308 results about "Sound source location" patented technology

The invention discloses a building sound wave reflection path analysis and noise source positioning method and system, and the method comprises the steps: S1, arranging a plurality of sound sensors according to the geometric structure of a target building, collecting sound signals, carrying out the signal sampling of the sound signals, and storing the sound signals in the form of a time sequence; s2, preprocessing the sound signal, extracting a time difference matrix, a frequency spectrum feature and an energy feature, merging into a three-dimensional time sequence feature, and normalizing to form a three-dimensional time sequence feature matrix; s3, establishing an LSTM network, and predicting a three-dimensional position and a sound wave reflection path of an output noise source; s4, optimizing and calculating a sound wave reflection path by using the geometric structure data of the target building, and generating a three-dimensional reflection path diagram; and S5, dynamically displaying a noise source position and a sound wave reflection path according to the three-dimensional reflection path diagram. According to the invention, high-precision three-dimensional positioning of a noise source can be realized in a complex building environment, accurate modeling is realized, and propagation and reflection paths of sound waves in a building are analyzed.

The invention relates to the technical field of arc fault diagnosis, and provides an energy storage system arc fault diagnosis method and system based on voiceprint detection, and the method comprises the following steps: collecting a voiceprint signal in real time, and carrying out the anti-interference preprocessing, and obtaining a time-frequency domain spectrogram; identifying the time-frequency domain spectrogram based on a multi-branch convolutional neural network and weighting the time-frequency domain spectrogram to obtain a time sequence feature sequence; inputting the time sequence feature sequence into a time sequence convolutional network model, and outputting global context features; performing dynamic weighted pooling on the global context features to obtain key frame feature vectors representing the arc fault; and inputting the key frame feature vector into an arc fault diagnosis classification model to obtain an arc fault type, an arc fault severity grade and sound source positioning information, and generating a corresponding alarm signal and a control instruction based on the arc fault severity grade. According to the invention, the detection sensitivity and the anti-interference capability are improved, and the safety protection level and the fault early warning capability of the energy storage system are improved.

The invention relates to the field of gas leakage identification, and discloses a gas leakage identification method and system based on sound localization, a medium and equipment, and the method comprises the steps: collecting a leakage sound wave signal through a microphone array, and extracting acoustic features in a complex background; simulating a diffusion process of gas in a turbulence environment after gas leakage through an established leakage gas convection-diffusion model, and combining gas concentration distribution in the simulated diffusion process with acoustic characteristics to predict sound source localization at a leakage position; modeling a sound source localization search process as POMDP, and iteratively updating a confidence state of a sound source position through a particle filter; spatial distribution features are extracted from the confidence state through DBSCAN clustering to serve as input of the LSTM-DQN network, spatial and temporal features are fused through the constructed LSTM-DQN network, cross-scene generalization is achieved through transfer learning, and sound source coordinates are dynamically optimized and output through the Q network. According to the invention, the positioning accuracy and real-time performance in a complex environment are improved.

The invention belongs to the technical field of sound source processing, and provides a sound source positioning and detecting method and device. The method comprises the following steps: acquiring delay estimation of microphones I and II and delay estimation of microphones I and III based on a three-path linear uniform microphone array; based on the delay estimation sum, respectively carrying out positioning calculation under near-field and far-field conditions; according to the sound source distance under the near-field condition, comparing the sound source distance with a distance judgment threshold value, and determining a far-field / near-field output sound source position; and carrying out feature extraction on the signals of any microphone array, and carrying out event classification based on a pre-trained convolutional neural network. According to the method, far / near field model selection is carried out according to the distance judgment threshold, large deviation generated by a single model in a critical region is avoided, continuous and stable positioning from short distance to long distance is achieved, time classification can be achieved while position calculation is carried out, and integrated output is achieved.

The invention relates to the technical field of data processing, in particular to a three-dimensional live-action model construction system for building structure demolition and reconstruction. The system extracts event combinations with obvious transfer correlation features for localization and analysis of dangerous sound sources. Through simulation of transmission of test waves in an initial acoustic slowness field, a most probable dangerous sound source position for generating a current event combination under each test wave is obtained by using an objective function optimization solution method. And further performing statistics on simulation information of all test waves, establishing a residual curve, screening out a brittleness event position based on feature extraction, and adjusting a slowness value in a current voxel through various parameters corresponding to the brittleness event position in an initial acoustic slowness field. Through the dynamic correction method, the obtained corrected acoustic slowness field can more effectively represent the specific change of the building structure in the dismantling process, so that the internal damage can be more clearly quantified.

