1798 results about "Target signal" patented technology

The invention discloses a multi-base-station AOA cooperative low-altitude target rapid positioning system. The system comprises an AOA measurement base station network, an AOA data preprocessing module, an adaptive weighted intersection positioning module, an extended Kalman filtering state estimation module and a data fusion and system integration module. The system synchronously measures the arrival angle of a target signal through multiple base stations, removes noise in combination with smoothing filtering and an anomaly rejection algorithm, and then solves the initial position of a target by using a self-adaptive weighted intersection algorithm based on measurement quality and geometric distribution. And then, fusing the target motion model and the measurement model by adopting an extended Kalman filtering algorithm to realize dynamic estimation and prediction of the position, the speed and the course. The system can realize high-precision and real-time positioning and continuous tracking of targets such as low-altitude unmanned aerial vehicles, small aircrafts and the like in a complex electromagnetic environment and a sight distance limited scene, and has visual display and regional alarm functions.

The invention relates to the cross technical field of signal processing and artificial intelligence, in particular to a multi-source noise removal method and system based on DAE, and the method comprises the steps: 1, carrying out the data collection and feature extraction of multi-source noise and pure signals; step 2, constructing a de-noising recognition knowledge base based on feature analysis; step 3, constructing a deep denoising auto-encoder model based on a knowledge base; step 4, hierarchical training and optimization guided by a mixed loss function of the deep denoising model; step 5, denoising processing of a target signal and output evaluation based on a discrimination model; according to the invention, noise data in multiple fields such as electromagnetism, remote sensing and biological signals are integrated, a dynamic mixing strategy and a data enhancement technology are adopted, a training set which highly simulates a real environment is constructed, and a unique cross-scene adaptation module can perform adaptive adjustment according to signal characteristics of different application scenes; the problem that a traditional method is poor in scene adaptability is solved.

The invention provides an ultrasonic fingerprint chip and an integral clock generation method and device of the ultrasonic fingerprint chip. Appropriate fingerprint pixel units can be selected from a plurality of fingerprint pixel units to serve as first-class pixel units and second-class pixel units, and the first-class pixel units and the second-class pixel units are respectively connected with a first-class detection circuit and a second-class detection circuit. Wherein a first integrator in the first type of detection circuit is sequentially connected with a first comparator, a time delay regulator, a clock dominant frequency duplicator and a frequency dividing circuit; the frequency dividing circuit is connected with the second type detection circuit; a second integrator in the second type detection circuit is connected with an amplification structure; the amplification structure is also connected with a second comparator; and the second comparator is connected with the time delay regulator in the first-class detection circuit. The circuit can automatically generate and obtain the integral clock signal which is matched with the ultrasonic fingerprint echo signal and is high in precision and good in effect, so that the received ultrasonic fingerprint echo signal is precisely processed, and a target signal with high quality is obtained.

The invention belongs to the technical field of automatic control, and particularly relates to a digital control system for strip coiling equipment, which comprises the following steps of: firstly, comprehensively acquiring strip tension data and state characteristic information by combining a tension sensing assembly and image acquisition equipment, dynamically adjusting a braking torque parameter, and then, acquiring a dynamic control signal by taking the linear speed of a coiling machine as a target signal; the speed of the uncoiling machine and the speed of the traction roller are synchronously aligned through a following strategy, then a taper tension control mode is adopted, the tension value is dynamically adjusted in combination with real-time coiling diameter parameters, the tension stability and the coiling regularity in the coiling process are ensured, and finally the strip deviation problem is detected and processed in real time according to a closed-loop deviation correction mechanism. The equipment control strategy in the strip coiling process is deeply bound with uncoiling control, synchronous coordination, coiling control and a deviation correction core module, and the integrated control capability of multivariable coordination and self-adaptive optimization is achieved, so that the automation and intelligence level of the strip coiling process is effectively improved.

The invention discloses a memory signal integrity enhancing system based on multi-dimensional parameter self-adaption, and belongs to the technical field of signal transmission. The system comprises a multi-dimensional signal acquisition module, a multi-dimensional parameter analysis module, a self-adaptive adjustment module, a memory signal optimization module and a feedback monitoring module, the multi-dimensional signal acquisition module is combined with multi-dimensional parameter analysis, signals of a data bus, an address bus and a control bus are synchronously acquired, a dynamic adjustment strategy is generated according to a model, and the self-adaptive adjustment module and the memory signal optimization module are optimized according to the dynamic adjustment strategy. Different optimization means are adopted for different parameter types, a customized optimization system with one parameter and one scheme is formed, it is ensured that the optimized target signal is optimal in amplitude stability, time sequence accuracy, anti-noise capacity and impedance matching degree, the feedback monitoring module is combined with the multi-dimensional parameter analysis module, and the multi-dimensional parameter analysis module is combined with the feedback monitoring module. And through full-dimension index monitoring and dynamic calibration, the continuous adaptability of the system to the running state of the memory and the long-term stability of signal integrity are guaranteed.

