138 results about "Beamforming algorithm" patented technology

The invention discloses an intelligent metasurface channel optimization method and system based on a beam forming algorithm, and relates to the technical field of intelligent metasurfaces, and the method comprises the steps: collecting real-time environment data, monitoring channel state data, and evaluating the influence of the environment and the channel state on a signal; evaluating the gain strategy of the intelligent metasurface, and evaluating the performance of the current beam forming strategy by combining the influence of the environment and the channel state on the signal; and calculating an optimal beam forming parameter by using a gradient descent method to realize channel optimization. According to the method, through comprehensive utilization of real-time environment monitoring, channel state evaluation, an advanced data analysis technology and a mathematical optimization method, dynamic adjustment and real-time optimization of intelligent metasurface channel optimization are achieved, efficient and stable operation of a communication system in a complex environment is ensured, the speed and reliability of data transmission are remarkably improved, and the method is suitable for popularization and application. The invention provides a more efficient, flexible and adaptive beam forming strategy optimization method, and the performance of a wireless communication system is remarkably improved.

The invention discloses a wireless communication anti-interference method and system based on data analysis, and belongs to the technical field of communication anti-interference, in the wireless communication anti-interference method and system based on data analysis, the active defense capability of the system to unknown interference is improved through virtual interference generation and physical suppression by linkage cooperation of a generative adversarial network and an adaptive beam forming algorithm. The generator continuously simulates a novel interference signal injection training environment, so that a beam forming algorithm learns in advance to form accurate null in an interference direction, and the response time when actual interference occurs is greatly shortened. Meanwhile, interference space features detected by the beam forming module in an actual scene reversely optimize a signal construction rule of the generator, and the matching degree of a generated sample and a real electromagnetic environment is enhanced. The dynamic mutual promotion mechanism not only enhances the timeliness of interference suppression, but also reduces the problems of signal quality fluctuation and excessive consumption of hardware resources caused by passive response in the traditional scheme.

The invention relates to a microphone array sound source positioning method and system based on cross-correlation-beam forming closed-loop optimization, and belongs to the technical field of sound source positioning. The method comprises the following steps: collecting multichannel sound signals through a microphone array and preprocessing the multichannel sound signals to extract time-frequency features and suppress noise interference; time delay information among the microphones is estimated by adopting a generalized cross-correlation phase transformation algorithm, and an optimization strategy is introduced to improve estimation stability and anti-interference performance; enhancing the target sound source signal in combination with a minimum variance undistorted response beam forming algorithm and an adaptive Kalman filtering mechanism; constructing a closed-loop feedback optimization mechanism based on the beam output signal to realize feedback adjustment; and adopting a hybrid network architecture, taking the beam output signal amplitude spectrum as input, and outputting the frequency spectrum or mask of the obtained target sound source signal. The method has the advantages of high calculation efficiency, high positioning precision and strong anti-interference capability, and is suitable for real-time acoustic signal processing in a complex environment.

The invention discloses a gas extraction pipeline tiny leakage positioning method based on multi-sensor fusion, which belongs to the technical field of positioning, is used for gas extraction pipeline leakage positioning, and comprises the following steps: establishing a state equation and an observation equation of a motion process of an inspection robot, and realizing inspection robot positioning under a navigation system based on Kalman filtering. And realizing coal mine gas extraction pipeline leakage source positioning under a microphone array coordinate system based on a beam forming algorithm, and obtaining coal mine gas extraction pipeline leakage source positioning under a navigation system through coordinate conversion. According to the method, the leakage source position of the gas extraction pipeline under the navigation system is directly given, maintainers can conveniently and quickly reach the leakage source position, and the first-aid repair time is greatly shortened; the positioning error of the inspection robot can be effectively reduced, and the phenomenon that the positioning error is accumulated along with time when the inspection robot only uses an accelerometer and a gyroscope for positioning is avoided; the influence of background noise on a positioning result can be greatly reduced, and the spatial resolution of a leakage positioning result is improved.