The invention discloses a conference sound reinforcement system based on an AI intelligent algorithm and 360-degree omni-directional noise reduction, and relates to the technical field of audio signal processing, the conference sound reinforcement system comprises a conference management center, the conference management center is in communication connection with the following modules: a multi-sound-source sensing module used for capturing 360-degree omni-directional sound field information in a conference environment and constructing a sound source space distribution model; according to the invention, the omnidirectional microphone array unit covers all directions of a conference space, synchronously collects audio data streams, eliminates the limitation of a conventional unidirectional microphone, combines the sound source positioning space mapping unit, constructs a sound source space distribution model based on the time difference of arrival and the phase difference through a deep learning model, and improves the sound source positioning accuracy. The azimuth angle, pitch angle and distance parameters of the sound source are accurately analyzed, the position of the sound source is mapped to a virtual space coordinate system, a dynamically updated 3D sound source distribution diagram is generated, the position change and intensity distribution of the sound source are reflected in real time, and the positioning precision in a complex acoustic environment is remarkably improved.

The invention discloses an indoor multi-sound-source positioning method based on DOA estimation and DOA association, and the method comprises the steps: judging single-source time-frequency points through the correlation of time delay inequality vectors of adjacent time-frequency points between microphones, and constructing a variable-size elastic single-source region; applying the FSSZ distribution condition of the sound source in a reference array to all arrays by using the high correlation characteristic of the FSSZ time-frequency distribution of the same sound source at different microphone arrays in a frame; performing middle DOA estimation on the FSSZs of all the arrays in the whole observation time period by using a circular integral cross spectrum method, and constructing a sound source position histogram in combination with FSSZ aggregation degree weighting; 2D positions of the plurality of sound sources are estimated from the sound source position histogram using 2D-CFAR. According to the invention, under the conditions of indoor reverberation and noise, position estimation can be carried out on a plurality of sound sources with an unknown number, the detection performance under the conditions of positioning precision and missed detection is obviously superior to that of an existing method, and the defects of the prior art are overcome.

The present invention discloses a cross-sound zone sound source localization method using dual hydrophones in a deep-sea environment, comprising: step 1: using the dual hydrophones to receive broadband signals radiated by a sound source in a specified sea area, and simultaneously using other hydroacoustic equipment to obtain environmental parameters of the sea area; step 2: using a time-spectral energy accumulation method to extract the arrival times of different sound lines from the received signal of one of the hydrophones, and estimating two multipath time delay differences; step 3: using a sound field calculation model BELLHOP to simulate two multipath time delay differences in different sound zones when the sound source is at different grid virtual points; step 4: calculating a cost function, and estimating the position of a target sound source; step 5: repeating steps 2 and 4 for the signal received by another hydrophone, and estimating the position of the target sound source; and step 6: performing a similarity analysis on four estimation results obtained by positioning the two hydrophones, and taking the average of the two estimation results with the greatest similarity as the final sound source position estimation result.

The invention provides a method and device for carrying out noise detection on a train, which can be applied to the field of railway and urban rail transit, and the method comprises the following steps: determining the initial noise reverberation duration and the sound source position of noise; iteratively executing the following operations to obtain the dynamic reverberation duration: determining the nth reverberation duration according to the sum of the (n-1) th noise reverberation duration and the preset duration; processing the nth noise reverberation duration and the reference reverberation duration according to tunnel shape parameters for the pipe tunnel to obtain an nth room coefficient; processing the nth room coefficient by using a target noise detection model corresponding to the sound source position to obtain an nth sound pressure level increment value of the noise; under the condition that a difference value between the Nth sound pressure level increment value and a preset standard sound pressure level increment value meets a preset convergence condition, determining the Nth noise reverberation duration as a dynamic reverberation duration; and processing the reference reverberation duration and the dynamic reverberation duration according to a reverberation noise prediction algorithm to obtain a noise value of the noise.

