CN110927668A - Sound source positioning optimization method of cube microphone array based on particle swarm - Google Patents

Sound source positioning optimization method of cube microphone array based on particle swarm Download PDF

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CN110927668A
CN110927668A CN201911145060.1A CN201911145060A CN110927668A CN 110927668 A CN110927668 A CN 110927668A CN 201911145060 A CN201911145060 A CN 201911145060A CN 110927668 A CN110927668 A CN 110927668A
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random
sound source
microphone array
microphone
microphones
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潘正祥
高敏
李建坡
朱淑娟
柴清伟
张庆华
李庚宸
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Shandong University of Science and Technology
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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S5/00—Position-fixing by co-ordinating two or more direction or position line determinations; Position-fixing by co-ordinating two or more distance determinations
    • G01S5/18—Position-fixing by co-ordinating two or more direction or position line determinations; Position-fixing by co-ordinating two or more distance determinations using ultrasonic, sonic, or infrasonic waves
    • G01S5/22—Position of source determined by co-ordinating a plurality of position lines defined by path-difference measurements

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Abstract

The invention discloses a particle swarm-based sound source positioning optimization method for a cube microphone array, and particularly relates to the technical field of computer signal processing. The positioning method comprises the steps of firstly setting the spatial distribution positions of n +1 microphones in a random microphone array, assuming that a sound source coordinate is s (x, y, z), establishing a random microphone array mathematical model according to the coordinate information of the spatial distribution of the random microphones, solving the mathematical model, and solving an estimated time difference tauiSo as to solve the estimated distance difference from the sound source to each array element by estimating the time difference
Figure DDA0002281932590000011
An error equation is established based on the estimated range difference. The invention provides a sound source positioning method for a random microphone array aiming at the problem that the positioning precision of a single microphone technology and a multi-element non-uniform microphone technology to an acoustic environment is not high.

Description

Sound source positioning optimization method of cube microphone array based on particle swarm
Technical Field
The invention relates to the technical field of computer signal processing, in particular to a particle swarm-based sound source positioning optimization method for a cube microphone array.
Background
Based on sound source localization by a microphone array, sound signals are collected by the microphone array, undesired sound source signals and noise are suppressed by using the spatial selection characteristics of the array, and the obtained observation data of the signal source are processed to determine the position of a target sound source. Sound source positioning based on a microphone array has the advantages of flexible beam control, higher spatial resolution, higher signal gain, stronger interference suppression capability and the like, and the microphone array system is widely applied to the fields of audio/video/hands-free communication/conference systems, voice recognition systems, voice control systems, vehicle-mounted telephones, hearing aids and the like.
Due to the complexity of the actual environment, the received signal of the microphone array is inevitably disturbed by noise introduced from the transmission medium, electrical noise inside the communication equipment, room reverberation and even voice of other speakers while acquiring the sound signal, and the speech signal is a broadband signal with a frequency band range of 300-. Compared to the narrowband signal, the wideband signal depends not only on the direction of arrival, but also on the signal frequency due to the phase difference of the array outputs. Therefore, the wideband signal array processing needs to solve the problems of large calculation amount of the algorithm, how to more reasonably utilize the joint sparsity of the wideband signal arrival estimation, and the like. Although the sound source positioning based on the microphone array solves most positioning requirements, the following problems still exist:
(1) positioning accuracy is inaccurate, some positioning deviation exists or some sound source information microphones cannot be accepted completely in the positioning process, and sound source transmission information is not considered fully;
(2) the problem that the sound source cannot be quickly positioned exists, and the position information of the sound source is quite fuzzy;
(3) the considered sound source propagation information is too single, and the condition that the sound source propagates in all directions is not considered.
Disclosure of Invention
The invention aims to solve the defects, and provides a sound source positioning optimization method of a square microphone array based on a particle swarm, which can enable sound source positioning to be more accurate by randomly distributing microphones in the microphone array and placing the microphones in an all-around manner, wherein the microphone array receives signals sent by a sound source when the sound source sends the signals, and the particle swarm optimization algorithm can enable the positioning to be more accurate.
The invention specifically adopts the following technical scheme:
a sound source positioning optimization method of a cube microphone array based on particle swarm,
firstly, the spatial distribution positions of n +1 microphones in the square random microphone array are set as follows:
M0(0,0,0)，M1(D11,D12,D13)，M2(D21,D22,D23)，M3(D31,D32,D33)，…，Mn(Dn1,Dn2,Dn3)，
wherein M is0Is a microphone at the origin, M1,M2,M3,...,MnRandom microphones for coordinates other than the origin, M1,M2,M3,...,MnForm a random microphone array, D11,D12,D13,...,Dn1,Dn2,Dn3The distances from the (n + 1) th microphone to the X axis, the Y axis and the Z axis respectively;
secondly, assuming that the sound source coordinate is s (x, y, z), establishing a random microphone array mathematical model according to the coordinate information of the random microphone spatial distribution:
Figure RE-GDA0002365743650000021
τifor sound sources arriving at random microphone MiI is 0,1,2,3,4,5,6,7, c is the speed of sound in air;
finally, solving a random microphone array mathematical model to obtain an estimated time difference tauiSo as to solve the estimated distance difference from the sound source to each array element by estimating the time difference
Figure RE-GDA0002365743650000022
Establishing an error equation according to the estimated distance difference:
Figure RE-GDA0002365743650000023
where m is the number of random microphone array microphones, i.e. m is n +1, (x)i,yi,zi) And for the random position of the microphone in the microphone array, training by using a particle swarm optimization algorithm by taking an error equation as a target function to determine the sound source position.
The invention has the following beneficial effects:
the method can reduce the error of the microphone array during sound source positioning, provides the random microphone array, can effectively receive signals randomly in all directions, and effectively reduces the sound source positioning error by utilizing a particle swarm optimization algorithm aiming at the problem of low positioning precision of sound source positioning.
Drawings
FIG. 1 is a flow chart of a sound source localization optimization method for a square microphone array based on particle swarm optimization;
FIG. 2 is a perspective view of a random microphone array;
Detailed Description
The following description of the embodiments of the present invention will be made with reference to the accompanying drawings:
as shown in fig. 1 and 2, a sound source localization optimizing method of a square microphone array based on a particle group,
firstly, the spatial distribution positions of n +1 microphones in the square random microphone array are set as follows:
M0(0,0,0)，M1(D11,D12,D13)，M2(D21,D22,D23)，M3(D31,D32,D33)，…，Mn(Dn1,Dn2,Dn3)，
wherein M is0Is a microphone at the origin, M1,M2,M3,...,MnRandom microphones for coordinates other than the origin, M1,M2,M3,...,MnForm a random microphone array, D11,D12,D13,...,Dn1,Dn2,Dn3The distances from the (n + 1) th microphone to the X axis, the Y axis and the Z axis respectively;
secondly, assuming that the sound source coordinate is s (x, y, z), establishing a random microphone array mathematical model according to the coordinate information of the random microphone spatial distribution:
Figure RE-GDA0002365743650000031
τifor sound sources arriving at random microphone MiI is 0,1,2,3,4,5,6,7, c is the speed of sound in air;
finally, solving a random microphone array mathematical model to obtain an estimated time difference tauiSo as to solve the estimated distance difference from the sound source to each array element by estimating the time difference
Figure RE-GDA0002365743650000032
Establishing an error equation according to the estimated distance difference:
Figure RE-GDA0002365743650000033
where m is the number of random microphone array microphones, i.e. m is n +1, (x)i,yi,zi) Is a random wheatAnd (3) taking an error equation as a target function according to the position of the microphone in the microphone array, training by utilizing a particle swarm optimization algorithm, and determining the sound source position.
It is to be understood that the above description is not intended to limit the present invention, and the present invention is not limited to the above examples, and those skilled in the art may make modifications, alterations, additions or substitutions within the spirit and scope of the present invention.

