Intuitionistic fuzzy association method and device for ADS-B monitoring data and radar tracks

Abstract

An embodiment mode of the invention discloses an intuitionistic fuzzy association method for ADS-B monitoring data and radar tracks. The method comprises the steps of carrying out association pretreatment on the ADS-B monitoring data and radar tracks to obtain a plurality of primary association radar tracks, obtaining fuzzy intuitionistic indexes corresponding to association attributes between the ADS-B monitoring data and the primary radar tracks, obtaining fuzzy decision grades corresponding to the association attributes according to the fuzzy intuitionistic indexes, and carrying out weighing summation on the fuzzy intuitionistic indexes to obtain final associated radar tracks. The associated attributes comprise the distance, the speed, the speed difference and the course angle difference. The embodiment mode of the invention further discloses an intuitionistic fuzzy association device for the ADS-B monitoring data and the radar tracks. By means of the method, the intuitionistic fuzzy association method for the ADS-B monitoring data and the radar tracks can improve association accuracy between the ADS-B monitoring data and the radar tracks and is easy to achieve.

Description

technical field [0001] The invention relates to the field of data association, in particular to an intuitive fuzzy association method and device for ADS-B monitoring data and radar tracks. Background technique [0002] In order to carry out effective, uninterrupted and reliable monitoring of low-altitude flying targets such as airplanes and aviation vehicles, most low-altitude radars and automatic dependent surveillance broadcast (Automatic Dependent Surveillance-Broadcast, ADS-B) equipment are used to conduct stable and reliable monitoring of low-altitude flying targets. monitor. Among them, the correlation between the ADS-B surveillance data and the radar track of the low-altitude radar is the key to realize the effective surveillance of the low-altitude flying target. In the prior art, methods for associating ADS-B surveillance data with radar tracks include: nearest neighbor data association (NN), probabilistic data association (PDA), joint probabilistic data associatio...

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Problems solved by technology

[0003] The inventors of the present application have found in long-term research and development that although the nearest neighbor data association method is simple and easy to implement, when the target data increases or the echoes are dense, the association accuracy rate is low. Although data association methods such as PDA and JPDA can solve the clutter multi-target data association problem in the environment, but the amount of calculation is large, and it is difficult to be directly applied in practice; in addition, the data association method based on fuzzy logic needs to consider a large number of fuzzy rules during the association, and the calculation amount is large, so it is difficult to apply in practice. Practical application; according to the intuitionistic fuzzy theory, there are three relationships between the target and the observation: membership, non-membership and unknown, and the unknown relationship should include the membership information and non-membership information of the target. However, FCM data association and fuzzy comprehensive association methods do not The affiliate information and non-affiliate information of the target contained in the unknown relationship between the ADS-B surveillance data and the radar track are not considered, which makes the association accuracy rate of this fuzzy data association method low

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