The invention belongs to the technical field of computer hearing, and discloses an audiovisual binaural sound source localization method based on a pulse neural network. Constructing an audio-visual sound source positioning network; frequency domain features and time domain features of the binaural audio signals are extracted through the frequency domain feature extraction module and the time domain feature extraction module respectively; spatial geometric features of the depth image are extracted through a spatial cue extraction module; the multi-source feature adaptive fusion module effectively fuses the frequency domain features, the time domain features and the spatial geometric features; the positioning module predicts the azimuth angle and the distance of the sound source based on the fusion features; and sound source prediction training is carried out by using the data in the front and back directions, and the trained audio-visual sound source positioning network is used for audio-visual binaural sound source positioning. The method improves the precision and robustness of sound source localization in a complex scene, and opens up a new path for the application of the multi-modal fusion technology in sound source localization. The difference between the front and rear sound sources is explicitly learned, so that the model learns a more complex nonlinear relationship between audio-visual characteristics and sound source positions.

The invention discloses a fan fault detection and positioning method and system based on a microphone array, and the method comprises the steps: obtaining a sound signal, and carrying out the first preprocessing of the sound signal, and obtaining a first sound signal; obtaining the position of a fault sound source by calculating the time difference of the first sound signals received by the microphones; optimizing the position of the fault sound source by using a first optimization method to obtain a position coordinate of the fault sound source; classifying fault types based on the fault sound source position coordinates to obtain a classification result; acquiring real-time monitoring data, and performing modeling in combination with the classification result to obtain a first neural network model; according to the method, historical operation data and historical fault information are acquired, the first neural network model is trained, the trained first neural network model is verified, a parameter prediction value is output, the parameter prediction value is judged, a fault result is obtained, and the deployment and extension cost is reduced through modular design and software and hardware optimization.

The invention discloses a method and system for ensuring smooth communication in a large private car, and relates to the technical field of vehicle-mounted central control. Comprising the steps of collecting audio data in a vehicle and extracting reference sound data of central control equipment; performing denoising processing on the audio data to generate communication voice data; separating the alternating current voice data according to the significant sound source; calculating an output sound pressure level of each loudspeaker according to a microphone position corresponding to the separated alternating current voice data, and performing voice gain compensation; accurate selection of communication voice data among passengers is realized by removing reference voice data in the audio data; accurate matching between passenger sound and seats is realized through accurate extraction of a significant sound source, and the position of the sound source is updated in real time; through the cooperation of the output sound pressure level and the voice gain compensation, the audio output is optimized, echoes caused by sound amplification of a loudspeaker are avoided, and the communication experience of passengers is improved.

The invention provides a livestock and poultry abnormal sound recognition and positioning method and system, and relates to the technical field of livestock and poultry breeding monitoring, and the method comprises the steps: extracting the sound characteristics of a livestock and poultry sound signal, carrying out the abnormal audio recognition according to the characteristic pattern of the sound characteristics, and obtaining the sound type of the sound signal; when the sound category is abnormal audio, calculating a generalized cross-correlation delay inequality to determine a sound source position range of the sound signal; and calling a particle swarm optimization algorithm to search the generalized cross-correlation delay inequality to obtain a distance value of an optimal sound source position of the sound signal, calling an SRP-PHAT algorithm to search to obtain a sound source position space point of the sound signal in a sound source position range, and finally determining a three-dimensional position coordinate when the livestock and poultry make a sound. Through the method and the device, the defects that livestock abnormal audio recognition is easily interfered by factors such as external environment noise and the like in the prior art, and the sound source positioning precision is limited in a multi-sound-source scene are overcome.

The invention relates to an equipment health optimal monitoring point selection method and system, and relates to the field of equipment monitoring, and the method comprises the steps: collecting sound signals of monitoring points around monitored equipment; determining a signal spectrum and a signal attenuation based on the sound signal; determining a sound source position according to the signal spectrum and the signal attenuation; calculating a signal-to-noise ratio based on the signal spectrum, matching and determining a noise reduction level, and weighting according to the noise reduction level and the sound source position to obtain a comprehensive score; calculating a comprehensive score in combination with the sound source position and the noise reduction level; according to the monitoring points and the sound signals, calculating a fluctuation ratio, and screening out a position with the fluctuation ratio smaller than a stable threshold value and higher than a score threshold value in the comprehensive score as a secondary monitoring point; determining the position distribution of secondary monitoring points according to the sound source position and the equipment structure; and selecting a point location with the maximum coverage degree from the position distribution, and determining the point location with the highest coincidence degree as the optimal point location based on matching of the signal spectrum and the fault spectrum. The application has the effects of improving the monitoring effect and realizing high-precision monitoring.

