3149 results about "Signal source" patented technology

The invention relates to the field of wearable equipment, and discloses a data processing method for assisting old people based on a smart watch, and the method comprises the steps: building an old people individual physiological baseline library at a smart watch end, and carrying out the dynamic comparison of the dislocation difference between a real-time collection signal and the baseline library; performing behavior interference separation on the individual compensation sequence, and generating a health time sequence feature block after interference stripping based on a multi-scene embedding model; an event entropy triggering mechanism is introduced into the health time sequence feature block, and when the drift rate exceeds an individual self-adaptive threshold value, a candidate health abnormal event is automatically marked; calibrating a signal source corresponding to the candidate health abnormal event as a local feedback loop node, and performing coupling correction on a signal in a local feedback loop; and based on the health monitoring priority feedback map, in combination with the global circadian rhythm change trend and the accumulated weight of the abnormal event, generating a multi-level interaction prompt instruction. The method has the advantage of improving the accuracy of the health monitoring data of the old people.

The invention discloses a zero-sequence pilot-frequency excitation method for a double-circuit line in an incomplete power failure environment, which comprises the following steps of: applying zero-sequence pilot-frequency signal excitation on a power failure line by using a pilot-frequency power supply as an excitation signal source of a zero-sequence network of the double-circuit line, different-frequency induced current and voltage are measured at secondary sides of a current transformer and a voltage transformer at two sides of the operation line, and different-frequency zero-sequence voltage and different-frequency zero-sequence current in the double-circuit line zero-sequence network are obtained; simultaneously solving a zero-sequence network equation, and calculating mutual impedance between double circuits; performing frequency conversion to obtain the power frequency mutual impedance of the line; and finally, carrying out simulation verification by constructing a non-full-stop double-circuit line zero-sequence mutual inductance impedance measurement system. According to the method, the multi-path coupling caused by the existing power frequency interference method and the accuracy problem caused by the signal measurement error of the zero sequence increment method are solved, the test calculation can be accurately completed under the complex interference working condition, and the safety risk caused by the single-phase reclosing operation is avoided.

The invention discloses an eSIM service cost intelligent optimization method based on different operator information sources, and particularly relates to the technical field of operator network management. The method comprises the following steps: collecting eSIM tariff rules of a plurality of operators and real-time charging data of eSIM terminals, extracting tariff terms and conditional expense trigger mechanisms hidden in charging behaviors of different operators by using an association rule mining algorithm, and constructing a multi-level cost structure model; on the basis of a network registration behavior log of the eSIM terminal, predicting the probability that each operator signal source has an abnormal registration event, and evaluating the risk that each operator signal source triggers a hidden cost trap in combination with a multi-level cost structure model; and according to the real-time network signal parameters of the eSIM terminal, a signal source recommendation strategy is generated in combination with the risk assessment result, and the eSIM terminal is driven to execute a signal source switching operation, so that real-time adjustment and cost optimization control of communication network selection are realized, and the service stability of the eSIM in a cross-network use scene is improved.

The invention provides a signal blind separation and intelligent reconstruction method and system in a complex scene, and relates to the technical field of signal processing, and the method comprises the steps: receiving an aliasing signal, and converting the aliasing signal into a multi-channel signal observation matrix; performing decomposition in a wavelet domain to obtain a wavelet coefficient, matching the wavelet coefficient with the sparse dictionary, and reconstructing a target signal source after optimization; estimating the number of signal sources based on covariance matrix eigenvalue distribution; mapping a signal source to a graph structure domain, extracting space and time sequence correlation through a mixed graph convolutional network, and obtaining a target separation signal through variational reasoning optimization; and finally, carrying out quality evaluation and post-processing to obtain a final reconstruction signal. According to the invention, the signal separation precision and robustness in a complex scene are improved.

