AII aims to infer the most likely future intent based on current aircraft motion states, therefore, it has become an essential method to enhance air traffic situational awareness [1]. Generally, aircraft motion states consist of aircraft IDs, latitude/longitude/altitude coordinates, ground speeds, accelerations and heading angles, which could be directly gained from the surveillance infrastructures like Radars and Automatic Dependent Surveillance-Broadcast (ADS-B) systems. Given current aircraft motion states, one important issue in gaining future air traffic situation prediction is to infer aircraft intent. This is significant because AII plays a fundamental role in conflict detection and avoidance, which hence determines the operational safety of air transportation system.


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    Title :

    Genetic algorithm and support vector machine based aircraft intent inference algorithm in terminal area


    Contributors:
    Yang, Yang (author) / Zhang, Jun (author) / Cao, Xian-bin (author) / Cai, Kai-quan (author)


    Publication date :

    2012-10-01


    Size :

    1223279 byte





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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