An Autonomous Ground Based Multi Sensor Data Fused TDR Prediction and Monitoring System
2022-26-1227
05/26/2022
- Event
- Content
- According to a study conducted by IATA, EASA and ICAO, runway excursions are common type of incidents that leads to major accidents. Runway excursion predominantly occur due to incorrect utilization of the touchdown zone (TDZ). A ground-based multi-sensor data fused touchdown region (TDR) prediction and monitoring system is proposed in this paper. This system autonomously analyses real-time environmental data with remote sensing capability around the runway site, gathers real-time information on flight critical parameters of approaching aircraft through an ADS-B Out data link, predicts ideal TDR over the runway TDZ for a particular aircraft, and estimates the expected contemporaneous TDR based on the monitored current approach profile. If the ideal and expected TDR do not overlap, there is a chance for an excursion. In such cases, the flight parameter that needs corrective action is determined and notified to the pilot. In order to analyze dynamic environmental data, mathematical models for sensor fusion techniques for several high performance, reliable and accurate aviation weather sensors/systems such as ceilometer, runway condition sensors, weather radar, thermal and visual cameras will be discussed in this paper. Furthermore, an architectural overview of the ground-based prediction and monitoring system based on a neural network along with a methodology for ADS-B interface is conceptualized.
- Citation
- Nagonda, A., and Manjunath, K., "An Autonomous Ground Based Multi Sensor Data Fused TDR Prediction and Monitoring System," SAE Technical Paper 2022-26-1227, 2022, .