A Survey of Techniques for Detection and Tracking of Airport Runways

Gong, Xiaojin; Abbott, Lynn; Fleming, Gary A.

doi:10.2514/6.2006-1436

Cited by 13 publications

(6 citation statements)

References 20 publications

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“…Some of these techniques include adaptive control [23,24,25], fuzzy control [23,26], neural networks, genetic algorithms and Lyapunov Theory [28]. Visual Servoing is a technique using the feedback information extracted from visual sensors in order to control a robot or UAV.…”

Section: Controller Designmentioning

confidence: 99%

Design and integration of vision based sensors for unmanned aerial vehicles navigation and guidance

Sabatini

Bartel

Kaharkar

et al. 2012

Optical Sensing and Detection II

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In this paper we present a novel Navigation and Guidance System (NGS) for Unmanned Aerial Vehicles (UAVs) based on Vision Based Navigation (VBN) and other avionics sensors. The main objective of our research is to design a lowcost and low-weight/volume NGS capable of providing the required level of performance in all flight phases of modern small-to medium-size UAVs, with a special focus on automated precision approach and landing, where VBN techniques can be fully exploited in a multisensory integrated architecture. Various existing techniques for VBN are compared and the Appearance-based Navigation (ABN) approach is selected for implementation. Feature extraction and optical flow techniques are employed to estimate flight parameters such as roll angle, pitch angle, deviation from the runway and body rates. Additionally, we address the possible synergies between VBN, Global Navigation Satellite System (GNSS) and MEMS-IMU (Micro-Electromechanical System Inertial Measurement Unit) sensors and also the use of Aircraft Dynamics Models (ADMs) to provide additional information suitable to compensate for the shortcomings of VBN sensors in high-dynamics attitude determination tasks. An Extended Kalman Filter (EKF) is developed to fuse the information provided by the different sensors and to provide estimates of position, velocity and attitude of the platform in real-time. Two different integrated navigation system architectures are implemented. The first uses VBN at 20 Hz and GPS at 1 Hz to augment the MEMS-IMU running at 100 Hz. The second mode also includes the ADM (computations performed at 100 Hz) to provide augmentation of the attitude channel. Simulation of these two modes is performed in a significant portion of the Aerosonde UAV operational flight envelope and performing a variety of representative manoeuvres (i.e., straight climb, level turning, turning descent and climb, straight descent, etc.). Simulation of the first integrated navigation system architecture (VBN/GPS/IMU) shows that the integrated system can reach position, velocity and attitude accuracies compatible with CAT-II precision approach requirements. Simulation of the second system architecture (VBN/GPS/IMU/ADM) shows promising results since the achieved attitude accuracy is higher using the ADM/VBS/IMU than using VBS/IMU only. However, due to rapid divergence of the ADM virtual sensor, there is a need for a frequent re-initialisation of the ADM data module, which is strongly dependent on the UAV flight dynamics and the specific manoeuvring transitions performed. Finally, the output provided by the VBN and integrated navigation sensor systems is used to design a flight control system using a hybrid Fuzzy Logic and Proportional-Integral-Derivative (PID) controller for the Aerosonde UAV.

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Section: Controller Designmentioning

confidence: 99%

Design and integration of vision based sensors for unmanned aerial vehicles navigation and guidance

Sabatini

Bartel

Kaharkar

et al. 2012

Optical Sensing and Detection II

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show abstract

“…Then two approaches can be used for attitude determination, one is a variant of the classical method [16] that allows the determination of the attitude states by considering one single pair of vectors (e.g., Â and Ŝ 1 , Ŝ 1 and Ŝ 2 ).In order to select the optimal pair of vectors, the errors associated to such combination are considered (the pair with the minimum RMS/RSS error is selected. The recursive algorithm method, uses all available information from 3 nonaligned antennae and 3 satellites (Â, Ŝ 1 , Ŝ 2 , Ŝ 3 ,), to obtain an estimation of the attitude of the vehicle by minimizing the following cost function:…”

Section: A P S Q S R S a S A S A Smentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Carrier-phase GNSS Attitude Determination and Control for Small Unmanned Aerial Vehicle Applications