The invention discloses a high-feature-resolution underwater weak target parameter estimation method based on NOMP, and the method comprises the steps: obtaining a receiving array signal, carrying out the preprocessing of the receiving array signal, carrying out the azimuth angle estimation through employing a conventional beam forming algorithm, and extracting a beam output signal in a main target direction; rough search is carried out on discrete time delay and Doppler factor grids, initial parameters of a current most significant path are estimated, continuous optimization is carried out through a Newton iteration method, and optimized path parameters are obtained; constructing a continuous path echo signal according to the received signal, deducting the contribution of the current path to the received signal from the received signal, updating a residual signal, and continuously searching the next path by taking the residual signal as a new input signal until an iteration termination condition is met; and outputting parameter estimation results of all paths. According to the method, high-precision and high-resolution extraction of weak target parameters can be realized in an environment with a low signal-to-noise ratio and remarkable underwater multipath interference.

The invention relates to the technical field of wireless communication, and discloses a wireless audio transmission optimization system based on adaptive beamforming, which comprises a multi-channel signal acquisition and preprocessing module for generating a feature matrix; the layered attention interference source feature extraction module is used for identifying the type and the position of an interference source; the user discomfort perception model building module is used for generating a personalized interference sensitivity map; the wave beam zero point dynamic adjustment module is used for dynamically adjusting the zero point position and depth of the wave beam forming algorithm; the reinforcement learning optimization module is used for receiving an execution result of the beam zero point dynamic adjustment module and user feedback data, continuously optimizing an interference suppression strategy by adopting a reinforcement learning method, and improving the adaptive capacity of the system to an unknown interference environment; through innovatively combining deep learning, user experience perception and reinforcement learning technologies, the problem of interference to wireless audio transmission is solved, and the user experience is optimized while the audio quality is improved.

The invention discloses an anti-suppression deception jamming detection suppression method and system, which combines the advantages of full autonomous navigation of inertial navigation, combines a satellite signal anti-interference processing technology, and comprehensively applies methods such as inertial / satellite integrated navigation, a multi-element satellite antenna array adaptive zeroing filtering algorithm, a beam forming algorithm and the like. And detection and suppression of suppression deception jamming are realized. According to the scheme of the embodiment of the invention, integrated navigation, a multi-array-element satellite antenna array zeroing adaptive algorithm and a satellite navigation anti-deception jamming signal processing method are integrated into one system at the same time; and a wave beam incoming vector obtained through combined navigation calculation is combined with a zero setting adaptive algorithm based on a multi-array-element satellite antenna array and an anti-suppression interference module, so that detection and suppression of suppression deception interference signals are realized. The scheme provided by the embodiment of the invention has a good anti-interference deception suppression effect.

The invention relates to the technical field of voice recognition, in particular to an implementation method and device of a multi-channel voiceprint recognition system, and the implementation method comprises the steps of multi-channel data acquisition and synchronization, signal preprocessing and enhancement, feature extraction and fusion, model training, real-time deployment and adaptive optimization. Compared with the problems that a traditional multichannel voiceprint recognition system depends on a fixed beam forming algorithm and an independent clock synchronization module, the synchronization error is large, manual parameter adjustment is needed for noise suppression, and generalization is poor, hardware-level clock synchronization is achieved through a PTP protocol, and the accuracy of noise suppression is improved. The method combines an end-to-end neural network to automatically learn noise distribution and a sound source space position, dynamically generates a beam forming weight, can improve the voice quality in a complex noise scene without manual intervention, remarkably reduces the interference of a synchronization error on sound source positioning, and enables the precision and stability of far-field voice enhancement to reach a new level.

