Vehicle detection method based on linear sound and vibration sensor array

Abstract

The invention provides a vehicle detection method based on a linear sound and vibration sensor array. The method comprises the following steps that 1, a sensor array is distributed and arranged; 2, the short time energy enveloping line of array signals is calculated; 3, the enveloping line of the sensor array signals are subjected to deviation overlapping; 4, interference signals and mistake correlation signals are deleted; 5, the vehicle signal detection and speed detection and the like are carried out. The similarity of the enveloping lines on the sensor array and the relevance between the speed and direction of the vehicle target are utilized, the sound or vibration signals can be singly adopted for carrying out vehicle detection, and the sound and vibration signals can be adopted in a combined way for detection.

Description

technical field [0001] The invention relates to a vehicle detection method, in particular to a vehicle detection method based on vehicle sound or vibration signals. This method can be used in the detection of road moving vehicles in unattended sensor networks, and can quickly detect vehicles moving along the road, and give the speed and direction. Background technique [0002] Sound and vibration signals are a general means of intelligence acquisition on the modern battlefield. They have passive detection, good concealment, high safety factor, can work continuously for a long time, and are not restricted by terrain and lighting conditions. They have the characteristics of all-round and all-weather detection capability. Vehicle target detection based on sound and vibration signals is an important means to grasp the battlefield situation and understand the distribution of enemy and enemy forces. This method also has a wide range of application requirements in anti-terrorism, ...

AI Technical Summary

Problems solved by technology

The detection method based on the difference between signal and noise features is relatively simple, but it is easily disturbed by noise, and the false detection rate is high; while the detection method based on pattern recognition, such as statistical recognition method, function recognition method, logic recognition method, fuzzy recognition method , gray recognition method, neural network recognition method, etc., can not only detect vehicle targets, but also identify vehicle types, but pattern recognition requires a large number of sample event libraries to achieve ideal detection results

Whether it is based on feature difference or pattern recognition, the moving vehicle detection can only detect the vehicle and cannot give the moving speed of the target vehicle.

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