The invention discloses a multi-voice separation method based on a lightweight dual-path Transform network, and the method comprises the steps: collecting audio multi-voice data, and carrying out the preprocessing of the data, and forming a data set; the method comprises the following steps: constructing a dual-path Transform network model DPTNet, and introducing a recurrent neural network to optimize the dual-path Transform network model DPTNet; and training the dual-path network model DPTNet, and performing engineering deployment based on the trained model. The method is beneficial to obtaining higher-quality audio fingerprint recognition capability, sound source separation capability and voice enhancement function, can be used for tracking and positioning the position of a sound source, helps positioning and tracking related applications, can be expanded to the medical field, can be used for heart sound segmentation, namely, recognition of specific signals of the heart, and can be applied to the field of medical science. The method helps to diagnose cardiovascular and other medical problems, and has technical innovation and practical application value.

The invention provides a sparse Bayesian learning-based matched broadband modal phase velocity inversion earth sound parameter method and system, and the method comprises the steps: extracting a local mode through employing a receiving signal of a vertical array, and removing the narrowband limitation of block sparse Bayesian; the broadband modal phase velocity is used for matching inversion of the earth sound parameters, and decoupling of the earth sound parameters is achieved. The method has the advantages that seabed parameters do not need to be known priori, the depth range of the extraction mode is not limited by the aperture of the VLA, and the method can be applied to a non-uniform vertical array; when the earth sound parameters are inversed, the earth sound parameters are not influenced by the terrain on the propagation path, and the earth sound parameters of any terrain can be inversed; known sound source position information is not needed, and the problem of inaccurate inversion result caused by inaccurate sound source position is avoided; and meanwhile, multi-distance sound source signals are used for inversion, so that the inversion of the earth sound parameters is more robust and accurate.

The invention discloses an intelligent security inspection method based on multi-element fusion, and the method comprises the steps: collecting sound data in an environment through employing a microphone array, and calculating the position of a sound source based on the time difference, intensity difference and phase difference of the sound data; constructing a sound feature recognition model, and recognizing the type of a sounding subject in the sound source position and emotion deviation of a part of types of subjects; according to the identified emotional deviation of the person, analyzing the vocal meaning corresponding to the subject type by adopting an ASR technology, and judging whether the vocal meaning corresponds to risk feature information or not; based on the sound production meaning containing risk characteristic information, optical identification, gas component analysis, equipment pose, a point cloud map and wind direction meteorological comprehensive research and judgment analysis are combined, risk judgment output is carried out through a cloud edge collaborative algorithm, matched alarm information is output and played, and meanwhile lamplight flickering is carried out. The dangerous case is comprehensively researched and judged, and the risk identification accuracy and the dangerous case disposal efficiency are improved.

The invention discloses an active clearance control method and system for a wind turbine generator, and relates to the field of clearance control, and the method comprises the steps: obtaining a sound source signal, wind speed data and rotating speed data of fan blades, and determining the position of a sound source based on the sound source signal; determining a clearance distance based on the sound source position; when the wind speed data and the rotating speed data of the fan blades are both larger than a set threshold value, and the clearance distance is smaller than or equal to a set early warning threshold value, control parameters are optimized through an improved tribe competition and member cooperation algorithm, and the optimized control parameters are obtained; and variable pitch operation control is conducted based on the optimized control parameters, so that active control over the clearance distance is achieved. According to the method, the problem of lack of a corresponding effective active safety control strategy can be solved, and meanwhile, the problems of high cost, low precision, poor environmental adaptability, non-real-time performance and the like of a current wind turbine generator clearance detection mode are solved.

The invention relates to a digital conference voice processing method, system and device and a storage medium, and the method comprises the following steps: carrying out the pickup of a conference voice, obtaining a mixed voice signal, carrying out the framing sampling, and forming a voice sampling sequence; carrying out sound source direction estimation based on the sequence to obtain multi-sound-source position information, and carrying out beam forming and spatial filtering on the voice sampling sequence according to the multi-sound-source position information to obtain a sound source separation signal; performing voice segment segmentation on the signal to obtain a voice segment sequence, extracting voiceprint features of each segment, and generating a speaker feature mark; and performing time sequence recombination on the voice fragment sequence by using the mark, constructing a speaking time sequence table, selectively outputting the voice fragment sequence according to the table, and finally generating clear and ordered conference voice. The technical problems that due to the fact that a traditional voice processing method lacks effective space-voiceprint joint constraint, voice separation is not thorough, identities of speakers are confused, and the speaking time sequence is disordered are solved.