The invention discloses a voice separation method and device, a storage medium and equipment. The method comprises the following steps: firstly, obtaining a to-be-separated mixed voice and a to-be-separated target video; acoustic features of the mixed voice are extracted; inputting the acoustic features of the mixed voice and an image of the lip shape of the target user contained in the target video into a multi-mode alignment model to obtain lip shape features of the target user; inputting the acoustic features of the mixed voice and the lip features of the target user into a multi-mode VAD model to obtain the separation probability of the mixed voice; and according to the separation probability of the mixed voice, in combination with a beam forming algorithm, multi-mode beam features corresponding to the mixed voice are calculated, then the acoustic features of the mixed voice, the lip features of the target user and the multi-mode beam features can be input into a multi-mode voice separation model, and according to a masking signal output by the model, the multi-mode voice separation is carried out. The target voice is separated from the mixed voice more accurately, so that the separation effect of the target voice is improved.

The invention discloses a portable satellite communication station signal optimization method and system, relates to the field of wireless communication, and is used for synchronously realizing dynamic adaptive management of multiple scattering paths. The method comprises the following steps: generating an earth surface image through multi-modal detection data, and carrying out layered calibration on scattering intensity; identifying a high-reflection sub-region according to the surface image and the layered calibration information thereof, and performing unified management on high-reflection and weak echo paths; based on the gain, interference and angle information of the multiple scattering paths, performing sub-array division on the antenna array according to priorities; phase stepping correction is carried out on the antenna units of the sub-arrays, and emission excitation is combined in adjacent path coverage areas; through a dynamic power scheduling and beam forming algorithm, the direction gain of each sub-array is optimized and sidelobe leakage is controlled. According to the invention, synchronous management of high reflection and weak echo paths can be realized, and the dynamic adaptability to scattering scenes is improved.

The invention discloses a federal learning assisted RIS joint beamforming method based on SCA and ADMM, and relates to the technical field of mobile communication. The invention provides a joint beamforming algorithm based on continuous convex approximation (SCA) and alternating direction multiplier (ADMM) by using federated learning to assist RIS for communication. The iteration of federated learning is optimized by using an SCA algorithm, so that faster convergence is realized; the ADMM algorithm is used to optimize the base station active beamforming and the RIS passive beamforming, and the energy efficiency and the sum rate of the system are improved.

The invention provides an intelligent reflection surface assisted low-altitude unmanned aerial vehicle Doppler-polarization combined beam forming system, and relates to the technical field of low-altitude communication, and the system comprises an unmanned aerial vehicle-mounted communication platform, a ground base station, a distributed deployment intelligent reflection surface array and a cooperative control system. According to the method, a joint channel model capable of capturing high-speed movement and a polarization effect is constructed; a Doppler polarization combined sensing and beam forming algorithm based on the model is designed, and processing is carried out on an unmanned aerial vehicle platform and / or a base station side; an IRS reflection coefficient optimization strategy considering Doppler and polarization characteristics is provided; and a set of self-adaptive cooperative control mechanism is established. Through cooperative work among the unmanned aerial vehicle end, the base station end and the IRS, the system can effectively compensate the Doppler effect and intelligently reconstruct a propagation environment by using polarization information and by means of the IRS, so that high-reliability, strong-anti-interference and large-coverage wireless communication is realized in a complex low-altitude dynamic environment.

The invention provides a multi-arm spiral subarray cooperative adaptive acoustic imaging system and method. The system adopts a circular substrate to construct an Archimedes spiral array. The innovative dynamic processing strategy comprises low-frequency sub-array combination and aperture expansion, intermediate-frequency independent processing and load balance maintenance, and high-frequency cross-arm virtual focusing array construction. The key technology covers multi-channel dynamic sampling, frequency band conflict arbitration, phase compensation beam forming and confidence weighted fusion. In the data fusion stage, a blind area is eliminated by adopting Delaunay triangulation and radial basis interpolation, and edge features are reserved in combination with anisotropic diffusion filtering. A temperature-sound velocity correction model is integrated in the system, and delay summation, MVDR and compressed sensing hybrid beam forming algorithms are applied to real-time processing. The output unit generates a three-dimensional acoustic thermodynamic diagram fusing Gaussian smoothing and edge enhancement. According to the scheme, the spatial sampling efficiency is optimized through spiral topology, the resolution and precision in a complex scene are improved through a dynamic recombination mechanism, and the method is suitable for industrial monitoring and noise source positioning.

