Next Article in Journal
Sensing Properties of a Novel Temperature Sensor Based on Field Assisted Thermal Emission
Next Article in Special Issue
Development of an Unmanned Aerial Vehicle-Borne Crop-Growth Monitoring System
Previous Article in Journal
Kriging with Unknown Variance Components for Regional Ionospheric Reconstruction
Previous Article in Special Issue
Unmanned Aerial Vehicle Systems for Remote Estimation of Flooded Areas Based on Complex Image Processing
Article Menu
Issue 3 (March) cover image

Export Article

Open AccessArticle
Sensors 2017, 17(3), 472; doi:10.3390/s17030472

Coordinated Target Tracking via a Hybrid Optimization Approach

1,2,* and 2
1
State Key Laboratory of Virtual Reality Technology and Systems, Beihang University, Beijing 100191, China
2
College of Astronautics, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China
*
Author to whom correspondence should be addressed.
Academic Editors: Felipe Gonzalez Toro and Antonios Tsourdos
Received: 30 December 2016 / Revised: 15 February 2017 / Accepted: 23 February 2017 / Published: 27 February 2017
(This article belongs to the Special Issue UAV-Based Remote Sensing)
View Full-Text   |   Download PDF [3258 KB, uploaded 27 February 2017]   |  

Abstract

Recent advances in computer science and electronics have greatly expanded the capabilities of unmanned aerial vehicles (UAV) in both defense and civil applications, such as moving ground object tracking. Due to the uncertainties of the application environments and objects’ motion, it is difficult to maintain the tracked object always within the sensor coverage area by using a single UAV. Hence, it is necessary to deploy a group of UAVs to improve the robustness of the tracking. This paper investigates the problem of tracking ground moving objects with a group of UAVs using gimbaled sensors under flight dynamic and collision-free constraints. The optimal cooperative tracking path planning problem is solved using an evolutionary optimization technique based on the framework of chemical reaction optimization (CRO). The efficiency of the proposed method was demonstrated through a series of comparative simulations. The results show that the cooperative tracking paths determined by the newly developed method allows for longer sensor coverage time under flight dynamic restrictions and safety conditions. View Full-Text
Keywords: unmanned aerial vehicles; UAV cooperation; persistent tracking; evolutionary algorithm unmanned aerial vehicles; UAV cooperation; persistent tracking; evolutionary algorithm
Figures

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).

Scifeed alert for new publications

Never miss any articles matching your research from any publisher
  • Get alerts for new papers matching your research
  • Find out the new papers from selected authors
  • Updated daily for 49'000+ journals and 6000+ publishers
  • Define your Scifeed now

SciFeed Share & Cite This Article

MDPI and ACS Style

Wang, Y.; Cao, Y. Coordinated Target Tracking via a Hybrid Optimization Approach. Sensors 2017, 17, 472.

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

1

Comments

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