Lag track correlative fusion method, system and application based on random distance

Abstract

The present invention belongs to the technical field of radars or similar systems special for application, and discloses a lag track correlative fusion method, system and application based on a randomdistance. The concrete flows of the method comprise: inputting a first-class reference track and multiple other-class tracks; selecting windows with sizes of n; calculating the lag correlation; finding a track set meeting the correlation threshold value; performing verification of the random distance for the track correlation in the set; determining the correlative track and performing track fusion; and calculating the incidence relation between the tracks with lag correlation, ranking the incidence relation, finding the track with the maximum incidence relation and taking the track with themaximum incidence relation as an correlative track, and employing a least square method to start fusion from the track lag moment. The lag track correlative fusion method, system and application basedon the random distance are high in classification precision and low in operation time complexity, can effectively solve the fusion problem of lag and interrupted tracks in the track correlation fusion, can improve the track correlation correction and effectively improve the integration of target feature portrayal description through fusion.

Description

technical field [0001] The invention belongs to the technical field of radar or similar systems suitable for specific applications, and in particular relates to a method, system and application of lagging track correlation fusion based on random distance. Background technique [0002] At present, the existing technology commonly used in the industry is as follows: the fusion between different types of tracks is a relatively new technology with high practicability. It is generally believed that when performing track fusion, the fused data should have the same data attributes, that is, the same type of data can be fused. The track fusion of air targets generally adopts multi-sensor data association technology, and Kalman filtering is used to achieve track smoothing. Algorithms for track fusion generally include simple convex combination track fusion method, weighted fusion estimation method and adaptive digital filtering method. However, these methods deal with the track inf...

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Problems solved by technology

[0003] To sum up, the problems existing in the existing technology are: the existing methods for solving the lag correlation of time data flow have the problems of low data dimension and small number of attributes, and do not consider the situation of multiple attributes corresponding to each moment , the application in multi-dimensional spatial data track lag correlation calculation has certain limitations; in the face of the fusion problem of lag track, the data corresponding to each moment may be multi-dimensional, and this method solves the two-dimensional sequence data The lag correlation between them cannot solve the problem of lag correlation calculation of three-dimensional or multi-dimensional data.

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