The invention discloses a sound source localization method based on a transmembrane attention mechanism, and the method comprises the steps: S1, collecting an audio signal, calculating the logarithmic Mel spectrum of the audio signal, and generating an MFCC audio feature; s2, receiving a video signal, and extracting frame-level video features of the video signal by using a convolutional neural network; s3, encoding the audio features and the video features, aligning modal features of the audio and the video through a contrast learning layer, optimizing modal sharing information and generating modal alignment features; s4, calculating a cross-modal attention weight: dynamically capturing the relevance between the audio features and the video features by using a cross-modal attention mechanism; and S5, screening candidate proposal regions with high confidence through the relevance between the audio features and the video features, weighting the candidate proposal regions, calculating the similarity between each candidate proposal region and the audio features, generating weighted region features, and outputting the sound source position and range. According to the invention, audio and video features can be fused in a transmembrane state, and sound source localization is accurately realized.

A display device may detect an ambient sound from audio data captured by a plurality of microphones on a display device. A display device may determine, based on the audio data, a location of a sound source of the ambient sound. A display device may generate contextual information about the ambient sound based on an audio segment of the audio data that includes the ambient sound. A display device may display the contextual information based on the location of the sound source.

The invention discloses a sound source localization method and device based on an improved generalized cross-correlation algorithm and a medium, and belongs to the field of sound source localization, and the method comprises the steps: collecting a sound source signal through a quaternary cross sensor array; constructing an improved weighting function according to the sound source signal; wherein the improved weighting function is obtained by weighted summation of a phase transformation weighting function and a maximum likelihood weighting function; performing generalized cross-correlation operation according to the sound source signal and the improved weighting function to obtain time delay; and performing geometric operation in the three-dimensional rectangular coordinate system based on the time delay to obtain a sound source position. Therefore, the accuracy and robustness of sound source localization can be improved in a low signal-to-noise ratio environment and a strong reverberation environment by implementing the method and the device.

The invention relates to the field of microphone sound reception, in particular to a precise sound reception system and method based on double microphone arrays and 3D visual identification, and the system comprises a sound source positioning module, a visual identification module, an audio processing module, a sound reception control module and a precise tracking module. The visual identification module is used for calculating the listening angle of the microphone array, the audio processing module is used for obtaining the sound arrival time difference of each microphone, the sound reception control module is used for outputting the position of a target sound source, and the precise tracking module is used for enabling the camera to track the target sound source. The method is advantaged in that requirements of real-time interaction scenes are satisfied, sound reception capability of the microphone array in complex scenes is improved, good robustness and accuracy are realized, sound source positioning precision and dynamic tracking capability are improved, and environment adaptability and real-time performance of microphone sound reception are improved.

The invention discloses a multi-modal speech enhancement method and device based on a deep learning model, and relates to the technical field of artificial intelligence, and the method comprises the steps: obtaining the head posture data, binaural audio signals and visual context information of a user in a virtual reality environment, coding the binaural audio signals into three-dimensional space acoustic features, and carrying out the coding of the three-dimensional space acoustic features; and extracting virtual sound source position features and lip motion features from the visual context information, inputting the features into an immersive fusion enhancement network, selectively enhancing or inhibiting acoustic features from different spatial directions, generating an enhanced audio stream, and outputting the enhanced audio stream through a binaural rendering engine. According to the method, the technical problems that in the prior art, due to the fact that multi-modal prior information cannot be effectively fused, voice enhancement lacks spatial selectivity, and an interference sound source irrelevant to vision is difficult to restrain are solved, and head posture dynamic attention and lip motion cross-modal constraint are fused; the technical effects of natural binding of auditory attention and a visual focus and effective suppression of an interference sound source are achieved.

The embodiment of the invention discloses an information processing method and device, electronic equipment and a computer readable storage medium, and relates to the technical field of augmented reality. The method comprises the following steps: separating single-person voices corresponding to a plurality of sound source positions from mixed voices; determining character features of a plurality of characters under the plurality of spatial positions; determining a first association relationship between the single-person voice and the character features and a second association relationship between the translated text and the character features; when the scene backtracking function is started, playing the stored mixed voice and scene image; when the sight line of the wearer focuses on the played virtual character, obtaining a target first association relationship and a target second association relationship corresponding to the playing moment, and further obtaining a target single-person voice and a target translation text of the virtual character at the playing moment; and playing the voice of the target single person, and displaying the target translated text space at the position of the virtual character. Therefore, according to the scheme, the user can obtain more effective information through scene backtracking.