The invention relates to the technical field of atmospheric humidity inversion, and relates to a GNSS-based atmospheric humidity inversion method and system, and the method comprises the steps: obtaining first information, second information and a trained first neural network, the first information comprises a GNSS signal collected by a low-altitude site, and the second information comprises surface humidity data around the low-altitude site; processing the first information by using a polarization filtering algorithm and a beam forming algorithm to obtain processed first information; training a second neural network according to the processed first information and second information to obtain a trained second neural network; inputting the first information and a correction parameter for correcting the wet delay into the trained first neural network to obtain an output result; and performing water vapor inversion according to the output result to construct a water vapor field. The method effectively improves the atmospheric humidity inversion precision of the low-altitude area.

The invention provides a special high-throughput satellite communication terminal for electric power, and relates to the technical field of electric power communication, and the special high-throughput satellite communication terminal comprises a baseband processing module which is used for carrying out differential encryption processing on different types of electric power data; the high-throughput satellite radio frequency module is used for suppressing sidelobe interference while realizing automatic satellite beam tracking through a beam forming algorithm during satellite communication, and calculating the optimal transmitting power through a self-adaptive power regulation algorithm; the communication transmission module is used for presetting a data priority based on a priority mapping table during data transmission and preempting satellite beam resources according to the data priority; the electric power Internet of Things protocol adaptation layer is used for realizing conversion between an electric power dedicated protocol and a satellite IP protocol, differential coding compression of electric power data and interrupted transmission in a link; and the beam optimization module is used for dynamically optimizing the beam pointing angle based on the satellite orbit parameters and the terminal geographic position. According to the scheme, the coverage degree of electric power communication in remote areas can be improved, and the safety and reliability of data transmission are improved.

The invention relates to the technical field of 5G communication modules, in particular to a 5G communication module capable of accurately positioning and a control method thereof, and the method comprises the steps: data acquisition: sampling from more than three 5G base stations or satellites at the frequency per second of 10-20 Hz, and comparing the time delay characteristics of different paths through employing a multipath signal separation algorithm according to the sampled data, a direct signal with the minimum time delay is reserved, signals of other paths are discarded, the time delay threshold value of multi-path separation is 10-20 ns, and signals with the delay larger than the threshold value are eliminated; according to the invention, the 5G antenna array module intelligently adjusts the antenna direction according to the receiving angle and the signal phase difference through the minimum mean square beam forming algorithm, and dynamically adjusts the beam width in combination with the environment density, thereby achieving the precise focusing and enhancement of signals, enabling the module to adaptively adjust the signal coverage in different complex environments, and achieving the adaptive adjustment of the signal coverage. The positioning stability is enhanced, the high-quality positioning effect is achieved, and the method is particularly suitable for a multi-path scene with many interferences.

The invention relates to the technical field of communication interference detection, and particularly discloses an interference detection method based on an OFDM communication system, and the method comprises the steps: S1, signal preprocessing, S2, time-frequency joint analysis, S3, deep learning model construction, S4, multi-interference source positioning, S5, intelligent interference suppression, and S6, interference information feedback. According to the method, Gaussian noise and non-Gaussian interference can be effectively distinguished through a third-order cumulant and other high-order spectrum analysis method, nonlinear features of complex signals can be captured, and the detection accuracy of complex interference is remarkably improved; the combination of the convolutional neural network and the long short-term memory network can automatically extract complex features in interference signals, provide more accurate interference type classification, utilize a beam forming algorithm and a multi-antenna array technology to accurately position a plurality of interference sources, and through a space-time joint estimation method, under the condition of facing the plurality of interference sources, improve the accuracy of the interference sources. And the positioning precision is obviously improved.

