Method and device for identifying target types

Abstract

The invention discloses a method and a device for identifying target types. The method comprises steps that a sound signal of a target is acquired through a planar sound transmission array, the target includes any one of a low-altitude aircraft, a light aircraft, a power delta wing, a cruise missile and a power paraglider, the direction of the sound signal is evaluated, spatial filtering processing on the sound signal after direction evaluation is carried out, after spatial filtering processing, characteristics of the sound signal, characteristic vectors corresponding to the characteristics of the sound signal and characteristics of the target are extracted, type confidence of the target is determined according to the characteristics of the sound signal, the characteristic vectors of the sound signal and the characteristics of the target, the type confidence is identified through the fusion identification technology, and thereby the type of the target is determined. Through the method, type identification accuracy of the target is improved.

Description

technical field [0001] The invention relates to the technical field of detection, in particular to a method and device for identifying target types. Background technique [0002] Our country has a vast territory, and important defense targets are distributed across the country. They are easily attacked by high-tech aircraft such as armed helicopters, cruise missiles, and unmanned aircraft. It is urgent to establish a low-altitude target detection and early warning system to protect important areas. The low altitude and small radar cross-section make it difficult for general radar to detect, but the sound radiated by these targets during flight is difficult to eliminate. Using these sounds to locate and identify low-altitude flying targets is the two keys of passive sound detection that modern scholars generally pay attention to. technology. [0003] The acoustic signals radiated by different target types are different. By extracting the voiceprint features of different targ...

AI Technical Summary

Problems solved by technology

[0004] However, template matching technology can only be used under specific conditions. Neural network technology requires sufficient sample data, sufficient training for the network, and the convergence of network weight coefficients to the global optimal solution. Otherwise, the neural network is very difficult to use in practice. It is difficult to achieve the expected effect, so it is difficult to achieve the expected effect in actual use of the classification recognition technology in the sampling technology, which affects the accuracy of the recognition result

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