Multi-sensor multi-feature fusion recognition method for three-dimensional dynamic target recognition

Abstract

The invention discloses a multi-sensor multi-feature fusion recognition method for three-dimensional dynamic target recognition. The method includes the following steps that firstly, two-dimensional planarization is conducted on a recognition target, and a two-dimensional projected image library is established; secondly, images are grayed and binarized, Hu moment features and Zernike moment features are extracted, and an image feature moment information database is established; thirdly, two BP neural networks are respectively trained according to two kinds of image feature moment information; fourthly, target image sequences to be recognized acquired through different sensors are preprocessed, Hu moment features and Zernike moment features are extracted, and the two kinds of feature moment information is input to the two trained BP neural networks respectively, an elementary probability distribution function is acquired through calculation, time domain fusion and space domain fusion are conducted on acquired elementary probability assigned values based on a D-S evidence theory so that recognition result information can be acquired, decision making is conducted on the recognition result information according to a judgment rule, and finally target recognition result information is acquired. According to the multi-sensor multi-feature fusion recognition method, the target recognition correctness probability can be increased.

Description

technical field [0001] The invention relates to information fusion recognition technology of multi-aircraft similar sensors, in particular to a multi-sensor multi-feature multi-level fusion identification method based on the combination of BP neural network and D-S evidence theory, which is suitable for multi-aircraft or multi-platform collaborative aircraft target type identification. Background technique [0002] In modern warfare, information dominance is a key factor affecting the overall strategy, and imaging reconnaissance and target recognition are the main ways to obtain information. Military targets such as military aircraft have very important strategic significance in war and play a very important role. The method of quickly discovering these strategic targets in a large amount of aerial reconnaissance image data and efficiently and quickly identifying the types of military aircraft targets will help combat commanders grasp the enemy's dynamics in real time for de...

AI Technical Summary

Problems solved by technology

[0004] When identifying a three-dimensional target, the target features extracted by a single sensor often cannot obtain a complete description of the target due to its own detection characteristics, and the similar feature information of the target extracted by multiple sensors has limited coverage of the target features. The correct probability of target classification recognition is low

Images