The invention discloses a method and a device for generating a binaural spatial audio with multiple sound sources according to a text. The method comprises the following steps of: inputting a description type text or a parameter type text of the audio; preprocessing the description type text or the parameter type text by adopting a big language model to generate structural information including sound events, sound duration, sound source position information and time sequence information; generating a plurality of single-channel audios corresponding to sound events and sound durations in the input text by using a diffusion model; adopting a binaural rendering model to render all the single-channel audios into binaural audios conforming to the sound source position information in the input text; and synthesizing each binaural audio obtained by rendering into a target binaural audio according to the time sequence information of each sound source in the input text. According to the method, the reasonable sound source orientation can be given according to the physical law when the sound source position is missing, and the accuracy of converting the text into the binaural space audio is greatly improved.

The invention relates to a multi-source intelligent combined pose measurement method for a floating hydrophone array, and the method comprises the following steps: 1, obtaining the pose information of each node of the hydrophone array through a multi-source sensing module, and synchronously receiving sound signals and extracting the TDOA information of each node under the condition that the sound source position is known; step 2, constructing a measurement equation based on TDOA information, and performing inverse solution on the position of each node of the hydrophone array in combination with a hyperbolic positioning principle and a sound velocity model; according to the method, an inverse solution positioning mode of'known sound source position and inverse solution of receiving array node position 'is adopted, a flexible underwater acoustic array dynamic measurement scene under the traction of a floating platform is specially aimed at, the technical limitation that traditional TDOA and USBL positioning depends on a fixed geometric structure is broken through, the method does not need to arrange a plurality of reference receiver arrays, and the positioning accuracy is improved. And a high-precision synchronous clock system is not needed, and high-precision acoustic positioning can be realized only by depending on a single sound source and the distributed nodes, so that the system complexity and the field deployment cost are remarkably reduced.

A sound source positioning device based on multi-microphone and time difference algorithm, the device comprises a sound signal acquisition module, a signal processing module, a positioning and communication module, a display module and a power module; the sound signal acquisition module adopts multiple output analog signal microphones to realize omnidirectional acquisition of sound signals; the signal processing module takes a single-chip microcomputer as the core and integrates analog signal amplification, filtering, peak detection, analog-to-digital conversion and time difference algorithm processing functions; the positioning and communication module combines a Beidou positioning module and a mobile communication module to realize sound source position determination and remote data transmission; the power module stably supplies power to each module in multiple gears. The present application combines multi-microphone cooperative acquisition with the time difference algorithm to improve the accuracy and stability of local single-point sound source positioning and can be applied to security monitoring, environmental monitoring, industrial inspection and other scenes.

The invention provides a sound wave propagation spatial distribution and sound source position control method, and relates to the technical field of loudspeaker control, and the method comprises the steps: building an analysis control model based on a sound source and a propagation auxiliary object; constructing a first area of sound wave propagation of the sound source in the analysis control model, and marking a second area of spatial distribution of sound wave propagation of the current sound source; mapping the target position to an analysis control model to generate a mapping point location; when the mapping point is in the second area or the mapping point is not in any first area, the sound source position is not controlled; and when the mapping point location is not in the second area but is in any first area, determining a target sound source in the first area, and determining a sound source position control parameter based on the control library correspondingly associated with the target sound source and the mapping point location. According to the sound wave propagation spatial distribution and sound source position control method, sound delivery is carried out according to the position of a film viewer, and the viewing experience of the film viewer is guaranteed.

The application discloses a near-field strong interference suppression method based on spherical wave deconvolution beam forming positioning, which comprises the following steps: performing fine grid division on a near-field scanning area of a linear array; performing spherical wave focusing beam forming on the near-field scanning area and two-dimensional deconvolution beam forming about distance-angle under the condition of unknown sound source position; calculating the distribution entropy characteristics of the deconvolution beam forming result in the angle dimension, and using a preset threshold to correlate the interference positioning of a target; constructing an array flow pattern matrix A of each near-field target l and generating a covariance matrix A; calculating the orthogonal complement space projection matrix of the covariance matrix A, and applying the orthogonal complement space projection matrix to the array element domain covariance matrix C to perform near-field interference suppression; using a far-field plane wave model to perform deconvolution beam forming calculation on the covariance matrix for suppressing near-field interference, so as to obtain passive detection results of the near-field strong interference suppression. The application can realize near-field interference positioning and interference suppression under the condition that the interference position is unknown.