The invention relates to the technical field of numerical control system fault pre-diagnosis, and particularly discloses a fault monitoring method and system for a numerical control machine tool. The method comprises the steps that a spindle vibration signal, a cutting force signal and a spindle current signal are collected; outputting an alignment signal set; respectively executing adaptive filtering processing according to the alignment signal set; constructing a multi-dimensional feature vector; constructing a health index under the processing behavior period; then accumulated trend deviation analysis is executed through a CUSUM algorithm; and judging whether the tool wear trend is abnormal. The technical problem that in the prior art, static threshold judgment is carried out based on a single signal source, and especially in a numerical control machining scene with signal noise interference, accurate early warning of the early wear trend of a tool cannot be achieved is solved. Due to the fact that a period calibration mechanism fusing spindle vibration, cutting force and current signals, feature vector entropy weight optimization and a CUSUM trend detection mechanism are adopted, the pre-diagnosis level of the numerical control machine tool on cutter state changes is improved.

The invention provides a broadband tunable low-phase-noise photo-generated microwave signal source and device, and relates to the technical field of photo-generated microwaves. According to the invention, a low-frequency optical pulse and a high-frequency microwave signal are respectively input into the electro-optical sampling phase-locked loop; and the electro-optical sampling phase-locked loop determines the synchronization error of the optical pulse and the microwave signal based on the phase difference between the optical pulse center point and the microwave signal zero crossing point. And taking the synchronization error as a feedback signal, and continuously adjusting the frequency and the phase of the microwave signal by the voltage-controlled oscillation module until the frequency and the phase are synchronized with the Nth harmonic of the optical pulse. By setting different initial frequencies of the voltage-controlled oscillation module, microwave signals with different integral multiple optical pulse frequencies can be obtained, and broadband tuning of photo-generated microwave signals is realized. Furthermore, the repetition frequency of the frequency comb is locked through beat frequency of two beams of reference laser and two adjacent comb teeth, the stability of the reference laser is transmitted to the optical pulse, and the stability of the reference laser is further transmitted to the microwave signal through synchronization of the optical pulse and the microwave signal, so that the phase noise of the photo-generated microwave signal source is reduced.

The invention discloses an equipment management system and a server, and relates to the technical field of servers, and the equipment management system is characterized in that a topology identifier storage assembly for storing slot position signal source identifiers is moved to a server mainboard end, so that the occupation of mainboard connector pins by information transmission is reduced; and meanwhile, the management control component establishes and stores a corresponding relation between the address of the arbitration component and the screen printing area of the case. The adapter card does not need to be pre-bound and configured, can automatically identify the screen printing area of the case through the relationship by inserting any communication interface of the mainboard, and generates slot screen printing information in combination with the pre-stored signal source identifier. The problems that a large number of pins are occupied due to the fact that the adapter card hardware address signal identification configuration needs to be transmitted through a connector, and the adapter card needs to be bound with the fixed configuration and lacks flexibility in the prior art are solved. The technical effects of reducing pin occupation, realizing flexible plugging of the adapter card and automatic identification of screen printing, reducing hardware development cost and meeting the requirement of the server for reserving more bus interfaces for the connector are achieved.

The invention discloses a signal sampling method for a multi-channel signal converter, and the method comprises the steps: carrying out the synchronous and parallel sampling of an analog signal source according to a multi-channel signal collection module, so as to obtain multi-channel original signal sequence data; performing inter-channel time delay calibration and amplitude normalization processing on the multichannel original signal sequence data to obtain a calibrated multichannel signal data set; the invention relates to the technical field of signal processing. According to the signal sampling method for the multi-channel signal converter, the multi-channel signal converter improves the data consistency and accuracy through the technologies of synchronous sampling, time delay calibration, amplitude normalization and the like, meanwhile, precision adjustment of self-adaptive filtering, dynamic threshold segmentation and entropy driving is adopted, signal interference and abnormal data are reduced, and the signal quality is improved. The non-uniform resampling and compression technology is adopted to optimize the storage and transmission efficiency, key data is ensured to be transmitted preferentially, hardware is accelerated through an FPGA, and the real-time performance and the processing capacity of the system are improved.

