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Sensors 2017, 17(1), 98; doi:10.3390/s17010098

Two-UAV Intersection Localization System Based on the Airborne Optoelectronic Platform

1
Chinese Academy of Science, Changchun Institute of Optics Fine Mechanics and Physics, Key Laboratory of Airborne Optical Imaging and Measurement, #3888 Dongnanhu Road, Changchun 130033, China
2
University of Chinese Academy of Sciences, #19 Yuquan Road, Beijing 100049, China
*
Author to whom correspondence should be addressed.
Academic Editors: Felipe Gonzalez Toro and Antonios Tsourdos
Received: 24 October 2016 / Revised: 15 December 2016 / Accepted: 22 December 2016 / Published: 6 January 2017
(This article belongs to the Special Issue UAV-Based Remote Sensing)
View Full-Text   |   Download PDF [5127 KB, uploaded 6 January 2017]   |  

Abstract

To address the limitation of the existing UAV (unmanned aerial vehicles) photoelectric localization method used for moving objects, this paper proposes an improved two-UAV intersection localization system based on airborne optoelectronic platforms by using the crossed-angle localization method of photoelectric theodolites for reference. This paper introduces the makeup and operating principle of intersection localization system, creates auxiliary coordinate systems, transforms the LOS (line of sight, from the UAV to the target) vectors into homogeneous coordinates, and establishes a two-UAV intersection localization model. In this paper, the influence of the positional relationship between UAVs and the target on localization accuracy has been studied in detail to obtain an ideal measuring position and the optimal localization position where the optimal intersection angle is 72.6318°. The result shows that, given the optimal position, the localization root mean square error (RMS) will be 25.0235 m when the target is 5 km away from UAV baselines. Finally, the influence of modified adaptive Kalman filtering on localization results is analyzed, and an appropriate filtering model is established to reduce the localization RMS error to 15.7983 m. Finally, An outfield experiment was carried out and obtained the optimal results: σ B = 1.63 × 10 4 ( ° ) , σ L = 1.35 × 10 4 ( ° ) , σ H = 15.8 ( m ) , σ s u m = 27.6 ( m ) , where σ B represents the longitude error, σ L represents the latitude error, σ H represents the altitude error, and σ s u m represents the error radius. View Full-Text
Keywords: UAV (unmanned aerial vehicles); airborne optoelectronic platform; intersection localization; coordinate transformation; accuracy analysis; adaptive Kalman filtering UAV (unmanned aerial vehicles); airborne optoelectronic platform; intersection localization; coordinate transformation; accuracy analysis; adaptive Kalman filtering
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Bai, G.; Liu, J.; Song, Y.; Zuo, Y. Two-UAV Intersection Localization System Based on the Airborne Optoelectronic Platform. Sensors 2017, 17, 98.

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