6655 results about "Interference (communication)" patented technology

The invention discloses a self-adaptive frequency spectrum monitoring and interference suppression method for a railway power transformer. The method comprises the following steps: S1, collecting original multi-source signal data; s2, performing high-order filtering and Z-score normalization processing on the original multi-source signal; s3, inputting the original multi-source signal into a multi-scale residual fusion time-frequency transformation network, and extracting a time-frequency feature tensor; s4, inputting the time-frequency feature tensor into the interference identification network fused with the attention mechanism; s5, dynamically activating an interference suppression module according to an identification result; s6, constructing a multi-dimensional tensor data structure, extracting sparse dictionary morphological features and spectral domain statistics, and generating a composite feature vector set; s7, inputting the composite feature vector into a health state evaluation module; and S8, uploading the diagnosis result to a remote monitoring platform through the embedded communication module. According to the invention, multi-dimensional perception and adaptive modeling are fused, and intelligent identification and remote monitoring of railway transformer faults are realized.

The present disclosure relates to a communication scheme and system therefor for converging an Internet of things (IoT) technology with a 5th generation (5G) communication system for supporting a higher data rate after a 4th generation (4G) system. The present disclosure is applicable to intelligent services (e.g., smart home, smart building, smart city, smart car or connected car, health care, digital education, retail, security and safety-related services, or the like) based on 5G communication technology and IoT-associated technology. The present disclosure discloses a method of measuring and reporting interference in a wireless communication system.

A wireless communication method and system enabling dynamic multi-path data transmission and reception across heterogeneous radio access networks. The method includes selecting between sequential, concurrent, or redundant multipath transmission strategies based on real-time measurements of link quality parameters, including signal-to-interference-plus-noise ratio (SINR), reference signal received power (RSRP), delay, and spectrum availability. The system further enables adaptive transmission power control, modulation scheme selection, and carrier configuration based on physical layer feedback, minimizing interference and optimizing spectral efficiency. Peer-to-peer communication between terminals is supported without base station mediation, reducing RAN load. Multi-base station connectivity is enabled, allowing terminals to simultaneously transmit through multiple nodes and aggregate at the core network. The architecture supports real-time topology control, dynamic link adaptation, and transmission parameter adjustment based on physical-layer constraints.

The invention provides a signal optimization transmission system and method based on HPLC and HRF dual-mode communication, a signal acquisition and processing module of the signal optimization transmission system based on HPLC and HRF dual-mode communication is used for acquiring signals of two communication modes of HPLC and HRF in real time, preprocessing the signals and extracting key signal parameters; the dual-mode switching module is used for dynamically switching an HPLC mode and an HRF mode based on channel quality; the access module is used for constructing a longitudinal backbone network and a transverse Mesh network, forming a hybrid topology, optimizing a routing path and coordinating resource allocation and conflict avoidance of HPLC and HRF; the intelligent decision module is used for predicting future interference intensity according to the historical interference data and adjusting channel parameters; the central coordinator module is used for network initialization and resource allocation; according to the system and the method, the HPLC mode and the HRF mode are automatically switched according to the channel quality, the longitudinal HPLC backbone network is combined with the transverse HRF Mesh network to form a four-dimensional communication network, and the robustness in a complex scene is remarkably improved.

The invention relates to the technical field of communication, in particular to an underground power distribution room communication system and method based on heterogeneous network and multi-modal fusion, and the system comprises a three-dimensional heterogeneous network cooperation module, a cross-modal feature fusion module, a dynamic routing decision engine module, a self-adaptive interference suppression system and a cross-layer cooperation optimization module. The three-dimensional heterogeneous network cooperation module comprises a 4G / 5G wireless communication sub-layer, a power line carrier communication sub-layer and an edge computing management sub-layer; the cross-modal feature fusion module comprises a multi-modal encoder group, a shared feature projection layer, a twin network structure and a cross-modal attention fusion module; and the dynamic routing decision engine module comprises a state space monitoring unit, a routing optimization unit and a millisecond-level path switching strategy. Through the arrangement, the reliability, the real-time performance and the energy efficiency of communication of the underground power distribution room are systematically improved, and a high-robustness communication infrastructure is provided for an intelligent power grid.