The invention discloses a spatio-temporal cross-scale dimension reduction characterization method, system and device for a multi-modal physiological signal. The method comprises the steps of multi-modal signal time sequence alignment, sliding variable scale segmentation, single-modal spatio-temporal feature pre-training, cross-modal coupling alignment and model migration application. In the single-mode spatial-temporal feature pre-training, single-mode signal fragments under different time processes or spatial arrangements are reconstructed through a codec, and multi-level spatial-temporal modeling and analysis of a signal source are realized; in cross-modal coupling alignment, spatial-temporal characteristics of physiological signals of other modals are reconstructed through a codec, and a coupling relationship among different modals of a physiological system is learned; the model after cross-modal coupling alignment can be migrated to a specific task for fine tuning, and the comprehensive characterization capability of physiological signals in a few modals, specified space or limited time collected by a backward device on a physiological system is enhanced. According to the method, through bottom-layer dimension reduction and migration, effective characterization of the whole complex physiological state by the easily obtained signals is achieved.

The present disclosure relates to the technical field of electromagnetic wave sensors, in particular to a signal transmitting, calibration, compensation and transceiving links, an integrated circuit, an electromagnetic wave sensor and a device, wherein the transmitting link includes an analog signal source and a digital phase shifter, the analog signal source may be configured to provide an initial analog signal, and the digital phase shifter may be configured to provide a phase shift signal in a digital domain and to perform phase shifting on the initial analog signal based on the phase shift signal, so as to perform a preset phase shifting operation on the initial analog signal, thereby effectively improving the phase modulation resolution and phase modulation accuracy.

The invention relates to the technical field of cable asset health management and predictive maintenance, and discloses a cable discharge signal blind separation and enhancement processing method based on an adversarial network, and the method comprises the steps: building a multi-modal monitoring data set through collecting mixed signals and environment data in cable operation; blind separation of discharge signals is realized by using the generative adversarial network, and prior information is not needed; identifying the number of potential signal sources through covariance analysis and double-criterion estimation; iterative optimization and signal enhancement are carried out in combination with a graph neural network and variational reasoning; and finally, through multiple cross validation and quality correction, an enhanced signal with high reliability is output. According to the method, the signal processing technology is deeply fused with asset management, risk prediction and operation and maintenance decision, weak discharge signals can be effectively separated and enhanced under the condition of low signal-to-noise ratio, the accuracy and reliability of cable early fault diagnosis are improved, and credible data support is provided for cable asset health state assessment, risk prediction and operation and maintenance decision.

The invention discloses a sparse Bayesian direction of arrival estimation method based on subspace compression and dictionary optimization, and belongs to the field of array signal processing. According to the method, the data dimension is reduced through the subspace compression technology, and the noise immunity is improved; signal power and noise power are automatically estimated in combination with a sparse Bayesian model, and dependence on information source number information is avoided; the calculation efficiency and the numerical stability are improved through a support set adaptive pruning strategy; and finally, a dictionary fine tuning mechanism is introduced, direction continuous optimization is realized on the basis of an original discrete grid, an off-grid error is eliminated, and direction-of-arrival estimation with sub-resolution precision is realized. The method is a novel method combining subspace compression, sparse Bayesian inference, adaptive pruning and angle optimization, can give consideration to estimation precision, calculation efficiency and application robustness, and is especially suitable for direction estimation under the complex actual conditions of low signal-to-noise ratio, few snapshots, unknown signal source number and the like.

The invention provides a pilot frequency combiner and a multi-system access platform, the pilot frequency combiner comprises a first substrate waveguide resonant cavity, the first substrate waveguide resonant cavity is provided with at least two input feed line ends, the at least two input feed line ends are used for introducing excitation signals of different information sources, a second substrate waveguide resonant cavity is stacked on the first substrate waveguide resonant cavity, and the second substrate waveguide resonant cavity is used for feeding excitation signals of different information sources. The second substrate waveguide resonant cavity is provided with an output feeder end, and the second substrate waveguide resonant cavity and the first substrate waveguide resonant cavity share a cavity wall; the common cavity wall is provided with at least two through coupling holes, and the coupling holes are communicated with the first substrate waveguide resonant cavity and the second substrate waveguide resonant cavity, so that excitation signals input by the at least two input feeder line ends are transmitted to the second substrate waveguide resonant cavity, and are output to an external antenna radiation end after being combined by the output feeder line end. According to the pilot frequency combiner provided by the invention, the isolation degree of multi-band signals is relatively good, the frequency expansibility is also good, and the design flexibility is relatively high.