Sabatini

Kaharkar²,

Bartel³

et al. 2013

J Aeronaut Aerospace Eng

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As part of our recent research to assess the potential of low-cost navigation sensors for Unmanned Aerial Vehicle (UAV) applications, we investigated the potential of carrier-phase Global Navigation Satellite System (GNSS) for attitude determination and control of small size UAVs. Recursive optimal estimation algorithms were developed for combining multiple attitude measurements obtained from different observation points (i.e., antenna locations), and their efficiencies were tested in various dynamic conditions. The proposed algorithms converged rapidly and produced the required output even during high dynamics manoeuvres. Results of theoretical performance analysis and simulation activities are presented in this paper, with emphasis on the advantages of the GNSS interferometric approach in UAV applications (i.e., low cost, high data-rate, low volume/weight, low signal processing requirements, etc.). The simulation activities focussed on the AEROSONDE UAV platform and considered the possible augmentation provided by interferometric GNSS techniques to a low-cost and low-weight/volume integrated navigation system (presented in the first part of this series) which employed a Vision-Based Navigation (VBN) system, a MicroElectro-Mechanical Sensor (MEMS) based Inertial Measurement Unit (IMU) and code-range GNSS (i.e., GPS and GALILEO) for position and velocity computations. The integrated VBN-IMU-GNSS (VIG) system was augmented using the inteferometric GNSS Attitude Determination (GAD)sensor data and a comparison of the performance achieved with the VIG and VIG/GAD integrated Navigation and Guidance Systems (NGS) is presented in this paper. Finally, the data provided by these NGS are used to optimise the design of a hybrid controller employing Fuzzy Logic and Proportional-Integral-Derivative (PID) techniques for the AEROSONDE UAV.

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“…Various controller schemes have also been applied in the past to the design of autonomous control/servoing systems for UAVs. Some of these techniques include Adaptive Control [4,11,30], Fuzzy Control [21,30], Neural Networks, Genetic Algorithms and Lyapunov Theory [29]. Beyond studying the possible synergies attainable from integration of GAD systems with other low-cost and low-weight/volume navigation sensors (e.g., VBN and MEMS-INS), and additional objective of our research is to develop an hybrid Fuzzy/PID controller using INS, GNSS and GAD input data and also capable of VBN guidance (visual servoing) during the final approach and landing phases of the flight.…”

Section: Introductionmentioning

confidence: 99%

Low-Cost Navigation and Guidance Systems for Unmanned Aerial Vehicles — Part 2: Attitude Determination and Control

Sabatini¹,

Rodríguez²,

Kaharkar³

et al. 2013

Annual of Navigation

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This paper presents the second part of the research activity performed by Cranfield University to assess the potential of low-cost navigation sensors for Unmanned Aerial Vehicles (UAVs). This part focuses on carrier-phase Global Navigation Satellite Systems (GNSS) for attitude determination and control of small to medium size UAVs. Recursive optimal estimation algorithms were developed for combining multiple attitude measurements obtained from different observation points (i.e., antenna locations), and their efficiencies were tested in various dynamic conditions. The proposed algorithms converged rapidly and produced the required output even during high dynamics manoeuvres. Results of theoretical performance analysis and simulation activities are presented in this paper, with emphasis on the advantages of the GNSS interferometric approach in UAV applications (i.e., low cost, high data-rate, low volume/weight, low signal processing requirements, etc.). The simulation activities focussed on the AEROSONDE UAV platform and considered the possible augmentation provided by interferometric GNSS techniques to a low-cost and low-weight/volume integrated navigation system (presented in the first part of this series) which employed a Vision-Based Navigation (VBN) system, a Micro-Electro-Mechanical Sensor (MEMS) based Inertial Measurement Unit (IMU) and code-range GNSS (i.e., GPS and GALILEO) for position and velocity computations. The integrated VBN-IMU-GNSS (VIG) system was augmented using the inteferometric GNSS Attitude Determination (GAD) sensor data and a comparison of the performance achieved with the VIG and VIG/GAD integrated Navigation and Guidance Systems (NGS) is presented in this paper. Finally, the data provided by these NGS are used to optimise the design of a hybrid controller employing Fuzzy Logic and Proportional-Integral-Derivative (PID) techniques for the AEROSONDE UAV.

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A Survey of Techniques for Detection and Tracking of Airport Runways

Cited by 13 publications

References 20 publications

Design and integration of vision based sensors for unmanned aerial vehicles navigation and guidance

Design and integration of vision based sensors for unmanned aerial vehicles navigation and guidance

Carrier-phase GNSS Attitude Determination and Control for Small Unmanned Aerial Vehicle Applications

Low-Cost Navigation and Guidance Systems for Unmanned Aerial Vehicles — Part 2: Attitude Determination and Control

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