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Aerospace 2016, 3(1), 5; doi:10.3390/aerospace3010005

Target Tracking in 3-D Using Estimation Based Nonlinear Control Laws for UAVs

Department of Mechanical and Aerospace Engineering, University of Texas at Arlington, 211 Woolf Hall, Box 19018, 500 W. First St., Arlington, TX 76010, USA
This paper is an extended version of our paper published in IEEE Multi-conference on Systems and Control, Denver, CO, USA, 28–30 September 2011.
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Author to whom correspondence should be addressed.
Academic Editor: David Anderson
Received: 21 December 2015 / Revised: 12 January 2016 / Accepted: 20 January 2016 / Published: 1 February 2016
(This article belongs to the Collection Unmanned Aerial Systems)

Abstract

This paper presents an estimation based backstepping like control law design for an Unmanned Aerial Vehicle (UAV) to track a moving target in 3-D space. A ground-based sensor or an onboard seeker antenna provides range, azimuth angle, and elevation angle measurements to a chaser UAV that implements an extended Kalman filter (EKF) to estimate the full state of the target. A nonlinear controller then utilizes this estimated target state and the chaser’s state to provide speed, flight path, and course/heading angle commands to the chaser UAV. Tracking performance with respect to measurement uncertainty is evaluated for three cases: (1) stationary white noise; (2) stationary colored noise and (3) non-stationary (range correlated) white noise. Furthermore, in an effort to improve tracking performance, the measurement model is made more realistic by taking into consideration range-dependent uncertainties in the measurements, i.e., as the chaser closes in on the target, measurement uncertainties are reduced in the EKF, thus providing the UAV with more accurate control commands. Simulation results for these cases are shown to illustrate target state estimation and trajectory tracking performance. View Full-Text
Keywords: backstepping; control; UAVs; estimation; kalman filter; 3D target tracking backstepping; control; UAVs; estimation; kalman filter; 3D target tracking
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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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MDPI and ACS Style

Ahmed, M.; Subbarao, K. Target Tracking in 3-D Using Estimation Based Nonlinear Control Laws for UAVs. Aerospace 2016, 3, 5.

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