1973 results about "Signal source" patented technology

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 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 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 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 discloses a distinguishing table type X-ray spectrometer and an X-ray absorption spectrum testing method, and relates to the technical field of spectral measurement. The high-resolution table type X-ray spectrometer comprises a sample signal source which is located in a Dowland circle and is used for generating X-rays; the exponential crystal is a bent crystal, the surface shape of the exponential crystal is defined by an exponential equation, so that different points on the curved surface of the crystal have different curvature radiuses and correspond to Rowland circles with different radiuses, each point on the exponential crystal is tangent to the corresponding Rowland circle, and the exponential crystal is used for performing monochromatization and focusing on the X-ray incident from the sample signal source; and the detector is positioned on a surface formed by the corresponding imaging points on each Rowland circle, and is used for receiving the X-rays which are monochromatized and focused by the index crystal and outputting corresponding light intensity signals. Therefore, through the cooperation of the index crystal and the multi-Rowland circle structure, the X-ray absorption spectrum test with high light receiving efficiency, high spectral resolution and wide energy spectrum range can be realized, and the comprehensive performance of the desk type spectrometer is improved.

The invention discloses a short-wave time difference positioning method based on particle swarm optimization, which is realized by aiming at a short-wave signal source positioning problem under the condition that ionized layer information is unknown through the following steps of: dynamically screening a receiving station combination with optimal geometric distribution by adopting a particle swarm optimization algorithm based on longitude and latitude and time difference observation data of a receiving station group; taking the main receiving station as a coordinate origin, and converting the geographic coordinates of the selected station into rectangular plane coordinates; constructing a time difference positioning equation set by using a Chan algorithm, and calculating a target position through pseudo-inverse solution and an iteration strategy; and filtering the ill-conditioned solution based on a geometric accuracy factor threshold, analyzing a positioning point cluster through sliding window density, and outputting median coordinates as a final positioning result. According to the method, the receiving station is innovatively selected and modeled as a combinatorial optimization problem, the positioning precision in a complex electromagnetic environment is remarkably improved through a collaborative architecture of particle swarm optimization and a Chan algorithm, and the problem of positioning drift caused by poor geometric distribution of stations in a traditional method is effectively solved.

A method and apparatus are provided, in which a higher layer configuration is received (2002), where the user equipment is configured with two timing reference signals for receiving a common communication having a same set of data from multiple signal sources. A downlink scheduling assignment including downlink control information is received (2004) in a control channel scheduling a physical downlink shared channel, wherein the downlink scheduling assignment comprises an indication of a transmission configuration indicator identifying two transmission configuration indicator states, which each indicate quasi-co-location information of a demodulation reference signal corresponding to the physical downlink shared channel relative to a respective one of the first and the second timing reference signals. The physical downlink shared channel is then received (2006) according to the downlink scheduling assignment including the downlink control information.

The invention discloses an underwater navigation positioning method and system based on supercontinuum laser intensity correlation. The system comprises a master control system, a transmitting end underwater base station and a receiving end underwater carrier. The method comprises the following steps: firstly, a main control system generates a super-continuum laser signal with pseudo-random code information, the super-continuum laser signal is separated into optical signals of different wavelength channels through a light splitting module, and the optical signals are respectively sent to underwater base stations uniquely corresponding to the wavelength channels and are emitted; then the underwater carrier receives optical signals from a plurality of base stations, identifies a signal source base station according to wavelength identification, performs correlation operation with a locally copied pseudo-random code sequence, determines signal arrival time TOA and calculates a pseudo-range; and finally, resolving the three-dimensional coordinate and local clock error result of the underwater carrier by combining the pseudo-ranges, absolute positions and transmission delays of the underwater carrier and the at least four base stations. According to the invention, high-precision and high-robustness absolute positioning of the underwater environment is realized, and the reliability of long-time positioning and navigation of the underwater robot is enhanced.

The invention discloses a spindle cutting force prediction method and device based on a multi-channel deep learning model and electronic equipment, and the method comprises the steps: building multi-channel time sequence input through collecting three-direction vibration signals of a machine tool spindle and three-phase current signals of a spindle motor, and inputting the signals into a multi-scale convolutional neural network module to extract local features; modeling a time dependency relationship through a bidirectional long-short-term memory network, and introducing a multi-head attention mechanism to enhance the modeling capability for a key time slice; fused features are sent into three independent output sub-networks, and cutting force components in the X direction, the Y direction and the Z direction are predicted respectively. In order to improve the overall prediction precision and the dynamic response capability of the model, a weighted composite loss function combining a mean square error, a time sequence smooth item and a peak value weighted item is designed. Compared with a traditional prediction method based on a physical model or a single signal source, the method does not need additional force measurement hardware, and is high in adaptability, high in prediction precision and fast in response to cutting force sudden change.