The invention discloses a low-altitude unmanned aerial vehicle trajectory tracking and monitoring method based on a 5G-A communication sensing integrated base station, and relates to the technical field of low-altitude traffic management and communication sensing fusion, and the method comprises the steps: firstly collecting multi-source data such as a communication sensing fusion signal, environment interference and unmanned aerial vehicle attributes, and carrying out the alignment and packaging of a unified timestamp and a coordinate system into a synchronous data frame; then, deep fusion and anti-interference processing are carried out on the data frames, noise is filtered out, and pure fusion data is generated; and furthermore, real-time track calculation and motion trend prediction are carried out on pure data by utilizing multi-base-station cooperative calculation and prediction. Based on this, through a multi-target feature recognition and clustering separation mechanism, independent individual trajectories are accurately stripped from a complex mixed data stream, and compliance verification and anomaly judgment are performed on the trajectories in combination with an airspace rule base. In this way, the problems of signal interference and multi-target aliasing in a complex environment can be effectively solved, and therefore high-precision global tracking of the low-altitude unmanned aerial vehicle and real-time monitoring of abnormal behaviors are achieved.

The invention discloses an unmanned aerial vehicle anti-interference communication link control method based on heterogeneous network convergence, and relates to the technical field of unmanned aerial vehicle anti-interference communication, and the method comprises the steps: S1, interference sensing and network state modeling, S2, intelligent link decision making, S3, spectrum avoidance and resource scheduling, S4, distributed feedback and cooperative anti-interference, and S5, heterogeneous network cooperative relay. S6, resource allocation and energy efficiency optimization; S7, performance evaluation and parameter optimization; and S8, multi-link redundancy backup. According to the invention, through S1, S2 and S7, a sensing, decision-making and optimization closed-loop system is constructed, LSTM interference prediction and three-dimensional network modeling in S1 provide accurate input, a dual deep Q network in S2 realizes low-delay link decision-making, and KPI evaluation and genetic algorithm dynamic parameter adjustment in S7, the signal-to-interference ratio is improved, the anti-interference adaptability is improved compared with a traditional passive response mode, and the method has the advantages that the method is simple and convenient to operate, and the cost is low. The creative breakthrough that interference does not reach strategy precedence is realized; through S3 and S4, an active anti-interference mechanism is formed, and compared with a single avoidance or suppression method, the interference elimination efficiency is improved.

The invention relates to the technical field of wireless communication, in particular to a wireless communication anti-interference enhancement system based on multi-mode signal fusion. Comprising an intelligent signal transceiving module, a signal sensing and preprocessing module, an interference feature coding and classification module, an interference suppression decision module, an interference suppression module, a signal fusion module, an interference suppression performance evaluation module, an interference feature library and an interference suppression strategy library, the interference feature coding and classification module adopts a three-layer progressive architecture of multi-dimensional manifold feature extraction, feature transformation and coding inspired by a group theory, and deep learning classification based on chaotic dynamics, extracts interference features from three dimensions of time domain, frequency domain and nonlinearity, and realizes accurate interference identification; the signal fusion module adopts a multi-level fusion strategy, and dynamically adjusts the fusion weight according to the signal quality; the interference suppression module selects an optimal suppression strategy according to the interference type, and executes frequency domain cancellation, space domain cancellation and time domain cancellation; and performance evaluation feedback forms a closed-loop optimization mechanism.

