Simulation And Measurement Data Quality Assessment Of Secondary Surveillance Radar

In the current civil aviation surveillance system,due to numerous advantages of Secondary Surveillance Radar(SSR)such as long detection distance and large acquisition of information,its data has become the primary surveillance data source for Air Traffic Control(ATC).The quality of SSR surveillance data directly affects the quality of surveillance services and the automated operation of the air traffic control system.Assessing the surveillance data quality is of great significance for improving the quality of surveillance services and control services.On the other hand,the rapid development of the civil aviation industry has led to a rapid increase in flight traffic.The huge flight flow puts a higher requirement on the air traffic control system and is also a new challenge for civil aviation safety.In the practice,there are often undesired occasions such as surveillance data loss and target report errors,which is a huge threat to flight safety.In order to ensure the civil aviation safety,it is necessary to have an in-depth exploration of the surveillance data quality.Based on the above background,in order to evaluate the quality of surveillance data,the quality evaluation of secondary radar surveillance data was carried out,which mainly includes the following two parts:1)Track filter algorithm design and simulation.By studying common motion models and filtering methods,the track filtering algorithm of horizontal direction and vertical direction based on Kalman filtering method and ?-? filtering method are designed,and their performance are verified by moving target simulation.2)SSR surveillance data quality evaluation.Based on the quality evaluation indicators proposed by Eurocontrol(European Organization for the Safety of Air Navigation),by establishing the reference track,the quality of the simulation surveillance data and the real surveillance data are respectively evaluated.Evaluation indicators analyzed in the paper include the horizontal position RMS(root mean square)error,track velocity angle RMS error,pressure altitude unsigned error,probability of update of horizontal position,and ratio of missed 3D position involved in long gaps.The statistical results of each indicator are given and are compared to the performance requirements for the horizontal separation interval and the minimum vertical interval service.For the surveillance data quality evaluation,there is still a lack of systematic and comprehensive research.Most of the research is combined with the filtering methods to analyze data accuracy.The data quality indicators studied in this paper have certain value for practical applications.