This paper presents work undertaken into the development of an automated air-based vision system for assessing
the performance of an approach lighting system (ALS) installation in accordance with International Civil Aviation
Organisation (ICAO) standards. The measuring device consists of an image sensor with associated lens system
fitted to the interior of an aircraft. The vision system is capable of capturing sequences of airport lighting images
during a normal approach to the airport. These images are then processed to determine the uniformity of the
To assess the uniformity of the ALS the luminaires must first be uniquely identified and tracked through an
image sequence. A model-based matching technique is utilised which uses a camera projection system to match
a set of template data to the extracted image data. From the matching results the associated position and pose
of the camera is estimated.
Each luminaire emits an intensity which is dependant on its angular displacement from the camera. As
such, it is possible to predict the intensity that each luminaire within the ALS emits during an approach.
Luminaires emitting the same intensity are banded together for the uniformity analysis. Uniformity assumes
that luminaires in close proximity exhibit similar luminous intensity characteristics. During a typical approach
grouping information is obtained for the various sectors of luminaires. This grouping information is used to
compare luminaires against one another in terms of their extracted grey level information. The developed
software is validated using data acquired during an actual approach to a UK airport.
This paper presents a novel measurement system that assesses the uniformity of a complete airport lighting installation. The system improves safety with regard to aircraft landing procedures by ensuring airport lighting is properly maintained and conforms to current standards and recommendations laid down by the International Civil Aviation Organisation. The measuring device consists of a CMOS vision sensor with associated lens system fitted to the interior of an aircraft. The vision system is capable of capturing sequences of airport lighting images during a normal approach to an aerodrome. These images are then post processed to determine the uniformity of the complete pattern. Airport lighting consists of elevated approach and inset runway luminaires. Each luminaire emits an intensity which
is dependant on the angular displacement from the luminaire. For example, during a normal approach a given luminaire will emit its maximum intensity down to its minimum intensity as the aircraft approaches and finally passes over the luminaire. As such, it is possible to predict the intensity that each luminaire within the airport lighting pattern emits, at a given time, during a normal approach. Any luminaires emitting the same intensity can then be banded together for the uniformity analysis. Having derived the theoretical groups of similar luminaires within a standard approach, this information was applied to a sequence of airport lighting images that were recorded during an approach to Belfast International Airport. Since we are looking to determine the uniformity of the pattern, only the total pixel grey level representing each luminaire within each banded group needs to be extracted and tracked through the entire image sequence. Any luminaires which fail to meet the requirements (i.e. a threshold value depending on the performance of the other luminaires in that band) are monitored and reported to the assessor for attention. The extraction and tracking algorithms have been optimised for minimal human intervention. Techniques such as component analysis as well as centre of mass algorithms are used to detect and locate the luminaires. A search algorithm is used to obtain the brightness (total grey level) of each luminaire. For the sample test at Belfast International Airport several luminaires were found that do not output sufficient intensity. As a final conclusion however, the Belfast International lighting pattern is legal and conforms to standards as no two consecutive luminaires fail in the pattern. The techniques used in this paper are novel. No known research exists that couples uniformity of airport lighting with photometrics. A solid basis has been established for future work on monitoring the individual characteristics of the luminaires. This includes colour and intensity measurements.
The International Civil Aviation Organization (ICAO) is the regulatory body for Airports. ICAO standards dictate that luminaires used within an airport landing lighting pattern must have a color as defined within the 1931 color chart defined by the Commission Internationale De L'Eclairage (CIE). Currently, visual checks are used to ensure luminaires are operating at the right color within the pattern. That is, during an approach to an airport the pilot must
visually check each luminaire within the landing pattern. These visual tests are combined with on the spot meter reading tests. This method is not accurate and it is impossible to assess the color of every luminaire. This paper presents a novel, automated method for assessing the color of luminaires using low cost single chip CCD
video camera technology. Images taken from a camera placed within an aircraft cockpit during a normal approach to an airport are post-processed to determine the color of each luminaire in the pattern. In essence, the pixel coverage and total RGB level for each luminaire within the pattern must be extracted and tracked throughout the complete image sequence and an average RGB value used to predict the luminaire color. This prediction is based on a novel pixel model which was derived to determine the minimum pixel coverage required to accurately predict the color of an imaged luminaire. Analysis of how many pixels are required for color recognition and position within a CIE color chart is given and proved empirically. From the analysis it is found that, a minimum diameter of four pixels is required for color recognition of the major luminaires types within the airport landing pattern. The number of pixels required for classification of the color is then derived. This is important as the luminaries are far away when imaged and may cover only a few pixels since a large area must be viewed by the camera. The classification is then verified by laboratory based experiments with different luminaire sources. This paper shows that it is possible to accurately predict the color of luminaires using automated image analysis. Whilst this is not a new phenomenon the authors have shown that it is possible to simulate the operation of a single chip CCD imager and illustrate the minimum pixel coverage that is required to accurately represent a colored luminaire from a moving platform. In addition, the color assessment of airport landing lighting has not yet been tackled using photometrics and dynamic cameras. The principles outlined are generic and can therefore be applied to other areas of lighting research such as signal and street lighting. Future color work with respect to airport lighting will concentrate on more complex models for the luminaire movement across a mosaic filter. A current assumption used in this paper is that there are no gaps between the pixel patches, which is not the case. As such an update on the model will incorporate inter-pixel gaps.