The invention discloses a satellite communication method and device and a storage medium. The satellite communication method comprises the following steps: determining the suitability between different sub-bands of a satellite and different beams of the satellite; constructing a chromosome population formed by a plurality of chromosome vectors; according to the suitability, initializing the chromosome vector; a fitness function is constructed, and the fitness function is used for indicating the severity degree of same-frequency interference occurring in the multiple coverage areas after sub-bands are allocated for all the beams according to the chromosome vectors; performing iterative optimization on the chromosome population through the fitness function according to a genetic algorithm, and determining an optimized chromosome vector; and according to the optimized chromosome vector, allocating a corresponding sub-band to each beam, and carrying out satellite communication. Therefore, the distributed sub-band with the lowest fitness can be determined for each beam, and interference between same bands is avoided.

The present invention relates to the technical field of communication anti-interference, and relates to an interference confrontation method, system, device and medium for a wireless communication network, the method comprising: obtaining spectrum data, the spectrum data comprising spectrum data deployed and collected by a wireless network according to an initial deployment scheme; performing feature extraction and fusion processing on the spectrum data to generate a spectrum situation map; performing reinforcement learning decision processing according to the frequency spectrum situation map to generate a dynamic anti-interference strategy; according to transmitting node combination parameters in the dynamic anti-interference strategy, a collaborative bait node group is obtained through distributed consensus algorithm processing; sending a virtual signal to an interference source according to the dynamic anti-interference strategy and the collaborative bait node group; and calculating the strategy effect of the virtual signal by using a reinforcement learning reward function to obtain an optimized anti-interference strategy, thereby breaking through the limitation of insufficient static coping and cooperation of a traditional anti-interference method, and realizing communication reliability and anti-interference adaptability in a complex dynamic interference environment.

The invention discloses a resource allocation method and system for 5G communication in an underground coal mine, and relates to the technical field of communication information processing, and the method comprises the steps: obtaining data information of an underground coal mine roadway, building a digital twin communication model through combining a synchronous positioning and map building algorithm and a wireless fingerprint matching algorithm, generating a channel profile map according to real-time data, and transmitting the channel profile map to a server; extracting channel data of each space node; constructing a computing resource pool for the 5G base station and the edge computing node, and packaging different service types into a plurality of network slice containers; according to the channel data, carrying out initial allocation on each container through a resource composer, and carrying out dynamic task migration among different MEC nodes to obtain a resource allocation state; dividing scheduling time according to a channel profile and a resource allocation state, and dynamically adjusting a duration proportion and bandwidth occupation of each window according to a task migration state; according to the invention, through digital twinning and dynamic scheduling, the problems of 5G communication coverage and interference in the underground coal mine are solved.

The invention relates to the technical field of artificial intelligence, and discloses a Bluetooth communication intelligent speech translation method and system based on multi-mode enhancement, and the method comprises the steps: collecting a multi-channel audio signal through a built-in multi-microphone array of a Bluetooth device, carrying out the dynamic direction self-adaptive beam forming of the multi-channel audio signal, and carrying out the self-adaptive beam forming of the multi-channel audio signal; extracting a Mel spectrogram feature of the direction enhancement signal, identifying lip regions of a plurality of candidate speakers in each frame of real-time speaking video captured by a camera, performing time sequence convolution on the lip regions to obtain a lip movement time sequence embedded vector, calculating a correlation score with the Mel spectrogram feature, separating the direction enhancement signal, and obtaining a lip movement time sequence embedded vector; and performing text transcription and conversion on the high-confidence separation voice to obtain a translation language text, and sending the synthesized target translation voice to a preset mobile terminal through the Bluetooth device to obtain a target translation result. According to the method, the real-time performance and accuracy of speech translation are improved in a multi-person scene, far-field speech, noise interference and accent difference.

