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

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          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.

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          Most cited references26

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          Vision-based Target Geo-location using a Fixed-wing Miniature Air Vehicle

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            Vision-based real-time target localization for single-antenna GPS-guided UAV

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              Vision-Based Target Geolocation Using Micro Air Vehicles

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                Author and article information

                Contributors
                Role: Academic Editor
                Role: Academic Editor
                Journal
                Sensors (Basel)
                Sensors (Basel)
                sensors
                Sensors (Basel, Switzerland)
                MDPI
                1424-8220
                06 January 2017
                January 2017
                : 17
                : 1
                : 98
                Affiliations
                [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; baigb@ 123456ciomp.ac.cn (G.B.); himyf0319@ 123456126.com (Y.S.); mzyj0617@ 123456126.com (Y.Z.)
                [2 ]University of Chinese Academy of Sciences, #19 Yuquan Road, Beijing 100049, China
                Author notes
                [* ]Correspondence: liu1577@ 123456126.com ; Tel.: +86-177-4301-7276
                Article
                sensors-17-00098
                10.3390/s17010098
                5298671
                28067814
                d271bcbd-aead-46f9-9538-29586c300917
                © 2017 by the authors; licensee MDPI, Basel, Switzerland.

                This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC-BY) license ( http://creativecommons.org/licenses/by/4.0/).

                History
                : 24 October 2016
                : 22 December 2016
                Categories
                Article

                Biomedical engineering
                uav (unmanned aerial vehicles),airborne optoelectronic platform,intersection localization,coordinate transformation,accuracy analysis,adaptive kalman filtering

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