The invention provides a far and near field voice separation method and device and wearable equipment, and the method comprises the steps: obtaining a near field beam forming signal and a far field beam forming signal according to a microphone array signal collected in a target scene and a beam forming algorithm; calculating distinguishing characteristics between the near-field beam forming signal and the far-field beam forming signal; obtaining a near-field voice probability of the microphone array signal according to the distinguishing characteristics; and outputting a near-field signal and a far-field signal according to the near-field voice probabilities of the near-field beam forming signal, the far-field beam forming signal and the microphone array signal. According to the embodiment of the invention, the near-field voice and the far-field voice can be effectively separated through the microphone array signal, so that the human voice of a wearer and the far-field human voice are obtained.

The invention relates to a broadcast emission signal optimization method based on multi-antenna cooperation, and the method comprises the steps: constructing a multi-antenna cooperation broadcast emission system which comprises a central control unit, a distributed antenna array, an environment perception module and a terminal feedback module; real-time channel state information (CSI) is collected through the environment sensing module, and a dynamic propagation environment map is constructed; and optimizing a radiation pattern of the antenna array by adopting a three-dimensional beam forming algorithm based on the propagation environment map. According to the multi-antenna cooperative broadcast emission signal optimization method, a cooperative architecture of the central control unit, the distributed antenna array, the environment sensing module and the terminal feedback module is adopted, dynamic beam forming and power optimization are achieved, the coverage uniformity of broadcast signals is remarkably improved, and blind areas and overlapped interference areas are reduced; the energy utilization efficiency is improved, the energy waste caused by ineffective radiation is reduced, the self-adaptive capability of the system is enhanced, and the channel environment change can be responded in real time.

The invention discloses a directional sound wave loudspeaker control method based on MEMS, and relates to the technical field of stereo loudspeakers. By initializing the MEMS array, the microphone array and the control circuit, stable operation of the system is ensured. The microphone array accurately locates a sound source by using a TDOA or beam forming algorithm, and the control circuit calculates phase and amplitude parameters of the MEMS unit to realize high-precision beam forming. The MEMS acoustic metasurface array transmits directional sound wave beams according to parameter adjustment, a microphone in a target area monitors sound wave quality in real time, and a control circuit dynamically and finely adjusts array setting through a feedback optimization algorithm to adapt to environmental changes. The system has the advantages of high-precision positioning, efficient beam forming, real-time optimization and low power consumption, is suitable for scenes such as smart home and virtual reality, and remarkably improves sound wave directionality and quality stability.

The invention discloses a fast synthesis and beam forming method for an arbitrary polarization reconfigurable array. The fast synthesis and beam forming method can be widely applied to a low-cost large-scale phased array. According to the invention, the polarization states of the antenna units and the array beamforming algorithm are switched through the radio frequency switch, and beamforming of any polarization state can be realized under the condition that each antenna unit only uses one radio frequency channel. In the design process, firstly, polarization state arrangement is solved with the information entropy of the polarization reconfigurable array as an optimization target, an optimal array topological structure is obtained, and then the excitation amplitude and the excitation phase are solved with the expected polarization state and the expected scanning angle. The maximum innovation of the invention lies in that under the condition that each antenna unit only uses one radio frequency link, the wide-angle scanning capability of any polarization beam is realized through the irregular distribution of the polarization state.