The embodiment of the invention provides a satellite communication and navigation integrated system, which comprises a baseband subsystem and a processor subsystem, the baseband subsystem comprises a front-end processing module, a low-orbit communication module, a navigation processing module and a decoder module, the front-end processing module is configured to preprocess an acquired satellite signal and output a baseband signal, and the decoder module is configured to decode the baseband signal. The baseband signal comprises a navigation signal and a low-orbit communication signal; the navigation processing module is configured to process the navigation signal to obtain a first target signal; the low-orbit communication module is configured to perform signal processing on the low-orbit communication signal to obtain a second target signal; the decoder module is configured to decode the first target signal and the second target signal to obtain navigation data and communication data; and the processor subsystem is configured to perform resource scheduling on the front-end processing module, the navigation processing module, the low-orbit communication module and the decoder module based on the navigation data and the communication data. According to the invention, the integrated requirement of the navigation chip on navigation and communication can be realized.

The invention provides a three-dimensional positioning method and system for a satellite-borne multi-base radar system based on weighted linear iteration, and the method comprises the steps: obtaining radar echo data of a plurality of receivers, carrying out the effective detection of a target, and carrying out the searching of a pitch angle and a space taper angle of a target signal through a two-dimensional adaptive filtering technology, obtaining two-dimensional angle estimation information of the target at different bases and different visual angles; constructing a nonlinear equation set according to two-dimensional angle information and slope distance information of the target under different visual angles, and performing first-order Taylor expansion on the nonlinear equation set to obtain a corresponding linear overdetermined equation set; and forming a precision matrix according to the known measurement precision of the radar system, and carrying out normalization operation and iterative solution on the linear overdetermined equation to obtain the three-dimensional coordinate of the target in the earth-centered earth-fixed coordinate system, thereby obtaining the latitude, longitude and height information of the target, and realizing the high-precision three-dimensional positioning of the multi-static radar system.

The invention relates to the technical field of computer simulation testing, in particular to a dynamic analogue simulation testing method and system for plate type structure service deformation. The technical problem that the structural damage identification precision is insufficient when fixed signal decomposition parameters are used for processing all detection signals is solved. The method comprises the following steps: acquiring a mesoscopic parameter set and a bimodal ultrasonic guided wave original signal set of a to-be-detected plate type structure; based on the mesoscopic parameter set, determining optimization parameters for decomposing the bimodal ultrasonic guided wave original signal set; decomposing the bimodal ultrasonic guided wave original signal set based on the optimized parameters and a signal decomposition algorithm, and determining a target signal set related to structural damage; and performing simulation comparison on the mesoscopic parameter set and the target signal set, and determining the service damage state of the plate type structure. The method is used for plate type structure damage identification scenes.

The embodiment of the invention relates to the technical field of battery manufacturing, and discloses a battery lithium precipitation online detection method, electronic equipment and a storage medium. The method comprises the following steps: acquiring an ultrasonic echo signal in a battery formation process; filtering the ultrasonic echo signal to obtain a target signal; the filtering processing is used for filtering signal components in a preset interference frequency band range generated by bubble disturbance in the formation process, or extracting signal components in a preset harmonic frequency band range of the ultrasonic excitation signals; the preset interference frequency band range and the preset harmonic frequency band range do not have an overlapping range; based on the target signal, extracting a time domain feature vector, a frequency domain feature vector and an attenuation coefficient feature vector to construct a feature matrix; and inputting the characteristic matrix into a lithium precipitation determination model, and outputting a lithium precipitation determination result. The problems that in the prior art, the lithium precipitation phenomenon in the formation process cannot be monitored in real time, the detection signal-to-noise ratio is low due to bubble disturbance, and lithium precipitation is difficult to accurately judge through single parameter detection are solved.

