Adaptive Filter Design for UAV Navigation with GPS/INS/Optic Flow Integration

Ding, Weidong; Wang, Jinling; Almagbile, Ali

doi:10.1109/icece.2010.1117

Cited by 18 publications

(8 citation statements)

References 6 publications

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“…Instead of markers, some add active beacon configurations. Rather than simply placing a symbol on the viewed aircraft, a form of light is placed where the MV system can see it broadcasting at specific frequencies and patterns seen in [16,17,44,45]. Ding, Wei, and Wang implemented a beacon-based experiment and achieved accuracies in the mm range within 10 m of the tanker [46].…”

Section: Monocular Visionmentioning

confidence: 99%

Combining Stereo Vision and Inertial Navigation for Automated Aerial Refueling

Johnson

Nykl

Raquet

2017

Journal of Guidance, Control, and Dynamics

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The lack of aerial refueling is a fundamental shortcoming of current Unmanned Aerial Vehicles (UAVs). UAV deployment continues to increase but the corresponding operational capabilities are limited by an inability to conduct extended operations. To alleviate this limitation and achieve the Air Forces global mobility and global strike missions, UAV must procure the capability to perform Automated Aerial Refueling (AAR). Such capability requires computing the precise relative attitude and separation (pose) between the tanker and unmanned receiver. This relative pose is fundamentally required to hold the receiver First, I wish to thank my advisor, Dr. Scott Nykl. His willingness to provide hours of guidance, amidst his own busy schedule, was indispensable. I also wish to thank the members of my committee, Dr.

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Section: Monocular Visionmentioning

confidence: 99%

Combining Stereo Vision and Inertial Navigation for Automated Aerial Refueling

Johnson

Nykl

Raquet

2017

Journal of Guidance, Control, and Dynamics

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“…The performing of these tasks in autonomous flights needs so-called data fusion which is a difficult task especially for small UAVs which are implemented usually at low altitude, and therefore have relatively high level of the barometric altitude sensor errors. There are systematic errors which are inherent in GPS usage at low altitude, and they are also rather important and for this reason special approaches such as robust nonlinear [11], [12] or adaptive [5] filtering are necessary. An alternative to the GPS is the usage of various complementary measurement systems such as optoelectronic cameras and passive radio-or ultrasonic locators which give direction-finding (or bearingonly) observations.…”

Section: Introductionmentioning

confidence: 99%

Tracking of the UAV trajectory on the basis of bearing-only observations

Miller

2014

53rd IEEE Conference on Decision and Control

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This work considers the tracking of the UAV (unmanned aviation vehicle) path on the basis of bearingonly observations including azimuth and elevation angles. The significance of this research becomes clear in the case when GPS either does not work at all or produce the high level of the measurement errors. It is assumed that either UAV's opto-electronic cameras or radar systems are able to capture the angular position of objects with known coordinates and to measure the azimuth and elevation angles of the sight line. Such measurements involve the real position of UAV in implicit form, and therefore some of nonlinear filters such as Extended Kalman filter (EKF) or others may be used in order to implement these measurements for UAV control. However, all such approximate nonlinear filters produce the estimations with unknown bias and quadratic errors. This peculiarity prevents the data fusion in more or less regular way. Meanwhile, there is well-known method of pseudomeasurements which reduces the estimation problem to the linear settings. In this article we develop the modified pseudomeasurement method without bias and with the possibility to evaluate the second moments of the UAV position errors which helps to realize the data fusion. On the basis of this filtering algorithm we develop the control algorithm for tracking of given reference path under external perturbation and noised angular measurements. Modelling examples show the nice performance of the control algorithm.

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“…In these days, there is an effort that optic flow measurements from CCD camera have been used to augment GPS/INS to provide more precise velocity information [2]. GPS/INS which provides speed, position and attitude information, however has errors when GPS is not available or cannot provide exact information when communication system is not robust.…”

Section: Introductionmentioning

confidence: 99%

Mobile Station Position Estimation using Remote Radio Head with Adaptive Power Control

Lee¹,

Kim²,

Lee³

2016

JAEST

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Abstract:The adaptive power control of CDMA (Code Division Multiple Access) communications between multiple MSs (Mobile Stations) with a link-budget based SIR (Signal-to-Interference Ratio) estimate is applied to inner loop power control algorithms. CTR (Consecutive Transmit-Power-Control Ratio) calculated from these algorithms can estimate MS speed, together with MS moving distance, but cannot estimate MS position. In this paper, RRH (Remote Radio Head) is introduced and it is concluded that BS (Base Station) calculates MS distance with CTR from one of RRHs, in addition BS that has RSSIs (Received Signal Strength Indicators) information from other two RRHs can estimate MS position.

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Adaptive Filter Design for UAV Navigation with GPS/INS/Optic Flow Integration

Cited by 18 publications

References 6 publications

Combining Stereo Vision and Inertial Navigation for Automated Aerial Refueling

Combining Stereo Vision and Inertial Navigation for Automated Aerial Refueling

Tracking of the UAV trajectory on the basis of bearing-only observations

Mobile Station Position Estimation using Remote Radio Head with Adaptive Power Control

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