The invention discloses a dynamic positioning precision optimization system based on a self-learning fusion model, and relates to the technical field of wireless positioning. Comprising the steps that an acquisition and synchronization module synchronously acquires AOA, RSSI and TOA signals from a plurality of anchor points and generates a synchronous multi-source signal flow; the discrimination module extracts multi-dimensional instability characteristics such as fluctuation entropy, angle jitter and delay abrupt change rate of the signal flow, and classifies the current channel environment into predefined modes such as high occlusion, non-line-of-sight error or stable line-of-sight; the mapping module calls a corresponding weight distribution strategy according to the modal identifier to generate a real-time fusion weight vector; the adaptive positioning module couples the weight vector to an unscented Kalman filter observation model, dynamically adjusts the weight of each signal source in state updating, and outputs an estimated position and a positioning confidence coefficient; the optimization module monitors the positioning confidence and iteratively optimizes the weight strategy online based on the deviation of the positioning confidence from the target value. The method effectively improves the positioning precision and robustness in a complex dynamic scene.

A half-spectrum search DOA estimation method based on characteristic value gradient jump belongs to the field of array signal processing, and comprises the following steps: modeling a received signal to obtain an array output vector; calculating a received signal covariance matrix; introducing a complex conjugate covariance matrix and a scanning source to construct a new covariance matrix, and constructing a spatial spectrum function; constructing a characteristic value gradient discrimination function, and adaptively estimating a signal source number by using the characteristic value gradient discrimination function; scanning angles are traversed by using a half-spectrum search method, and a signal direction of arrival is verified and determined by combining an MVDR algorithm according to a sharp spectrum peak formed by a spatial spectrum function. According to the method, source number priori knowledge is not needed, the source number can be identified autonomously, the problem that estimation is inaccurate under complex conditions in traditional half-spectrum search is solved, and the method has good robustness under the scene of unknown source number. According to the method, the limitation that few traditional half-spectrum search angle estimation is inaccurate is overcome, and a new thought is provided for half-spectrum search DOA estimation under the condition that the number of information sources is unknown.

The invention relates to the technical field of defect detection, and discloses an insulating sleeve defect detection method and device based on electromagnetic induction, and the method comprises the steps: employing a main detection coil to excite a composite insulating sleeve to generate an electromagnetic field, and employing an auxiliary compensation coil to receive a mixed induction signal; performing interface reflection component extraction on the mixed induction signal, and calculating a dielectric parameter value of the composite insulating sleeve; calculating an interface compensation parameter of the auxiliary compensation coil based on the dielectric parameter value; generating a compensation magnetic field opposite to an interface reflection phase by using an auxiliary compensation coil according to an interface compensation parameter, and receiving a compensated detection signal by using a main detection coil and performing phase gradient analysis to obtain a position coordinate and a size parameter of an internal defect of the composite insulating sleeve; according to the invention, hardware-level separation of electromagnetic excitation and interface compensation is realized, active inhibition of interface reflection is carried out from a signal source, and automation and intelligentization of defect detection of the composite insulating sleeve are further realized.

In some implementations, the techniques described herein relate to a method including: receiving a stream of security events from a plurality of event generators; generating security signals based on the security events, the security signals including a subset of the security events; aggregating and correlating the security signals using a signal source; evaluating the security signals and determining risk levels using a plurality of independent processors; determining that action is required based on a combined output of the security signals and determined risk levels; and executing a security response responsive to the action.

The invention discloses an eye pattern generation method based on channel simulation, a storage medium and electronic equipment, and the method comprises the steps: carrying out the channel simulation according to a target channel parameter, a signal source parameter and an initial code pattern sequence, and generating jitter-free initial eye pattern data; obtaining a deterministic jitter parameter and a random jitter parameter, and generating a deterministic jitter time sequence based on the obtained deterministic jitter parameter and the initial code pattern sequence; generating a random jitter time sequence based on the obtained random jitter parameter; synthesizing the deterministic jitter time sequence and the random jitter time sequence to generate a total jitter time sequence offset sequence; and modulating time sequence information in the initial eye pattern data by using the total jitter time sequence offset sequence to generate a target eye pattern. Simulation of deterministic jitter and random jitter is added in the channel simulation process, and the consistency of the simulation result and the signal characteristic of a real communication scene is greatly improved.

The invention provides a medical accelerator beam excitation device and a control method thereof, and belongs to the technical field of medical accelerators, and the medical accelerator beam excitation device comprises an integrated exciter which comprises a horizontally arranged first electrode pair and a vertically arranged second electrode pair; the excitation signal source is used for generating a working point excitation signal or a slow extraction excitation signal; the excitation signal source outputs a working point excitation signal or slowly leads out the excitation signal to the power amplification and routing module, and the power amplification and routing module is used for performing power amplification on the received excitation signal and routing the amplified excitation signal to the first electrode pair or the second electrode pair; and the first electrode pair and the second electrode pair are used for applying an excitation effect on the beam current according to the amplified excitation signal. According to the application, the excitation electrode and the power amplification link can be multiplexed, and two functions of working point excitation and slow extraction excitation can be simultaneously realized on one set of device, so that the space of the accelerator is effectively saved.

