Moving target recognition method based on acoustic-shock compound sensor

Abstract

The invention relates to a moving target recognition method based on acoustic-shock compound sensor. The moving target recognition method comprises the steps: compounding an acoustic sensor and a shock sensor together into an acoustic-shock compound sensor, simultaneously acquiring an acoustic signal and a shock signal from an environment, judging the level of wind noise in the current environment according to an alarm situation of the acoustic sensor and the shock sensor, performing target recognition by adopting the acoustic signal when the wind noise is low, and performing target recognition by adopting the shock signal when the wind noise is high. According to the moving target recognition method, the target recognition can be performed by selecting different signals according to the noise situation of the environment, a classification failure can not be caused due to large noises, and the low classification rate can not be caused due to difference of geological conditions.

Description

technical field [0001] The invention relates to the technical field of target recognition, in particular to a moving target recognition method based on an acoustic shock composite sensor. Background technique [0002] Detecting and identifying moving targets is one of the important functions of environmental monitoring systems. Target classification and recognition is to classify the target into a pre-delineated type by analyzing and processing the characteristics of the target signal. The usual practice is to find out a feature with the best separability, and then determine a certain judgment rule based on this feature, so that the misrecognition rate caused by classifying the test object according to this rule is the smallest. [0003] The currently used moving target recognition methods mainly include methods based on images, sounds and vibrations. In an ideal environment, the image-based target recognition rate can reach 90%, but its recognition rate is easily affected...

AI Technical Summary

Problems solved by technology

In an ideal environment, the image-based target recognition rate can reach 90%, but its recognition rate is easily affected by the environment and light, and the installation cost and maintenance cost are high, which is not conducive to wide-scale use

The target recognition method based on vibration has a long detection range and low power consumption, but the vibration signal of the target will change with the change of geological conditions. The classification effect will be worse under various geological conditions

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