Claims (1)

1. A sound source positioning optimization method of a cube microphone array based on particle swarm is characterized in that,
firstly, the spatial distribution positions of n +1 microphones in the square random microphone array are set as follows:
M0(0,0,0)，M1(D11,D12,D13)，M2(D21,D22,D23)，M3(D31,D32,D33)，…，Mn(Dn1,Dn2,Dn3)，
wherein M is0Is a microphone at the origin, M1,M2,M3,...,MnRandom microphones for coordinates other than the origin, M1,M2,M3,...,MnForm a random microphone array, D11,D12,D13,...,Dn1,Dn2,Dn3The distances from the (n + 1) th microphone to the X axis, the Y axis and the Z axis respectively;
secondly, assuming that the sound source coordinate is s (x, y, z), establishing a random microphone array mathematical model according to the coordinate information of the random microphone spatial distribution:
Figure RE-FDA0002365743640000011
τifor sound sources arriving at random microphone MiI is 0,1,2,3,4,5,6,7, c is the speed of sound in air;
finally, the process is carried out in a batch,solving a random microphone array mathematical model to obtain an estimated time difference tauiSo as to solve the estimated distance difference from the sound source to each array element by estimating the time difference
Figure RE-FDA0002365743640000012
Establishing an error equation according to the estimated distance difference:
Figure RE-FDA0002365743640000013
where m is the number of random microphone array microphones, i.e. m is n +1, (x)i,yi,zi) And for the random position of the microphone in the microphone array, training by using a particle swarm optimization algorithm by taking an error equation as a target function to determine the sound source position.
CN201911145060.1A 2019-11-21 2019-11-21 Sound source positioning optimization method of cube microphone array based on particle swarm Pending CN110927668A (en)

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Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN113593548A (en) * 2021-06-29 2021-11-02 青岛海尔科技有限公司 Awakening method and device of intelligent equipment, storage medium and electronic device
CN114720943A (en) * 2022-06-06 2022-07-08 深圳市景创科技电子股份有限公司 Multi-channel sound source positioning method and system

Citations (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN108168556A (en) * 2018-01-11 2018-06-15 中国矿业大学 Merge particle group optimizing and the driving support frame ultra wide band location method of Taylor series expansions
CN109932689A (en) * 2019-02-24 2019-06-25 华东交通大学 A kind of General Cell optimization method suitable for certain position scene

Patent Citations (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN108168556A (en) * 2018-01-11 2018-06-15 中国矿业大学 Merge particle group optimizing and the driving support frame ultra wide band location method of Taylor series expansions
CN109932689A (en) * 2019-02-24 2019-06-25 华东交通大学 A kind of General Cell optimization method suitable for certain position scene

Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN113593548A (en) * 2021-06-29 2021-11-02 青岛海尔科技有限公司 Awakening method and device of intelligent equipment, storage medium and electronic device
CN113593548B (en) * 2021-06-29 2023-12-19 青岛海尔科技有限公司 Method and device for waking up intelligent equipment, storage medium and electronic device
CN114720943A (en) * 2022-06-06 2022-07-08 深圳市景创科技电子股份有限公司 Multi-channel sound source positioning method and system

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