Study On ADS-B Data Evaluation And Application In UAT Mode

Automatic dependent surveillance-broadcast(ADS-B)is a new type of aviation flight technology,which is determined by the international civil aviation organization as the main future navigation surveillance technology.Because ADS-B ground station is affected by the many adverse factors,such as terrain environment and electromagnetic environment and ground station itself performance limit,etc.,so lead to ADS-B monitor performance reach the monitoring requirements we need.But the information provided by ADS-B monitor data and monitoring data message itself some characterization can reflect the effects of these adverse factors.Therefore,it is of great significance to evaluate the monitoring performance by analyzing the data.Conformance monitoring is an important function of air traffic control.Its primary purpose is to monitor the flight path of the aircraft and to detect whether there is any excessive deviation in its flight path.In addition to the excessive deviation of monitoring flight trajectories,there are other monitoring contents and various application scenarios,such as track deviation tracking,etc.This paper based on the ADS-B data information can intuitively reflect the impact of ADS-B operating performance of the bad factors,first of all,the ADS-B data message is received,analyzed and saved.Then according to the relevant indicators,to evaluate the performance of ADS-B monitor,accuracy and integrity and funnelled rate,rate of discrete degree and hops,which focus on using gaussian process to track data modeling,and analysis of the location of the discrete degree and hops rate.Finally,the actual data of Civil Aviation Flight University of China academy are analyzed.Existing various monitoring systems can provide location information,this paper uses the ADS-B system to provide the location of the data as a state measurement values,using gaussian process to establish the model of machine learning,get consistent monitoring model framework,and gives the specific experiments prove the feasibility of the framework.