Optical Aircraft Positioning for Monitoring of the Integrated Navigation System during Landing Approach

Hecker, P.; Bestmann, U.; Wolkow, S.; Angermann, M.; Dekiert, A.

doi:10.17285/0869-7035.0011

Cited by 3 publications

(7 citation statements)

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“…The first one is the log of real-time on-board calculations made by the SZTAKI sensor during flight tests in Septfonds private airfield (France) with the VISION K50 UAV. The second data set is the imagery and state log of one approach to LOAN 09 runway (Wiener Neustadt/Ost Airport), which was provided by the C2Land Phase B team for comparison of results [ 11 ].…”

Section: Real Flight Resultsmentioning

confidence: 99%

“…Vision-based navigation in general has three main components: sensor type (ultraviolet [ 10 ], infrared [ 11 , 12 ], visible RGB/mono [ 11 , 13 ], stereo [ 14 ]), a priori data (terrain model [ 10 ], satellite images [ 15 ], UAV images [ 16 ], 3D position of key features [ 11 , 13 , 14 ]), and data accumulation (single frame [ 11 , 13 , 14 ] and optic flow/SLAM [ 6 , 16 , 17 , 18 , 19 , 20 ]). Runway relative navigation for autonomous landing is a special case.…”

Section: Introductionmentioning

confidence: 99%

“…Four corner points of the runway (parallel lines with four points) are also enough for 6D pose calculations. Hecker et al [ 11 ] use the Aeronautical Information Publication database to get 3D runway corner points, and this model is projected to camera image using global orientation derived from IMU and estimated position of the camera. The projection is fine-tuned in a region of interest (ROI) based on line contour features.…”

Section: Introductionmentioning

confidence: 99%

“…IR has the advantage of weather independence, however, it has lower resolution, higher price, and lack of texture details. IR is beneficial for all-weather complete runway detection from longer distances, while RGB can provide detailed information about threshold marker and center line at the end of the approach and during landing and taxiing [ 11 ]. Line features are straight edges which can be detected with horizontal/vertical Sobel filters, which are separable 2D filters thus they can be applied to the whole image at low computation cost.…”

Section: Introductionmentioning

confidence: 99%

“…The results of different FOV sensors are compared. Beyond the own flight test results, the image processing method is also tested on the real flight data which was provided by the C2Land project [ 11 ]. The paper summarizes the main concepts for navigation data extraction from image features of a runway ( Section 2 ), presents the image processing method for threshold marker detection ( Section 3 ), introduces the experimental platform and the monocular image sensor hardware ( Section 4 ) and finally discusses the raw image-based navigation results ( Section 5 ).…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Optical Navigation Sensor for Runway Relative Positioning of Aircraft during Final Approach

Hiba

Gáti

Manecy

2021

Sensors

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Precise navigation is often performed by sensor fusion of different sensors. Among these sensors, optical sensors use image features to obtain the position and attitude of the camera. Runway relative navigation during final approach is a special case where robust and continuous detection of the runway is required. This paper presents a robust threshold marker detection method for monocular cameras and introduces an on-board real-time implementation with flight test results. Results with narrow and wide field-of-view optics are compared. The image processing approach is also evaluated on image data captured by a different on-board system. The pure optical approach of this paper increases sensor redundancy because it does not require input from an inertial sensor as most of the robust runway detectors.

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Section: Real Flight Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Optical Navigation Sensor for Runway Relative Positioning of Aircraft during Final Approach

Hiba

Gáti

Manecy

2021

Sensors

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The accuracy of determining the coordinates of an unmanned aerial vehicle with a navigation complex integrating an electro-optical positioning system

Sheinikov

Коваленко

Sanko

2023

Naučn. vestn. MGTU GA

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The article proposes the approaches to updating a strapdown inertial navigation system (SINS) based on data of the airborne electro-optical system (EOS) of an unmanned aerial vehicle (UAV). It is specified that the EOS is presented as a navigation data sensor. The rationale for the feasibility of such an approach is formed, especially in the terms of signal lack or suppression of satellite radio-navigation systems. It is proposed to ensure the accuracy of self-contained navigation by assigning an UAV route, including waypoints with terrestrial references (TRs). Notably, TR-associated image information is preliminarily downloaded into the flight management computer (FMC). The automated TR identification system with denoted coordinates at next waypoints, using airborne data, in fact, allows for alternative global positioning. The reliable operation of such an integrated navigation system over sufficiently extended legs of flight path, first, depends on the accuracy of its constituent elements. Taking into consideration the fact that conventional sensors of navigation information, such as a SINS and an altimeter, are quite well studied in numerous contributions. The article focuses on the UAV airborne electro-optical system and, specifically, on its application features as a navigation sensor. The factors influencing the accuracy of the UAV positioning data determination at waypoints according to the data of the airborne EOS are considered. The developed mathematical model of errors for the UAV inertial optical navigation complex (IONC) is presented. The analysis of the impact of airborne altimeter inaccuracies, earth’s surface features and the shift of the onboard digital camera optical axis, caused by random evolutions of the carrier body in turbulent atmosphere on the positioning accuracy, was conducted. The results of calculating lapses in determining the UAV positioning data, equipped with IONC, are given.

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Real-Time Monocular Vision System for UAV Autonomous Landing in Outdoor Low-Illumination Environments

Lin

Jin

Chen

2021

Sensors

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Landing an unmanned aerial vehicle (UAV) autonomously and safely is a challenging task. Although the existing approaches have resolved the problem of precise landing by identifying a specific landing marker using the UAV’s onboard vision system, the vast majority of these works are conducted in either daytime or well-illuminated laboratory environments. In contrast, very few researchers have investigated the possibility of landing in low-illumination conditions by employing various active light sources to lighten the markers. In this paper, a novel vision system design is proposed to tackle UAV landing in outdoor extreme low-illumination environments without the need to apply an active light source to the marker. We use a model-based enhancement scheme to improve the quality and brightness of the onboard captured images, then present a hierarchical-based method consisting of a decision tree with an associated light-weight convolutional neural network (CNN) for coarse-to-fine landing marker localization, where the key information of the marker is extracted and reserved for post-processing, such as pose estimation and landing control. Extensive evaluations have been conducted to demonstrate the robustness, accuracy, and real-time performance of the proposed vision system. Field experiments across a variety of outdoor nighttime scenarios with an average luminance of 5 lx at the marker locations have proven the feasibility and practicability of the system.

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Optical Aircraft Positioning for Monitoring of the Integrated Navigation System during Landing Approach

Cited by 3 publications

References 0 publications

Optical Navigation Sensor for Runway Relative Positioning of Aircraft during Final Approach

Optical Navigation Sensor for Runway Relative Positioning of Aircraft during Final Approach

The accuracy of determining the coordinates of an unmanned aerial vehicle with a navigation complex integrating an electro-optical positioning system

Real-Time Monocular Vision System for UAV Autonomous Landing in Outdoor Low-Illumination Environments

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