The embodiment of the invention discloses an orientation estimation method, device and system for leakage noise of a water supply network. The method comprises the following steps: acquiring an acoustic signal acquired by a positioning array, wherein the array element spacing of the positioning array is smaller than half-wavelength; the method comprises the following steps of: extracting a main frequency band of each channel signal in an acoustic signal by utilizing power spectral density based on the channel signal acquired by each array element in the acoustic signal; the method includes determining an adaptive dominant frequency band of an acoustic signal based on dominant frequency bands of all channel signals in the acoustic signal. Furthermore, the method includes estimating the orientation of the leakage noise by using a beamforming algorithm based on the acoustic signal and its adaptive dominant frequency band. In this way, according to the embodiment of the invention, the small-aperture array can be used for replacing a leakage listening rod to collect the sound signals of the pipe network, the frequency component with the high signal-to-noise ratio in the self-adaptive main frequency band is screened out from the sound signals, and then high-resolution orientation estimation is achieved through the beam forming algorithm.

The invention discloses a low-altitude aircraft trajectory detection and channel tracking method based on super-large-scale MIMO, and the method comprises the steps: firstly transmitting a pilot signal to a base station by a user aircraft, designing a beam forming algorithm under a full-connection architecture, and then designing a beam forming algorithm capable of obtaining a channel image with obvious key point features under low pilot overhead, obtaining a channel image based on the hybrid beam forming architecture; the method comprises the following steps: designing an image key point detection algorithm, obtaining position information of an aircraft in an observation area at a first moment and performing fine adjustment, designing an efficient channel tracking module at a subsequent moment, then completing channel reconstruction and trajectory matching based on the estimated position information of the aircraft, and finally designing a trajectory-based low-altitude aircraft supervision algorithm. And track error detection, aircraft signal interruption detection, unauthenticated intrusion aircraft detection and the like of the aircraft in the authentication range of the base station are realized. According to the method, the uplink channel can be quickly estimated, and the real-time performance and reliability of a communication link between the aircraft and the base station are guaranteed.

A method operable to track reconstruction of a tissue volume from disjoint acoustic sensors. The method includes placing modular acoustic elements individually at positions with respect to the tissue volume, tracking the positions of the modular acoustic elements individually, creating a volumetric distribution map of the tracked modular acoustic elements, registering the volumetric distribution map, and reconstructing an image of the tissue volume or transmit a focused ultrasound by providing the registered distribution map to a beamforming algorithm.

The invention discloses a non-contact super-resolution guided wave array imaging method based on deep learning, and relates to the technical field of structure nondestructive testing and imaging. The method comprises the following steps: step 1, establishing a non-contact guided wave array for data acquisition, and applying a delay and summation beam forming algorithm to acquired guided wave array response data to generate an initial guided wave imaging image, step 2, extracting the space distribution probability of defects from the initial guided wave imaging image, constructing a de-noised DAS image, and carrying out de-noising on the de-noised DAS image. The method comprises the following steps: step 1, denoising a DAS image, and extracting a local sub-image region containing defects from the denoised DAS image, step 2, generating a high-resolution defect image through a multi-scale residual network, and dynamically optimizing an imaging result by adopting a quantitative index. The diffraction limit of a traditional imaging method is broken through in combination with a multi-scale deep neural network structure; and the subwavelength defect in the structure can be clearly visualized.

A method performed by a Radio Access Network (RAN) node. The method is for assisting a network node in locating a position of a User Equipment (UE) in a wireless communications network. The RAN node comprises a Multiple-Input Multiple-Output (MIMO) antenna system capable of performing beamforming. The RAN node receives (502), on the MIMO antenna system, one or more uplink signals from the UE. The one or more uplink signals comprises one or more out of: a Line of Sight (LoS) signal and one or more non LoS (nLoS) multipath reflections. The RAN node determines (503) an Angles- of-Arrival (AoA) and a Time-of-Arrival (ToA) related to the received LoS signal and each of the nLoS multipath reflections. The RAN node extracts (504), based on a temporal beamforming algorithm the LoS signal and the one or more nLoS multipath reflections, from the one or more received uplink signals. Additionally, the RAN node sends (505) information to the network node. The information comprises one or more out of one or more: determined AoA, determined ToA, extracted LoS signal and extracted nLoS multipath reflections.