The invention discloses a multi-frequency-point multi-polarization parallel sampling phased-array antenna automatic calibration platform, and relates to the technical field of antennas, and the platform comprises a control center which is used for parameter modeling and test task configuration, parallel sampling strategy generation, and data storage and tracing; the FPGA hardware controller is used for generating synchronous trigger pulses and synchronously triggering the radio frequency switch matrix, the multi-path signal source, the six-axis mechanical arm, the multi-probe array module, the double-axis rotary table and the vector network analyzer VNA array; the radio frequency switch matrix is used for quickly switching multi-frequency-point multi-polarization signals; the multi-path signal source, the six-axis mechanical arm, the multi-probe array module, the double-axis rotary table and the vector network analyzer VNA array are used for synchronously collecting test data; the data processing module is used for receiving the sampling data, calculating a test index and carrying out closed-loop compensation and result verification; the test efficiency, the equipment utilization rate and the measurement precision are remarkably improved, and full-process automatic calibration and multi-dimensional data tracing are achieved.

The invention relates to the technical field of transformer substation monitoring, and discloses a power supply and distribution safety monitoring method and system for a transformer substation. The method comprises the following steps: acquiring various data in a transformer substation, and performing time synchronization calibration on the three types of data; dividing a power supply and distribution operation mode into a steady-state mode, a transient mode and an overload mode based on the calibrated data, extracting a harmonic distortion rate, a dielectric loss angle tangent value and a vibration spectrum entropy value of a current waveform in each mode, and generating an operation characteristic matrix; detecting an operation mode switching event, and calculating a characteristic offset between modes; decomposing a degradation characteristic component in the operation characteristic matrix according to a matching degree between an insulation aging stage and current dielectric loss data in a historical fault case library; coupling compensation correction is performed on the degradation characteristic component in combination with the cross influence relationship between the electrical parameters and the mechanical parameters of the equipment; and reversely tracing the abnormal signal source equipment node along the topological structure of the power supply and distribution network based on the corrected degradation characteristic component, and outputting an equipment maintenance sequence.

The invention relates to the technical field of power sources, and provides a power source control system, which comprises a signal source interface, a signal conditioning circuit, a power transmitter, a voltage control circuit and a controller, the signal source interface, the signal conditioning circuit and the power transmitter are connected in sequence, the power transmitter is connected with the voltage control circuit, and the voltage control circuit is connected with the controller; the signal source interface is used for receiving an external signal sent by an external signal source; the signal conditioning circuit is used for performing signal amplification and gain adjustment on an external signal to obtain a power amplification signal; the power transmitter is used for converting the power amplification signal into a radio frequency signal and transmitting the radio frequency signal; the controller is used for controlling the voltage control circuit to adjust the output voltage of the radio frequency signal according to a first voltage value corresponding to the radio frequency signal and a second voltage value when the radio frequency signal is transmitted last time. By adjusting the output voltage of the radio frequency signal, the output voltage is matched with the radio frequency signal, and the signal transmission quality and transmission efficiency are improved.

A method and apparatus are provided, in which a higher layer configuration is received (2002), where the user equipment is configured with two timing reference signals for receiving a common communication having a same set of data from multiple signal sources. A downlink scheduling assignment including downlink control information is received (2004) in a control channel scheduling a physical downlink shared channel, wherein the downlink scheduling assignment comprises an indication of a transmission configuration indicator identifying two transmission configuration indicator states, which each indicate quasi-co-location information of a demodulation reference signal corresponding to the physical downlink shared channel relative to a respective one of the first and the second timing reference signals. The physical downlink shared channel is then received (2006) according to the downlink scheduling assignment including the downlink control information.

The invention provides an arrival wave angle estimation method based on a zero scanning leaky-wave antenna. A rectangular waveguide is selected as a basic structure to design a periodic leaky-wave antenna only working in a-1 harmonic state; designing necessary antenna simulation parameters; a first leaky-wave antenna is designed; adjusting the gap interval p, and designing a second leaky-wave antenna; obtaining pattern functions of the first leaky-wave antenna and the second leaky-wave antenna; proper amplitude and phase parameters are selected for directional diagram synthesis, and a new directional diagram function is obtained; constructing an array guiding matrix suitable for the MUSIC algorithm; signal sources are arranged at different positions, simulation testing is carried out through MATLAB, and the incoming wave angle estimation capability of the zero-point scanning leaky-wave antenna is verified. According to the invention, a feasible technical path is provided for high-precision positioning and tracking application in future 6G mobile communication. The antenna is especially suitable for application in millimeter wave and terahertz frequency bands, such as vehicle-mounted communication, unmanned aerial vehicle platforms, military electronic countermeasures and the like.

