstract

To obtain the geographical position of the ground target accurately, a geolocation algorithm based on the digital elevation model (DEM) is developed for an airborne wide-area reconnaissance system. According to the platform position and attitude information measured by the airborne position and orientation system and the gimbal angles information from the encoder, the line-of-sight pointing vector in the Earth-centered Earth-fixed coordinate frame is solved by the homogeneous coordinate transformation. The target longitude and latitude can be solved with the elliptical Earth model and the global DEM. The influences of the systematic error and measurement error on ground target geolocation calculation accuracy are analyzed by the Monte Carlo method. The simulation results show that this algorithm can improve the geolocation accuracy of ground target in rough terrain area obviously. The geolocation accuracy of moving ground target can be improved by moving average filtering (MAF). The validity of the geolocation algorithm is verified by the flight test in which the plane flies at a geodetic height of 15,000 m and the outer gimbal angle is <47°. The geolocation root mean square error of the target trajectory is <45 and <7 m after MAF.

Citation Download Citation

Chuan Qiao, Yalin Ding, Yongsen Xu, and Jihong Xiu "Ground target geolocation based on digital elevation model for airborne wide-area reconnaissance system," Journal of Applied Remote Sensing 12(1), 016004 (4 January 2018). https://doi.org/10.1117/1.JRS.12.016004

Received: 11 July 2017; Accepted: 12 December 2017; Published: 4 January 2018

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