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Multi-acoustic sensor array intelligent sensing method and system

An acoustic sensor and intelligent perception technology, applied in the field of target positioning and recognition, can solve the problems of large tracking errors, achieve the effects of reducing tracking errors, improving recognition accuracy, and eliminating the influence of noise

Pending Publication Date: 2020-09-01
UNIV OF ELECTRONIC SCI & TECH OF CHINA
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0003] First of all, due to the state fusion of each detection node based on Kalman filtering, it can only be applied to the linear observation system, and the system observation noise and process noise are Gaussian white noise, and the tracking error is large

Method used

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Embodiment 1

[0040] Such as image 3 A multi-acoustic sensor array cooperative positioning method is shown, including an acoustic target positioning and identification method, wherein the acoustic target positioning method includes the following steps:

[0041] The acoustic target localization method comprises the following steps:

[0042] According to the conversion relationship between the spatial position of the sound source and the azimuth angle, the azimuth observation model of the target sound source is established,

[0043] Determine the spatial spectrum distribution of the propagation operator algorithm according to the azimuth observation model;

[0044] The spatial spectral distribution of the propagation operator algorithm is applied to the likelihood function of the improved particle filter, and the particle filter method is used to calculate the state estimation value of each microphone array for the acoustic target.

[0045] According to the estimated value of each acoustic...

Embodiment 2

[0103] Based on the principle of the system and method of the above-mentioned embodiment, this embodiment specifically uses 5 linear sound transmission arrays, the number of array elements in each array is M=8, the number of snapshots is 100, the signal-to-noise ratio SNR=5, and five detection nodes The positions are Node1(80,100), Node2(300,90), Node3(380,200), Node4(250,260) and Node5(120,250), the unit is meter. The particle filter adopts period T=1s, particle number N=500, and tracking time is 60s. The sound source target moves uniformly in the two-dimensional plane from the initial position (5, 5) with the speed v=[7.5, 4.5], and the unit is m / s. For the simulation results, see Figure 4 , from the perspective of the tracking effect of the spatial position, the multi-sensor cooperative tracking algorithm based on PF-MUSIC can successfully realize the dynamic tracking of the target in the two-dimensional plane.

Embodiment 3

[0105] Based on the system and method of Embodiment 1, this embodiment specifically uses 3 L-shaped sound transmission arrays, the number of array elements in each array is M=16, the number of snapshots is 100, the signal-to-noise ratio SNR=5, and 3 detection node positions Node1(40,100,0), Node2(80,30,10) and Node3(100,100,20) respectively. The particle filter adopts period T=1s, particle number N=500, and tracking time is 30s. The sound source target moves from the initial position (5, 5, 5) at a speed v = [7.17, 7.17, 4.17], the unit is m / s, and moves uniformly in the three-dimensional plane. For the simulation results, see Figure 5, from the tracking effect of the spatial position, the multi-sensor cooperative tracking algorithm based on PF-MUSIC can successfully realize the dynamic tracking of the target in the three-dimensional plane, and the positioning accuracy is high.

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Abstract

The invention discloses a multi-acoustic sensor array intelligent sensing method and system. An acoustic target positioning method comprises the following steps: establishing an azimuth observation model of a target acoustic source according to a conversion relationship between an acoustic source spatial position and an azimuth angle, and determining spatial spectrum distribution of a propagationoperator algorithm according to the azimuth observation model; applying the spatial spectrum distribution of the propagation operator algorithm to a likelihood function of improved particle filtering, using a particle filtering method to calculate a state estimation value of each microphone array for a sound target, and according to the state estimation values of each sound target, performing fusion according to a scalar weighted linear minimum variance fusion criterion to obtain a motion state of the target. On the basis of a cooperative tracking algorithm of a PF-PM multi-sensor array, two-dimensional angle and three-dimensional space real-time tracking of a sound source can be realized, and the tracking error after fusion is greatly reduced.

Description

technical field [0001] The invention relates to the field of target positioning and recognition, and more specifically relates to a multi-acoustic sensor array intelligent sensing method and system. Background technique [0002] In traditional acoustic detection systems, several microphones are generally fixedly arranged in a certain area, and whether there is a target signal at each observation point is determined according to the relationship between the acoustic signal collected by the microphone and the preset threshold. The existing multi-acoustic sensor data-level positioning algorithm is based on the measurement of the time difference between the arrival of the special parameters of the target echo signal at each detection node and the reference point, and then uses these measurement parameters to solve the positioning equation, combined with Kalman filter fusion to obtain the target motion parameter estimation results Locate the target. There are following defects i...

Claims

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Application Information

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IPC IPC(8): G01S5/22G01S15/66G01S15/86G01C21/16G01S19/39
CPCG01S5/22G01S15/66G01S15/86G01C21/165G01S19/393
Inventor 李学生董飞彪阎迎春江彦桥陈敏徐利梅
Owner UNIV OF ELECTRONIC SCI & TECH OF CHINA
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