The invention discloses a directional pickup system for intelligent glasses, which relates to the technical field of intelligent glasses and comprises heterogeneous microphone array modules used for being arranged on two sides of glasses legs to form spatial asymmetric array digital microphones and realizing coverage of + / -90 degrees in a horizontal plane and + / -30 degrees in a vertical plane by utilizing a binaural sound source positioning principle. The receiver is used for receiving acoustic signals from the environment. The adaptive beam control module calculates a sound source azimuth angle based on a dynamic beam forming algorithm and the delay inequality of microphone array signals, adjusts digital beam pointing in real time, and updates the frequency to be greater than or equal to 50Hz; according to the multistage noise suppression module, a bone conduction sensor is integrated at a nose pad of a glasses frame, sound source positioning is assisted through jaw vibration signals, environmental noise is suppressed, and a three-stage noise reduction mode is set; and the execution module is used for executing switching of pickup modes based on sound sources with different distances, wherein the pickup modes comprise a near-field mode and a far-field mode. According to the invention, through fusion of bone conduction and air conduction, environment pickup is effectively and adaptively carried out.

The invention discloses voice enhancement intelligent glasses based on ambient light and motion perception, and belongs to the technical field of intelligent glasses. Voice enhancement intelligent glasses based on ambient light and motion perception comprise a glasses frame and a supporting part, the supporting part is connected with the glasses frame through a hinge, and the supporting part comprises a first glasses leg and a second glasses leg; the camera is fixedly connected to the mirror frame; the first sensor is fixedly connected to the mirror frame; the gyroscope is connected to the glasses frame; the main control board is fixedly connected in the second glasses leg; the main control board is electrically connected with the camera and the first sensor through connecting wires; bone conduction loudspeakers are connected in the first glasses leg and the second glasses leg; the voice definition is effectively improved by utilizing the light intensity and color temperature data collected by the ambient light sensor and adjusting the gain and balance of the voice signals, the head movement track is tracked in real time in combination with the gyroscope, the pickup direction of the microphone array is dynamically adjusted in combination with the beam forming algorithm, and the movement artifact noise is effectively reduced.

The invention provides a coal gangue identification method, which comprises the following steps of: firstly, determining the layout of an auditory sensor array; then, coal gangue audio signals are collected, and array element receiving signals are obtained; then, implementing a beam forming algorithm on each array element receiving signal to obtain an audio feature representing coal gangue difference information in a beam forming signal; processing the obtained audio features to obtain a multi-dimensional tensor matrix x containing the coal gangue audio features; and finally, by taking the multi-dimensional tensor matrix chi as input, identifying the coal gangue by using a deep learning network to obtain a coal gangue identification result. According to the auditory coal gangue recognition method provided by the invention, the auditory sensor array is adopted, and the influence of factors such as noise and underground equipment interference on coal gangue audio recognition can be remarkably reduced by performing beam forming on the audio signals of the target area; and the classification identification model is combined to carry out intelligent identification on the coal gangue, so that the coal gangue identification accuracy is improved.

The present invention discloses a method and system for detecting and suppressing anti-suppression deception interference. Combining the advantages of fully autonomous navigation of inertial navigation and satellite signal anti-interference processing technology, it comprehensively utilizes inertial / satellite combined navigation, multi-element satellite antenna array adaptive zeroing filtering algorithm, beamforming algorithm and other methods to achieve detection and suppression of anti-suppression deception interference. The solution of the embodiment of the present invention integrates the combined navigation, multi-element satellite antenna array zeroing adaptive algorithm and satellite navigation anti-suppression interference signal processing method into one system, and combines the beam direction vector calculated by the combined navigation with the zeroing adaptive algorithm based on the multi-element satellite antenna array and the anti-suppression interference module to achieve detection and suppression of suppression deception interference signals. The solution provided by the embodiment of the present invention has good anti-interference suppression deception effect.