The invention provides a non-contact pressure and fatigue state identification method based on double-indication joint reasoning, and relates to the field of psychological and physiological analysis, and the method comprises the steps: collecting a face visible light video and a first EDA signal; extracting an rPPG signal and a first facial behavior indication sequence; processing the signal amplitudes of the first EDA signal and the first facial behavior indication sequence to obtain a target EDA signal and a target behavior indication sequence; inputting the rPPG signal and the target behavior indication sequence into a fatigue detection model to obtain fatigue information; inputting the rPPG signal and the target EDA signal into a psychological stress detection model to obtain psychological stress information; and synchronously outputting and displaying the fatigue information and the psychological pressure information based on a preset signal waveform comparison display area. The psychological stress state and the fatigue state are analyzed at the same time, double indications are used for comprehensive consideration, cross-scene state fluctuation is identified, and the precision and efficiency of psychological stress state and fatigue state analysis can be effectively 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 discloses a narrow pulse suppression method and device for dynamic adjustment of dead time, a medium and a controller, and the method comprises the steps: presetting the dead time of M periods in the future according to the real-time state of a motor and the dead time and current change rate of the first N periods, and outputting a working condition label at the same time, N and M being positive integers; determining target dead zone time Td according to the working condition label and the dead zone time of the M periods in the future; determining a dead zone time ratio Dd according to the target dead zone time Td, constructing an interval section of a PWM signal according to the dead zone time ratio Dd and a narrow pulse time ratio Dp, and constructing an upper bridge arm duty ratio function Dt and a lower bridge arm duty ratio function Db corresponding to each interval section according to the dead zone time ratio Dd and a duty ratio instruction Dm of the PWM signal; according to the interval section where the duty ratio instruction Dm of the PWM signal is located, a duty ratio function of the corresponding interval section is called, and a target PWM signal is output.

The invention discloses a spectral interference system resolution improving method and system, and the method comprises the steps: building an ISE-Net end-to-end deep neural network model, enabling the convolution kernel size of an efficient channel attention module of the ISE-Net end-to-end deep neural network model to be adaptively determined according to the number of input channels, and constructing a mapping relation between narrowband and broadband interference signals; and generating an ideal narrowband signal and a double-bandwidth target signal according to a spectral interference physical formula, defining a loss function by minimizing deviation between model output and the target signal, updating parameters and dynamically adjusting a learning rate by using an AdamW optimizer until model loss is converged, and completing data generation and training. An input narrowband signal horizontal axis is converted to a corresponding frequency domain axis, and is subjected to time shifting and intensity scaling preprocessing to adapt to the model. A signal processing flow suitable for a single / multi-layer structure is constructed, a bandwidth expansion signal is obtained through decomposition, expansion and reconstruction, and the resolution of a spectrum interference system is improved. The method has the advantages of high calculation efficiency, high generalization and flexible deployment.

The invention discloses a blind signal source separation method based on a multi-resolution attention separation network, and belongs to the technical field of signal processing. The method comprises the following steps of signal preprocessing, multi-scale feature extraction, attention module training, multi-resolution feature fusion, signal source recognition model training, model performance real-time monitoring and multi-scene adaptation optimization, and microcosmic and macroscopic features of signals are effectively captured through a multi-scale channel feature coding network. The adaptability of the model to non-stationary signals and complex structure signals is enhanced, the separation precision is improved, the attention mechanism can dynamically adjust feature weights, highlight target signal features, suppress background noise and remarkably improve the signal separation quality, meanwhile, calculation resource allocation is optimized, the model reasoning time is shortened, and the method is suitable for large-scale popularization and application. The MRAS-Net adopts a classification-oriented consistency synthesis strategy to ensure that the synthesized virtual signal features and the real signal features are highly consistent in classification tasks, and the generalization ability and the result interpretation of the model are enhanced.

The invention discloses a radar moving target parameter preprocessing method and system based on classification, and relates to the technical field of radar signal processing. The method comprises the following steps: constructing a signal model for a radar moving target needing to be identified and processed in a region of interest for simulation, and establishing a moving target signal data set; classifying according to the motion condition of the moving target in the moving target signal data set, preprocessing the moving target signal according to a classification result, and obtaining feature information in a corresponding category; taking the feature information as sample data, and training a classification model through the sample data to obtain a trained classification model; and inputting a to-be-processed moving target signal into the trained classification model for classification and identification, and obtaining a corresponding classification test result. The method can effectively reduce the calculation amount, improve the parameter estimation speed and save calculation resources.

The invention discloses an oil and gas field integrated dynamic simulation construction method and system based on artificial intelligence, and the method comprises the steps: S1, carrying out the space-time alignment and standardized cleaning of a multi-source heterogeneous data signal, and generating a fusion data signal with unified space-time; s2, a physical information embedded deep learning model architecture is constructed, the architecture receives the fusion data signal, and a mixed training target signal fusing data driving and mechanism driving is generated; s3, training the deep learning model by using a fusion data signal of a historical time sequence, and finally obtaining a convergent intelligent agent model; and S4, feeding the current oil and gas reservoir state parameters and the production control parameters into the intelligent agent model as input signals, and directly outputting a dynamic prediction signal. The oil and gas field integrated dynamic simulation construction method and system based on artificial intelligence can solve the problem that traditional oil and gas field numerical simulation calculation is low in efficiency.

