The Flight Plan Model Based On Rough Sets And Its Application In The Wireless Target Recognition

There are two important issues in Wireless Target Recognition Systems: the firstone is ‘how to judge two attributes are match or not’, the other one is ‘how to measurethe matching degree’. The solution of these two questions has great positive meaning tothe way of improving the correct recognition probability and distinguishing multipleidentities.Firstly, this article introduces the research and developmental status of the existingTarget Recognition Systems and the Rough Set Theory at home and abroad. After that,the common Cooperative Target Recognition methods are listed in this paper, includingRadar Identification, Special Rules Identification and Flight Plan Identification, etc.With the support of Rough Set Theory and Attribute Relation Theory, the conceptof Generalized Rough Membership was promoted by the author. This concept providesa solution to the issues which were mentioned in the first paragraph.The author founds an algorithm of ‘Rough Flight Plan Identification’ which isbased on the concept of Generalized Rough Membership. Compared with the traditionalFlight Plan Identification, the generalized method has two main areas of improvements:(1) The Generalized Rough Membership is adopted as a tool to measure the match-ing degree between the attribute information and the flight plan information.(2) The information of attributes relation is also used in the algorithm of ‘RoughFlight Plan Identification’.Finally, this article simulates the correct identification probability of both tradition-al and rough flight plan identification under one-to-one recognition; with the conditionthat all targets are cooperative targets. The results of the simulation are listed as follows:(1) With the channel transition probability roughly between1×104~1×103, thecorrect identification probability of Rough Flight Plan Identification improves at least5%than the traditional one.(2) With the channel transition probability roughly between1×103~1×102, thecorrect identification probability of Rough Flight Plan Identification improves at least10%than the traditional one.(3) With the channel transition probability roughly between1×102~1×101, thecorrect identification probability of Rough Flight Plan Identification is still better thanthe traditional one, but the values approach to each other gradually.Besides, the impacts of the main parameters of Rough Flight Plan Identification arealso simulated in this article.