The invention discloses a safety early warning method and system based on Beidou + UWB positioning, and relates to the technical field of personnel positioning and safety early warning, and the method comprises the steps: collecting positioning signal data in real time, and carrying out the preprocessing; based on real-time quality evaluation of a positioning signal source, adaptively adjusting a fusion weight, and generating a continuous high-precision positioning data sequence; predicting a future motion trail by using the trail prediction model, performing border crossing judgment in combination with electronic fence spatial data, and outputting a border crossing prediction mark; performing risk analysis by taking the track sequence and the border crossing mark as input and combining the spatial distance between the personnel and the electronic fence, the movement speed and the regional risk level, and outputting a risk score and a level mark thereof; and performing graded response according to the risk grades, and recording and feeding back safety early warning data. According to the invention, high-precision continuous positioning in a complex environment is realized, personnel border-crossing active early warning and risk grading response are supported, and the real-time performance, the accuracy and the intelligent level of safety supervision are remarkably improved.

The invention relates to the technical field of discharge monitoring and early warning, in particular to a partial discharge real-time monitoring and early warning system based on multi-source data fusion, which is characterized in that decision tree classification is carried out on a mixed transient signal flow through a signal physical separation module, and pure electromagnetic wave speed type and mechanical wave speed type signal sources are separated; the feature marking module extracts feature points with a unified time reference and marks physical attribute categories; the double-path credibility fusion module executes time difference logic verification on the two types of feature points, a credible discharge event is marked only when an electromagnetic wave verification result and a mechanical wave verification result are logic values 1 at the same time, event confidence parameters are generated through dynamic confidence fusion, and physical interlocking verification and uniqueness locking are achieved; the anti-interference response module dynamically adjusts a response threshold value based on the event confidence parameter, and only triggers a targeted response to the threat which is physically and essentially confirmed to be real discharge and has confidence reaching the standard; the problem of distinguishing a real discharge event from multi-source interference is solved, and the real discharge event is reliably identified.

The invention discloses a geotechnical engineering slope stability real-time monitoring method and a geotechnical engineering slope stability real-time monitoring system, which are characterized in that a blind source separation technology combining independent component analysis and physical constraint is introduced, an original displacement time sequence and an environment temperature time sequence of a plurality of GNSS (Global Navigation Satellite System) measuring points are regarded as multi-channel mixed signals, and statistical independence among signal sources is utilized to monitor the stability of a slope in real time. Periodic environment noise, instrument random noise and drift and real slope deformation signals are effectively separated from the mixed observation signals; and then, through correlation verification with physical quantities such as the field environment temperature and the like, automatic calibration is performed on the separated source signals, and temperature effect source signals and long-term creep source signals with physical labels are accurately identified and extracted, so that accurate elimination of noise components and high-fidelity reconstruction of pure deformation signals are realized. Therefore, the accuracy of real-time monitoring of the slope stability of geotechnical engineering can be effectively improved, and a solid data basis and a decision basis are provided for early warning and prevention of slope disasters.

The invention provides a microwave superheterodyne frequency sweep measurement system based on Rydberg atoms, and belongs to the technical field of microwave frequency measurement. The laser module excites detection light of 780 nm and coupling light of 480 nm, and the two beams of light are reversely input into the atomic gas chamber through the dichroscope; signal microwaves are generated by a radio frequency signal source and are radiated to the position of the atomic gas chamber through the horn antenna; local oscillation microwaves are generated by the microwave module and are also radiated to the position of the atomic gas chamber through the horn antenna; the atomic gas chamber serves as a mixer to form a difference frequency signal; the spectrum analyzer is used for monitoring low-frequency difference frequency signals generated in the frequency mixing process in real time and recording signal intensity in real time. According to the invention, high-precision and wide-band microwave frequency measurement is realized, continuous and smooth frequency sweeping response can be provided in a frequency range, and absolute frequency detection of microwave signals is realized under the condition that a complex frequency comb technology is not introduced. The hardware architecture is simplified, the automation degree is improved, and integration, popularization and application are facilitated.