The invention provides a signal shielding method based on deep reinforcement learning, and belongs to the technical field of artificial intelligence and communication crossing. The method comprises the steps that S1, a large number of historical wireless communication signals are acquired to construct a data set to train a signal interference strategy generation model; s2, deploying the signal interference strategy generation model to a signal shielding device; s3, verifying and analyzing the signal shielding instruction to obtain a shielding parameter, collecting a real-time wireless communication signal, and inputting the real-time wireless communication signal and the shielding parameter into a deployed signal interference strategy generation model to obtain a real-time signal interference strategy; and S4, the signal shielding device modulates the real-time interference signal based on the real-time signal interference strategy, and the power amplifier performs power amplification on the real-time interference signal and then transmits the real-time interference signal to the outside through the radio frequency antenna so as to perform signal shielding. The method has the advantages that the accuracy, the real-time performance and the expansibility of signal shielding are greatly improved, and the power consumption of signal shielding is reduced.

The invention discloses a dynamic beam adaptive optimization method for the Internet of Vehicles, and the method comprises the steps: firstly obtaining the current position, speed and driving direction of a vehicle, and carrying out the prediction of a future trajectory through combining historical trajectory information and employing a Kalman filtering technology and the like; and selecting a candidate beam direction from the predefined beam codebook. The system receives channel quality feedback information of a communication link in real time, and dynamically updates a beam forming weight based on an improved recursive least square algorithm. According to the algorithm, a composite adaptive adjustment mechanism of an error size and an error change trend is introduced, a multi-objective optimization function is constructed, and performance indexes such as link quality maximization, interference power minimization and beam switching frequency minimization are effectively balanced in a dynamic environment, so that an optimal beam direction is obtained. Finally, the real-time switching of the antenna array beams is realized through a low-overhead and low-delay control protocol. According to the method, track perception and a self-adaptive feedback mechanism are fused, and good real-time performance, stability and expandability are achieved.

The invention discloses an unmanned aerial vehicle communication terminal supervision method based on multi-source information fusion, and the method comprises the following steps: S1, multi-source information collection: collecting multi-source heterogeneous data of an unmanned aerial vehicle communication terminal in parallel, the multi-source heterogeneous data at least comprises terminal transmitting power, received signal strength (RSSI), signal-to-noise ratio (SNR), adjacent region interference strength, wireless link transmission error rate, terminal positioning data, flight state data and environmental meteorological data; and S2, information fusion and feature extraction: carrying out space-time alignment and normalization processing on the multi-source heterogeneous data collected in the step S1, inputting the data into an information fusion model for feature layer fusion, and outputting a group of fusion feature vectors capable of comprehensively representing the current operation state of the communication terminal. According to the invention, more reliable unmanned aerial vehicle communication terminal supervision can be realized.

The invention relates to the technical field of monitoring systems, in particular to an electromechanical equipment control method and system for building intelligent system integration. Comprising the following steps: collecting operation parameters of electromechanical equipment and building environment parameters in real time; the operation parameters and the building environment parameters are transmitted to a central control unit through a communication network; the operation parameters of the central control unit and the building environment parameters are input into a preset evaluation model, and the operation state and abnormality diagnosis information of the equipment are output; generating a corresponding control strategy through an intelligent algorithm; the control command is converted into a control command through the central control unit and is sent to the execution mechanism through the communication network, and the execution mechanism regulates and controls the electromechanical equipment and sends a feedback signal to the central control unit. The multi-source sensor is used for collecting operation parameters and environment parameters in real time, and the data precision is guaranteed in combination with a self-calibration mechanism; meanwhile, data interference and leakage risks are reduced through encryption processing, and a high-quality data basis is provided for subsequent analysis.

The invention provides an OTFS radar communication integrated signal processing method and system based on time-frequency-space domain joint optimization. According to the method, pilot symbol positions and densities are configured in an OTFS time-frequency grid according to channel time-varying characteristics and bandwidths, and a Doppler index range is set to optimize channel information acquisition; deploying a controllable reflecting surface, constructing a phase modulation matrix based on a target position and communication channel parameters, dynamically adjusting a phase gradient direction, and separating energy of a target echo and a communication signal; within a set Doppler index range, calculating frequency offset estimation, correcting a time domain sampling point of a received signal, and generating a phase correction vector; and positioning a spatial aliasing main interference area, and inhibiting symbol interference and spatial aliasing caused by a high-speed target through frequency domain beam forming weighting and phase rotation compensation in combination with a phase correction vector and a sub-Doppler parameter in the area. According to the invention, time-frequency-space domain cooperative efficient processing of OTFS radar communication integrated signals is realized.

