Next Article in Journal
Fiber-Optic Fabry-Pérot Interferometers for Axial Force Sensing on the Tip of a Needle
Next Article in Special Issue
Two-UAV Intersection Localization System Based on the Airborne Optoelectronic Platform
Previous Article in Journal
Enhancement of Fluorescence-Based Sandwich Immunoassay Using Multilayered Microplates Modified with Plasma-Polymerized Films
Previous Article in Special Issue
Small UAS-Based Wind Feature Identification System Part 1: Integration and Validation
Article Menu
Issue 1 (January) cover image

Export Article

Open AccessArticle

Real-Time Multi-Target Localization from Unmanned Aerial Vehicles

Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun 130033, China
University of Chinese Academy of Sciences, Beijing 100049, China
Author to whom correspondence should be addressed.
Academic Editors: Felipe Gonzalez Toro and Antonios Tsourdos
Sensors 2017, 17(1), 33;
Received: 3 September 2016 / Revised: 14 December 2016 / Accepted: 19 December 2016 / Published: 25 December 2016
(This article belongs to the Special Issue UAV-Based Remote Sensing)
PDF [9934 KB, uploaded 26 December 2016]


In order to improve the reconnaissance efficiency of unmanned aerial vehicle (UAV) electro-optical stabilized imaging systems, a real-time multi-target localization scheme based on an UAV electro-optical stabilized imaging system is proposed. First, a target location model is studied. Then, the geodetic coordinates of multi-targets are calculated using the homogeneous coordinate transformation. On the basis of this, two methods which can improve the accuracy of the multi-target localization are proposed: (1) the real-time zoom lens distortion correction method; (2) a recursive least squares (RLS) filtering method based on UAV dead reckoning. The multi-target localization error model is established using Monte Carlo theory. In an actual flight, the UAV flight altitude is 1140 m. The multi-target localization results are within the range of allowable error. After we use a lens distortion correction method in a single image, the circular error probability (CEP) of the multi-target localization is reduced by 7%, and 50 targets can be located at the same time. The RLS algorithm can adaptively estimate the location data based on multiple images. Compared with multi-target localization based on a single image, CEP of the multi-target localization using RLS is reduced by 25%. The proposed method can be implemented on a small circuit board to operate in real time. This research is expected to significantly benefit small UAVs which need multi-target geo-location functions. View Full-Text
Keywords: multi-target localization; UAV; real time; lens distortion correction; RLS multi-target localization; UAV; real time; lens distortion correction; RLS

Figure 1

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).
Printed Edition Available!
A printed edition of this Special Issue is available here.

Share & Cite This Article

MDPI and ACS Style

Wang, X.; Liu, J.; Zhou, Q. Real-Time Multi-Target Localization from Unmanned Aerial Vehicles. Sensors 2017, 17, 33.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics



[Return to top]
Sensors EISSN 1424-8220 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top