The invention relates to the technical field of fault detection, in particular to a high-voltage connector loosening fault detection method and device and an automobile, and the method comprises the following steps: forming a surface acoustic wave resonator array based on an interdigital transducer array, an acoustic wave resonator and a flexible waveguide; butting a signal source radio frequency cable with the pin interdigital electrode chip, triggering data acquisition, performing Fourier transform on original data, and judging the loosening risk of the connector according to each parameter threshold value; carrying out three-dimensional modeling on the connector plugging interface, carrying out modal analysis on the model, and obtaining surface acoustic wave frequencies, group velocities and phase distribution under different pre-tightening forces so as to identify a contact force abnormal region; based on a multi-stage early warning mechanism, rapid locking is achieved through electrorheological fluid, and displacement is finely adjusted through a magnetostrictive rod. According to the invention, the loosening hidden danger can be quickly and accurately locked, a tight protection system is constructed by multi-stage early warning and mechanical self-locking, and the loosening risk of the high-voltage connector can be greatly reduced from early warning to active intervention.

Provided are automatic level control (ALC) circuit, signal source, method for controlling signal source output power, and storage medium. The ALC circuit includes: at least two stages of ALC loops, each ALC loop including an amplifier, a coupler, a power detector, and an attenuation control module connected sequentially. An output end of an adjustable attenuator is connected to an input node of first stage of ALC loop; an output node of each stage of ALC loop, other than last stage of ALC loop, is connected to a normally on end of a two-way single-on switch, a first gating end of the two-way single-on switch is connected to an input node of a next stage of ALC loop, and the output node of the last stage of ALC loop and a second gating end of each two-way single-on switch are connected to an output end of the ALC circuit.

The invention provides a test method and a test system for a digital optical fiber repeater, an external signal source is not needed, the resource occupation is low, and the independent test of each part of the digital optical fiber repeater is supported, the test method comprises the following steps: a waveform data packet is pre-stored, and the waveform data packet comprises waveform data intercepted from a standard test signal; in response to the test instruction, performing signal reconstruction based on a pre-stored waveform data packet, and generating a test waveform conforming to a communication standard; outputting the test waveform to a radio frequency hardware link of the digital optical fiber repeater, processing the test waveform through the radio frequency hardware link, converting the test waveform into a testable radio frequency signal, and outputting the testable radio frequency signal; and demodulating the output radio frequency signal through the test equipment, and carrying out radio frequency parameter calibration.

The invention discloses a sparse regularization direction of arrival estimation method based on a risk minimization principle, and belongs to the technical field of array signal processing and underwater acoustic signal processing. The method comprises the steps of receiving array signals and establishing an observation model; constructing a sparse representation and over-complete dictionary; establishing and initializing a regularization optimization model; carrying out adaptive weight updating and risk-driven parameter selection; after regularization parameters are determined, a fast iterative shrinkage threshold algorithm FISTA is adopted to carry out optimization solution, and dictionary refinement is carried out on the detected direction after each iteration convergence so as to reduce off-grid errors; and after a small amount of outer layer iteration is repeated, outputting a final DOA estimation result and corresponding power. According to the method, self-adaptive selection of regularization parameters and noise levels can be realized, and the problem of precision degradation under complex conditions of low signal-to-noise ratio, limited snapshot number, signal source correlation, power imbalance and the like is effectively solved without manual parameter adjustment, so that the robustness and practicability of estimation are remarkably improved.

The invention relates to the technical field of signal reconstruction, in particular to a complex electromagnetic environment-oriented millimeter wave signal blind source separation and reconstruction system, which comprises a frequency spectrum trend division module, a path fading construction module, an initial cluster label generation module, a multi-solution path screening module and a fusion reconstruction execution module. According to the method, power spectral density sequence processing is carried out on millimeter wave frequency domain data, a multi-dimensional feature group is formed according to a path loss factor, an angle of arrival and the like, and an initial feature cluster is screened through an Euclidean distance, so that the accuracy of signal source classification is effectively improved; after the frequency domain response and the phase contour are continuously subjected to point comparison, path screening is completed by integrating a mean square error residual value, the path misjudgment probability is reduced, time domain resampling and phase frequency offset standardization are executed in fusion reconstruction, the consistency and fidelity of signal reconstruction are enhanced, and the reconstruction precision is improved. The whole process improves the separation accuracy and reconstruction precision of mixed signals in a complex electromagnetic environment.