The invention relates to the technical field of wireless communication, in particular to a production line wireless communication system and method. The system comprises a multi-dimensional feature sensing module, an interference intelligent cognition and decision-making module, a communication opportunity decision-making module and a channel resource arrangement module. An expected action sequence, transient current features and spatial position topology of an interference source are collected through a multi-dimensional feature sensing module, and an interference source multi-dimensional feature set is generated through fusion; the interference intelligent cognition and decision-making module performs space-time spectrum joint modeling of an interference field based on the feature set, generates a workshop electromagnetic environment situation map, constructs a whole network link toughness map in parallel, and generates a conflict-free communication scheduling table through fusion analysis and multi-dimensional cost optimization; the communication opportunity decision module converts the dispatch table into an executable instruction; and the channel resource arrangement module executes the instruction and realizes closed-loop feedback. According to the method, the problem of communication uncertainty caused by industrial electromagnetic interference is solved, and reliable transmission of key services such as automatic guided vehicle scheduling and man-machine interaction is ensured.

Aspects of the subject disclosure may include, for example, receiving, via an antenna, a communication signal generated by a communication device, and detecting interference in the communication signal, wherein the interference is generated by one or more interference sources, wherein the interference is detected by monitoring a near field region of the antenna, an intermediate field region of the antenna, a far field region of the antenna, or any combinations thereof, wherein the monitoring excludes monitoring only the far field region of the antenna. Other embodiments are disclosed.

This disclosure provides systems, methods, and apparatuses, including computer programs encoded on computer storage media, for wireless communication. In one aspect of the disclosure, a method for wireless communication performed by a user equipment (UE) includes receiving cross-link interference (CLI) resource configuration information and angle-of-arrival (AoA) estimation configuration information, The method also includes receiving CLI associated with an uplink transmission transmitted by another UE, and determining a CLI value for the CLI based on the CLI resource configuration information. The method includes determining an AoA value associated with the CLI based on the AoA estimation configuration information, the AoA value corresponding to an estimated AoA at the UE associated with the uplink transmission. The method further includes transmitting CLI report data indicating the determined CLI value and AoA report data indicating the estimated AoA value. Other aspects and features are also claimed and described.

The invention discloses an unmanned aerial vehicle soft landing control method based on track prediction and multi-source cooperative decoy, and the method comprises the steps: introducing a communication protocol recognition mechanism in a blocking process of an instruction link of an unmanned aerial vehicle, and achieving the conversion from extensive broadband suppression to protocol precise interference; the problems that in the prior art, power consumption is high, interference on legal communication is large, and the frequency hopping unmanned aerial vehicle resisting effect is insufficient can be effectively solved. In the scheme, signal integrity is guaranteed through monitoring and preprocessing, an unmanned aerial vehicle link protocol is identified through feature extraction and protocol library matching, and then a targeted interference template is generated, so that the interference effect can accurately fall on key positions such as a leader sequence, a CRC field, a subcarrier or a control frame and the like; therefore, synchronization, verification or data transmission can be destroyed under the condition of low power, and accidental damage of broadband noise to services such as co-frequency Wi-Fi and Bluetooth is avoided.

The invention discloses an optical fiber vibration signal time identification and classification method, system and device based on a Mam-YOLOv10 neural network and a medium, and belongs to the technical field of optical fiber communication, and the method comprises the steps: obtaining OTDR signals of a plurality of targets based on an optical fiber vibration signal collection system, and carrying out the denoising of the OTDR signals; performing short-time Fourier transform on the de-noised OTDR signal to obtain a two-dimensional time-frequency diagram of the vibration signal; based on the two-dimensional time-frequency diagram, multi-scale features of the optical fiber vibration signals are extracted; and inputting the multi-scale features into a Mam-YOLOv10 neural network containing a Mama attention block to complete identification and classification of the optical fiber vibration signals. According to the method, the influence of interference fading on the pattern recognition accuracy is effectively reduced, meanwhile, the hardware complexity is reduced, the attention weight is automatically adjusted according to different fault scenes and data characteristics, and the accuracy of optical fiber fault recognition and classification is improved.

