# UAV-Based Airport Lights Inspection Without GNSS Positioning Support
## 2 Related Works  
The inspection of visual aids in the case of lights requires measurements of the parameters of illumination in the space of the airport. Flight inspection systems are dominating these assignments. UNIFIS 3000-G2: Misson System developed by Norwegian Special Mission AS (NSM) represents an example of a modular system that can be installed on different aircraft: Beechcraft, Bombardier, Cessna, Embraer, Piaggio. The system includes NAVAID's flight inspection tools configured by the user for desired inspections tasks [8]. The Polish Air Navigation Services Agency (PANSA) caries out inspections of air traffic aids and the validation of instrument flight procedures in Poland. The agency carries out periodic, ad hoc, and category inspections and measurements of airport infrastructure: NAVAID's navigation light systems, approach light systems (ALSs), runway light systems, and PAPIs [9]. Aerodata developed the AeroFIS flight inspection system with in-house aircraft integration capability. AeroFIS can be coupled to the flight director/autopilot of an aircraft for automated flight inspection procedures; this reduces the flight time for completing inspections [10]. Radiola's aerospace flight inspection systems have the capability to down-link real-time data. A portable computer serves as the data recording system providing fast data acquisition and analysis. The solution is advantageous when complex commissioning tasks are performed [11]. Modular and portable CARNAC Automatic Flight Inspection Systems can be installed temporarily on aircrafts that can carry out other missions: medical evacuation, training, television, environmental monitoring, etc. The systems are fully automatic [12]. The solutions use multi-constellation multi-frequency GNSS position reference systems with the capability of utilizing satellite-based correction data services for determining the geodetic positions of aircrafts during flight inspection missions. UAVs have recently begun to establish a position as a viable alternative to manned flight inspection systems. The authors in [13] reviewed the potential of UAVs and concluded that developments in this area can effectively supplement or replace conventional inspections. UAVs can also improve the accuracy and consistency of inspections. They can capture high-resolution images of aviation infrastructure, which can be analyzed to detect defects and anomalies. Analysis can be performed using state-of-the-art image processing methods or using new algorithms based on emerging AI approaches. UAVs can provide access to hard-to-reach areas of aviation infrastructure. The introduction of these systems finds regulatory and operational challenges that limit the full automation of the inspection process [14]. Inspection services, using UAVs, for airport lights are provided by a number of companies and successfully compete with traditional flight inspection systems. Canard Drones developed a solution for PAPI calibration that uses differential GNSS positioning. The operation is performed in a few minutes and can be carried out during day- or nighttime [15]. Drone Flight Inspection (DeFI) outputs a graph of the colour transition of PAPI units, obtaining insight into the functional condition of the units [16]. Colibrex prepared a versatile UAV platform with exchangeable payloads for ILS, VOR, and PAPI [17]. The authors in [18] discussed the problems of preparing software for processing video data collected during UAV flights for determining PAPI light parameters. The principle of operation of these systems is based on registering the images of lights during UAV flights and processing the collected data. The extraction of lights--image objects--must be immune to ambient light changes and explicitly localize the lights on the image. In order to evaluate the space parameters of light illumination, such as the direction of illumination and angles of visibility, precise knowledge of the camera position during the recording is required.