The invention discloses a satellite antenna servo system vibration sound signal sample enhancement method based on a physical constraint generative adversarial network, and the method comprises the steps: carrying out the multi-mode signal collection and fault simulation, and providing a high-fidelity signal source for training; fault physical parameter modeling is carried out, and a fault physical parameter vector and a fault frequency equation are defined; constructing a physical constraint generative adversarial network training model, and designing a double-branch generator and a physical constraint discriminator; training the physical constraint generative adversarial network, and outputting a high-fidelity vibration sound sample; according to the invention, intelligent fault early warning and diagnosis support is provided for stable operation of a satellite communication system.

The invention relates to the technical field of data fusion, in particular to a multi-source electrocardiosignal correction method and system based on adaptive fusion, and the method comprises the following steps: constructing a multi-channel input tensor, extracting local features through a weight calculation network, carrying out the adaptive weight fusion and dimension reduction of multiple paths of signals, and carrying out the correction of the multi-source electrocardiosignal. A nonlinear mapping relation is established through a deep reconstruction network, a standard waveform is reconstructed, and network parameters are optimized based on reconstruction error reverse iteration. According to the method, local neighborhood features of multichannel signals are extracted by constructing a weight calculation network, a dynamic channel weight sequence reflecting the real-time contribution degree of a signal source is constructed, the amplitude intensity is adaptively adjusted according to the signal quality, unstable channel noise interference is effectively inhibited, and high-quality signal components are enhanced; a deep reconstruction network is used for carrying out nonlinear feature transformation on a fusion sequence, accurate mapping from non-standard input to standard lead waveforms is established, and weight distribution and optimization of signal reconstruction parameters are achieved in combination with an error back propagation mechanism.

The invention relates to an integrator circuit for eliminating thermal noise and a Delta-sigma modulator, and belongs to the technical field of electronic signal processing, the modulator comprises at least two stages of integrators, a quantizer, a feedback DAC and an adder; the integrator comprises an integrator circuit, and the integrator circuit comprises a sampling module for sampling an input signal source; the double-path multi-phase clock control pre-amplification auxiliary storage circuit module alternately samples and stores thermal noise voltage and offset voltage; the integral amplifier is used for amplifying a signal output by the double-path multi-phase clock control pre-amplification auxiliary storage circuit module; and the integrating capacitor is connected between the integrating amplifier and the two-way multi-phase clock control pre-amplification auxiliary storage circuit module, and feeds back the signal after integration processing to the two-way multi-phase clock control pre-amplification auxiliary storage circuit module to realize signal modulation and noise shaping. The thermal noise introduced in the sampling process is effectively reduced, and the area of the whole chip is reduced while the signal-to-noise ratio is improved.

The invention provides an electrical performance calibration device and method for fusing electrolytic hydrogen production and a hydrogen fuel cell. The electrical performance calibration device comprises an upper computer, a first digital sampling voltmeter, a second digital sampling voltmeter, a synchronous data acquisition card, a synchronous inspection switch, a current converter, a voltage converter, an electric pile, a programmable power supply, a self-calibration module and an external calibration signal source, the synchronous inspection switch is used for detecting a single-cell voltage bus of a galvanic pile and feeding back the single-cell voltage bus to a sampling end of the first digital sampling voltmeter, and a feedback end of the first digital sampling voltmeter is connected with a first input end of the upper computer; the current converter is used for detecting a current loop of the galvanic pile; the voltage converter is used for detecting the total voltage of the electric pile; and the programmable power supply is connected with a power supply terminal of the electric pile. According to the invention, the problems of poor synchronism, lack of self-calibration, low impedance measurement precision and incompatibility of two-way metering during electrical performance calibration of electrolytic hydrogen production and hydrogen fuel cells are solved.