The invention provides a dual-unmanned aerial vehicle cooperative obstacle avoidance and communication link reconstruction system and method, and belongs to the technical field of wireless communication and unmanned aerial vehicle cooperative control. The system is composed of two unmanned aerial vehicles, serves as a mobile base station to provide relay communication for users, and cooperatively perceives an aerial target. The method comprises the following steps: establishing an integrated model integrating tracks, NOMA signals and layered continuous interference cancellation; calculating communication and sensing key indexes; constructing an optimization problem which takes maximization of the minimum average interaction rate between the unmanned aerial vehicles as a target and takes power, QoS, perception and security constraints into consideration; a distributed architecture is adopted to decompose problems, and a Dual-TD3 algorithm is proposed to collaboratively optimize beam forming and a flight path. According to the dual-unmanned aerial vehicle cooperative obstacle avoidance and communication link reconstruction system and method, dynamic intelligent distribution of communication and sensing resources is realized, and the interaction rate, the robustness and the resource utilization rate of the system in a dynamic scene are remarkably improved.

The invention discloses a ship state monitoring system and method based on multi-source data, and relates to the technical field of ship engineering, the system comprises a bionic flexible sensing module, a multi-source data acquisition module, an anti-interference communication module, a multi-source data fusion module, an edge calculation processing module, an intelligent fault diagnosis module and a man-machine interaction and decision support module; wherein the bionic flexible sensing module acquires broadband vibration signals, the multi-source data acquisition module accesses multi-source data, the anti-interference communication module realizes data transmission based on a metamaterial antenna and the like, the multi-source data fusion module generates a standardized data set, and the edge calculation processing module completes feature extraction and abnormity pre-screening. The intelligent fault diagnosis module locates a fault and generates a report, and the man-machine interaction and decision support module visualizes data; the bottleneck of curved surface detection is broken through, data transmission is guaranteed, and accurate diagnosis is realized.

The invention relates to the technical field of communication signal analysis, in particular to a communication signal analysis method and device, equipment and a storage medium. The method comprises the following steps: carrying out full-band signal continuous acquisition on a detection area, and extracting an original signal flow; performing potential electromagnetic interference detection and electromagnetic interference distribution marking on the original signal flow to obtain an interference source distribution diagram; dynamic interference suppression is carried out based on the interference source distribution map, real-time suppression parameter adjustment is carried out, and a calibration optimization signal flow is constructed; performing real-time intensity calculation on the calibration optimization signal flow, and constructing a regional signal intensity distribution model; and performing signal quality evaluation and real-time decision early warning based on the regional signal intensity distribution model. According to the method, the communication signal quality and stability of the area can be accurately and rapidly evaluated.

The invention provides an auxiliary method and device for a phased-array antenna to track a low-orbit satellite. The method provided by the invention comprises the steps of predicting a movement track of a satellite based on an initial parameter, and determining an initial direction of a phased-array antenna based on the movement track; analyzing the power density change of a first satellite signal received by the phased-array antenna, predicting the relative position change of the phased-array antenna and the satellite based on the power density change, and adjusting the direction of the phased-array antenna based on the relative position change; when the difference between the direction of the phased-array antenna and the direction of a second satellite signal actually received by the phased-array antenna is larger than a preset value, the direction of the phased-array antenna is corrected based on the actual strength and the receiving direction of the second satellite signal, and the corrected phased-array antenna points to the satellite. The method and the device provided by the invention are used for solving the problems of insufficient precision, strong interference sensitivity, weak recapture capability and the like of a traditional tracking system, and reliable support is provided for efficient and stable communication of low-orbit satellites.

