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ROBUST ESTIMATION AND ADAPTIVE GUIDANCE FOR MULTIPLE UAVS' COOPERATION

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Date Issued:
2009
Abstract/Description:
In this paper, an innovative cooperative navigation method is proposed for multiple Unmanned Air Vehicles (UAVs) based on online target position measurements. These noisy position measurement signals are used to estimate the target's velocity for non-maneuvering targets or the target's velocity and acceleration for maneuvering targets. The estimator's tracking capability is physically constrained due to the target's kinematic limitations and therefore is potentially improvable by designing a higher performance estimator. An H-infinity filter is implemented to increase the robustness of the estimation accuracy. The performance of the robust estimator is compared to a Kalman filter and the results illustrate more precise estimation of the target's motion in compensating for surrounding noises and disturbances. Furthermore, an adaptive guidance algorithm, based on the seeker's field-of-view and linear region, is used to deliver the pursuer to the maneuvering target. The initial guidance algorithm utilizes the velocity pursuit guidance law because of its insensitivity to target motion; while the terminal guidance algorithm leverages the acceleration estimates (from the H-infinity filter) to augment the proportional navigation guidance law for increased accuracy in engaging maneuvering targets. The main objective of this work is to develop a robust estimator/tracker and an adaptive guidance algorithm which are directly applicable UAVs.
Title: ROBUST ESTIMATION AND ADAPTIVE GUIDANCE FOR MULTIPLE UAVS' COOPERATION.
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Name(s): Allen, Randal, Author
Xu, Chengying, Committee Chair
University of Central Florida, Degree Grantor
Type of Resource: text
Date Issued: 2009
Publisher: University of Central Florida
Language(s): English
Abstract/Description: In this paper, an innovative cooperative navigation method is proposed for multiple Unmanned Air Vehicles (UAVs) based on online target position measurements. These noisy position measurement signals are used to estimate the target's velocity for non-maneuvering targets or the target's velocity and acceleration for maneuvering targets. The estimator's tracking capability is physically constrained due to the target's kinematic limitations and therefore is potentially improvable by designing a higher performance estimator. An H-infinity filter is implemented to increase the robustness of the estimation accuracy. The performance of the robust estimator is compared to a Kalman filter and the results illustrate more precise estimation of the target's motion in compensating for surrounding noises and disturbances. Furthermore, an adaptive guidance algorithm, based on the seeker's field-of-view and linear region, is used to deliver the pursuer to the maneuvering target. The initial guidance algorithm utilizes the velocity pursuit guidance law because of its insensitivity to target motion; while the terminal guidance algorithm leverages the acceleration estimates (from the H-infinity filter) to augment the proportional navigation guidance law for increased accuracy in engaging maneuvering targets. The main objective of this work is to develop a robust estimator/tracker and an adaptive guidance algorithm which are directly applicable UAVs.
Identifier: CFE0002535 (IID), ucf:47650 (fedora)
Note(s): 2009-05-01
Ph.D.
Engineering and Computer Science, Department of Mechanical Materials and Aerospace Engineering
Doctorate
This record was generated from author submitted information.
Subject(s): H-infinity
Kalman
filtering
estimation
Velocity Pursuit
Augmented Proportional Navigation
guidance
Persistent Link to This Record: http://purl.flvc.org/ucf/fd/CFE0002535
Restrictions on Access: public
Host Institution: UCF

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