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Research Of CAVS Availability Prediction Theory

Posted on:2021-02-08Degree:MasterType:Thesis
Country:ChinaCandidate:T Y HuangFull Text:PDF
GTID:2392330602970752Subject:Master of Engineering
Abstract/Summary:PDF Full Text Request
Cockpit Traffic Information Display(CDTI)Assisted Visual Interval(CAVS)is a flight operation application based on ADS-B IN surveillance information.During the visual approach phase,CAVS helps pilots maintain visual separation from the Traffic-to-follow(TTF)equipped with ADS-B OUT / IN.CAVS operation is based on the global satellite navigation system,and puts forward strict requirements on its accuracy and integrity.The United States uses ADS-B technology in combination with satellite technology to make ADS-B availability predictions for the implementation of ADS-B operation routes to determine whether ADS-B is available.This article mainly does the following work for CAVS availability prediction.First,this article introduces the basic working principles of GNSS and ADSB,briefly introduces the function and operation mode of CAVS,deeply studies the two important parameters of navigation position accuracy and integrity,and simulates them.Then,analyze and study the correlation between QAR and ADS-B open space data,establish an evaluation method for implementing CAVS operation,and complete the CAVS monitoring application interface simulation.The simulation analysis of the air-to-ground data shows that the data can meet the requirements of CAVS operation,and the deviation analysis of the flight test data in the horizontal,directional and glide paths is carried out.Analyze and compare the minimum operating interval range between TCAS and CAVS.Finally,a collision risk model is established for the operation of CAVS,the collision probability is calculated based on the predicted navigation performance data,and the interval safety of CAVS applications is analyzed and verified based on the predicted data.
Keywords/Search Tags:CDTI Assisted Visual Separation, Automatic Related Surveillance Broadcast, Availability Prediction, Collision Risk Mode
PDF Full Text Request
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