The invention discloses a high-dynamic mobile ad hoc network communication and sensing integrated routing method, device and equipment and a storage medium, an OFDM (Orthogonal Frequency Division Multiplexing) sensing system is adopted to actively acquire feature information of neighbor nodes, and meanwhile, neighbor features passively acquired based on communication feedback are matched and fused, so that the sensing precision and efficiency in an ad hoc network are remarkably improved. In order to reduce noise interference of a wireless communication environment and realize prediction of a future state of a network, a Kalman filter is adopted to carry out dynamic filtering and state estimation on neighbor feature information. And on the basis of the processed sensing data, the node further calculates stability and effectiveness indexes of the link, inputs the stability and effectiveness indexes into a link quality comprehensive evaluation model constructed by fuzzy logic, and finally generates predictive link quality parameters to provide priori knowledge for following routing selection. And the routing efficiency and the resource utilization are optimized through an on-demand routing normal form and a multipath routing mechanism. And meanwhile, through a node early warning mechanism and a fault pre-detection mechanism, the control overhead is remarkably reduced, and the network stability is improved.

The present invention relates to the technical field of energy meter electrical parameter measurement. Disclosed is an intelligent anti-interference system for a power line carrier energy meter. The system comprises: collecting voltage and current signals of a power line, and constructing a sample database; performing time-frequency feature classification by means of a preset model, and establishing feature and scenario mapping by synchronizing scenario recognition results; building a scenario interference recognition network on the basis of the mapping result; collecting real-time data of N communication channels of a power line carrier energy meter, and performing channel coordination decision and anti-interference enhancement; performing communication data evaluation on the basis of a comprehensive scoring function; and performing anti-interference management on the basis of channel access decision, anti-interference enhancement, and a parallel access result. The present invention solves the technical problem of poor accuracy and reliability of metering data of existing power line carrier energy meters caused by interference signals and noise when the power line carrier energy meters are in complex electromagnetic environments, and achieves the technical effect of improving the anti-interference capability and the reliability of the power line carrier energy meters.

The invention discloses a noise signal recognition method based on deep learning. The method comprises the steps of original signal collection, signal preprocessing, noise recognition feature extraction, noise signal recognition model establishment and noise signal intelligent recognition. The invention relates to the technical field of digital signal data processing, in particular to a noise signal identification method based on deep learning, and innovatively provides a self-adaptive signal mode decomposition method based on a combined judgment mechanism of energy threshold value judgment and energy range value judgment. Decoupling and reservation of different frequency bandwidth information in an original signal can be effectively completed, and the recognition accuracy of non-stationary communication noise is improved; a frequency band filter bank constructed based on a Gaussian function is introduced, so that the accuracy of communication signal identification is improved; a method for constructing a noise recognition model by fusing graph neural network structure modeling and an original type reference vector matching mechanism is innovatively proposed, and the recognition robustness of the model to non-stationary communication interference signals is improved.

The invention provides an anti-interference sound signal data extraction method based on energy data perception, and belongs to the technical field of underwater sound signal processing, and the method comprises the steps: carrying out the A / D sampling and digital orthogonal demodulation of a received sound signal, and obtaining a baseband signal; performing low-pass filtering and downsampling on the baseband signal to obtain a preprocessed signal; performing matched filtering on the pre-processed signal by using a reference signal; the key improvement lies in that a local energy estimation function of a preprocessed signal is calculated, and normalization processing is carried out on a matched filtering result and the energy estimation function to obtain a normalized detection signal. The method effectively suppresses the shielding effect of a strong interference signal on a weak target signal under a non-orthogonal reference signal and a strong near-end and weak far-end scene, remarkably reduces the misrecognition probability, and improves the accuracy and reliability of the extraction of a long-distance and low-signal-to-noise-ratio target beacon signal in a complex underwater acoustic environment. The method is suitable for underwater navigation, positioning and communication systems.