The invention relates to a low-noise high-precision pressure measuring circuit which comprises a bridge type sensor, an alternating-current excitation signal source, a phase-sensitive detector, a low-pass filter, a reference signal source and a signal conditioning amplifier. The alternating current excitation signal source modulates a differential voltage signal generated by the bridge type sensor to a high-frequency alternating current excitation signal generated by the alternating current excitation signal source to obtain a high-frequency pressure signal; the high-frequency pressure signal is amplified by the signal conditioning amplifier to form a modulated signal; the phase-sensitive detector performs frequency mixing on the modulated signal and a reference signal generated by a reference signal source to obtain a frequency mixing signal; the frequency mixing signal is filtered by a low-pass filter to form a direct-current voltage signal for pressure measurement; the reference signal generated by the reference signal source and the high-frequency AC excitation signal generated by the AC excitation signal source have the same frequency. According to the circuit, signals are modulated to a high-frequency area with low noise energy to be processed by adopting alternating-current excitation and coherent detection technologies, the signals and noise are effectively separated, and extremely high measurement resolution and precision are achieved.

The invention discloses an image fusion enhancement method for a multi-signal-source liquid crystal splicing screen, and relates to the technical field of large-screen display control, and the method comprises the steps: building a virtual coordinate system taking a physical gap as a reference at an input end, carrying out the decoding, time synchronization and unified mapping of a multi-source heterogeneous signal, converting the multi-source heterogeneous signal into a unified color space, and carrying out the image fusion enhancement of the multi-signal-source liquid crystal splicing screen. The display consistency of different signal sources is ensured; then, a compensation model based on a brightness attenuation function is introduced into the splicing boundary area, edge pixel brightness is subjected to self-adaptive correction, and brightness unevenness caused by physical gaps is relieved; calculating the content complexity based on the row-level gradient magnitude in the fusion screen area, dynamically constructing a content-sensitive fusion weight, and carrying out weighted fusion on the images on the two sides to generate a transition image frame; and through joint output of the transition image frame and the original side image frame, visual seamless connection of the splicing gap area is realized. Therefore, the integral continuity and visual experience of tiled display are effectively improved while the image detail fidelity is ensured.

The invention discloses a fractional frequency division frequency synthesizer with output signal phase synchronization and frequency modulation continuous wave functions, and the basic structure is a charge pump phase-locked loop. Comprising a phase frequency detector, a first charge pump, a second charge pump, a low-pass filter, a voltage-controlled oscillator, a first buffer, a second buffer, a two-frequency divider chain, an IQ undersampling circuit, a local oscillator generator, a programmable multimode frequency divider, a Delta-Sigma modulator (DSM), a first selector, a second selector, a third selector, a tracking phase accumulator, a numerical control oscillator, an accumulation phase difference register and an atan2 logic circuit. The device comprises a main phase control circuit, a phase adjusting circuit, an enabling control circuit, a waveform generator and a serial peripheral interface. The decimal frequency-division frequency synthesizer can be applied to a general-inductance integrated system, ensures that output signals provided by a plurality of decimal frequency-division frequency synthesizers are consistent in phase in a multi-channel radio frequency transceiving system adopting a multi-chip splicing mode, and can also be applied to the general-inductance integrated system as a sensing signal source; and the speed and the distance of an object can be quickly sensed by the high linearity and the quick chirp capability of an output signal. The decimal frequency division frequency synthesizer is applied to a linear frequency modulation continuous wave radar system, initial phase synchronization can be carried out firstly, then frequency continuous modulation is carried out, and measurement errors can be eliminated. In view of functional similarity of partial modules of the synchronous loop and the FMCW loop, such as a phase frequency detector, a charge pump, a voltage-controlled oscillator and the like, the modules can be shared, so that the power consumption and area cost of the system are remarkably reduced.

The invention relates to the technical field of geological exploration, and discloses an exploration method and device for intelligent fusion of multi-geophysical field data. The method comprises the steps of signal source excitation, data acquisition and synchronization, data recording and transmission, preprocessing, feature value extraction, AI model fusion processing, joint inversion, imaging and interpretation and the like. According to the invention, multi-physics field data is synchronously acquired, and a multi-source heterogeneous data intelligent preprocessing and feature extraction method and a multi-physics field data fusion and joint inversion method based on artificial intelligence are provided for data such as earthquake, electromagnetism and gravity in a unified signal analysis framework. Through the steps, the problems of data isomerism, space-time inconsistency, inversion multiplicity and the like in geophysical exploration are solved.