The invention discloses a high-speed serial signal linear equalization circuit which comprises an input terminal, a continuous time linear equalizer (CTLE), a super source follower, a variable gain amplifier (VGA) and an adaptive feedback. The input end is connected with a 100-ohm internal resistance differential signal source of the transmitting end through a channel; the equalization circuit CTLE is connected to the output end of the input end connection module, two groups of resistance switches (RsMF and RsHF) of the CTLE module are respectively controlled by 4-bit binary codes to enable source degeneration resistors Rs of two stages of CTLEs to be variable, two groups of capacitance switches (CsMF and CsHF) are respectively controlled by 2-bit binary codes to enable source degeneration capacitors Cs of the two stages of CTLEs to be variable, and the two groups of capacitance switches (CsMF and CsHF) are respectively controlled by 2-bit binary codes to enable source degeneration capacitors Cs of the two stages of CTLEs to be variable. The change of a zero pole of the circuit is realized through the change of the source degeneration resistor Rs and the source degeneration capacitor Cs, and the adjustability of the difference between the high-frequency gain and the low-frequency gain of the circuit is realized, so that the multi-gear adjustability of the equalization capability is realized.

The invention discloses a hydropower station signal source side data anti-interference acquisition method and system. The method comprises the following steps: constructing a multi-source interference feature recognition network according to an environment state of a hydropower station, obtaining an interference source distribution feature spectrum, and obtaining an original signal through space-frequency domain joint filtering preprocessing based on the spectrum; performing recursion processing on the original signal by adopting an adaptive Kalman filtering algorithm to obtain a high-fidelity target signal; processing the high-fidelity target signal based on a multi-scale feature extraction and verification mechanism to obtain a credibility quantitative purification signal; and processing the credibility quantitative purification signal based on a compensation strategy to obtain a high-reliability output signal. According to the method, the influence of interference signals is gradually removed from interference source identification, filtering processing, signal reconstruction and quality evaluation to signal compensation, and finally, a result subjected to multiple anti-interference processing is obtained, so that various interferences in a complex environment of a hydropower station can be effectively resisted, and high-reliability data acquisition is realized.

The invention relates to the technical field of wireless communication, and discloses an information source number detection method and system based on a non-circular signal. The method comprises the following steps: calculating a compensation sample covariance matrix of a received signal, and obtaining a sample canonical correlation coefficient through Takagi decomposition of the compensation sample covariance matrix; constructing a marginal likelihood function of the maternal typical correlation coefficient; taking a sample canonical correlation coefficient as an estimated value of a corresponding matrix, and establishing an estimated statistic by applying a minimum description length criterion; and obtaining the number of the parent typical correlation coefficients when the estimation statistic is minimized, and taking the number as an estimation value of the actual number of the non-circular signals. According to the method, the characteristic that the non-circular signal compensation covariance is not zero is fully utilized, the marginal likelihood function with the minimum redundancy parameters is adopted to construct the statistics, high-precision estimation of the number of the non-circular signals can be achieved, and necessary guarantee is provided for practical application scenes such as direction of arrival estimation and wave velocity formation.

The invention provides a low-altitude multi-source equipment data base fusion method and system based on deep learning, and belongs to the technical field of low-altitude data processing. A multi-modal dynamic strategy generation engine is adopted to analyze multi-dimensional context information such as equipment modality, space environment and task intention and generate an optimal fusion strategy instruction; according to the present invention, adaptive adjustment fusion is carried out according to the current situation, when the GPS signal is interfered, the dependence on the GPS signal is automatically reduced, the weight of other reliable signal sources is enhanced, and when the optical sensor fails in the heavy fog weather, the data processing assembly line is dynamically reconstructed, the image processing micro service is bypassed, and the radar data is preferentially processed. The dynamic self-adaption and toughness anti-interference capability of the low-altitude multi-source data fusion process is improved, various interferences can be effectively resisted, high-precision fusion output is always kept in a complex and changeable low-altitude environment, data source selection and weight are flexibly adjusted according to a real-time dynamic environment and task requirements, and the real-time dynamic environment and task requirements are met. And the accuracy and the response speed of low-altitude multi-source data fusion are improved.