The invention relates to a same-frequency signal separation method and device based on an attention mechanism, equipment and a medium, and belongs to the technical field of wireless communication. The method comprises the following steps: acquiring a mixed signal in a same-time and same-frequency interference scene, and simulating to generate a plurality of types of modulation signals as priori pure signals; inputting all the priori pure signals into a priori signal feature extraction network trained based on an Arcfu loss function to obtain embedding centers of various modulation signals as priori information; a target signal separation network is constructed and trained, in the network, mixed signal features are extracted according to a mixed signal encoder, modulation features are coded and extracted from an embedding center according to a modulation feature coding module, bidirectional cross attention calculation is performed on the mixed signal features and the modulation features according to a cross attention module, and the target signal separation network is obtained. And a fusion feature focused on the target signal is obtained and decoded, and a target estimation signal is reconstructed and output. According to the method, accurate separation of the target signals in the same-time and same-frequency interference scene can be realized.

The invention relates to the technical field of vision measurement, and discloses a pipeline deformation vision measurement method and system based on a detection robot, and the method comprises the steps: collecting and preprocessing an image of the inner wall of a pipeline through an image sensor carried by the detection robot, and obtaining a preprocessed pipeline image; performing defect perception mask processing and periodic convolutional coding to obtain a semantic potential vector; a target signal-to-noise ratio is calculated according to a UWB transceiver in the detection robot for transmission; recovering the time domain pulse signal received by the ground receiving end to obtain a semantic potential vector, and reconstructing to obtain a reconstructed pipeline image; according to the method, the pipeline contour point set of the reconstructed pipeline image is extracted, ellipse fitting is carried out on the pipeline contour point set, the continuous pipeline deformation curved surface is constructed, discontinuous artifacts at the splicing position of the pipeline image are eliminated, the image semantic integrity is guaranteed, high-fidelity pipeline image reconstruction is achieved, and then accurate measurement of pipeline deformation is achieved.

The invention provides a PWM signal generation circuit and a control device. The PWM signal generation circuit comprises a control module, a delay chain module and an edge detection module, wherein the delay chain module and the edge detection module are electrically connected with the control module; the edge detection module is used for receiving an original PWM signal output by the PWM system, detecting the edge of the original PWM signal based on an edge detection instruction, generating an edge indication signal and sending the edge indication signal to the delay chain module; the delay chain module comprises a plurality of delay units and is used for delaying the edge of the original PWM signal by target delay time to generate a target PWM signal; according to the invention, the delay operation is carried out on the original PWM signal at the specified edge through the delay chain module, the target PWM signal with the resolution higher than that of the original PWM signal is obtained, and the high-resolution PWM signal is generated by using the low-frequency clock of the PWM system on the premise of not changing the system work clock period of the PWM system.

The invention discloses a starter carbon brush wear real-time monitoring system and method, and relates to the technical field of starter monitoring, and the method comprises the following steps: carrying out the environment light field analysis of the contact surface of a carbon brush and a commutator in a starter, building a three-dimensional reference data model based on the reflection intensity, the incident angle and the polarization state, a high-reflection area is positioned on the basis of the model, and an interference data list containing high-reflection interference information is generated. According to the invention, by constructing the three-dimensional reference model and combining the modulation light source, the phase-locked window and the cross polarization structure, accurate separation of a target signal and environmental interference is realized; and the wear confidence index is generated through synchronous demodulation, and adaptive closed-loop control is formed, so that the monitoring precision and the system robustness are improved, and the reliability and the maintenance efficiency of the starter are remarkably enhanced.

The invention discloses an echo signal processing method based on a multi-order FRFT domain feature fusion sparse dictionary, and belongs to the technical field of underwater acoustic signal processing and target detection, and the method comprises the steps: screening out a plurality of differential fractional orders through employing the differential features of a target echo and a reverberation signal in different fractional order transform domains; constructing a sparse sub-dictionary based on each differential fractional order, and training a fusion weight of each sub-dictionary through an adaptive gradient optimization strategy; and finally, target signal extraction and strong reverberation suppression are realized through weighted fusion and sparse reconstruction. According to the method, the accuracy and stability of a sparse reconstruction result can be improved, the signal-to-mixing ratio of signals can be effectively improved, target echoes and strong reverberation are further distinguished, good robustness and engineering application value are achieved, and an effective technical means is provided for underwater weak signal detection and strong interference.

The invention provides a communication method, terminal equipment and network equipment. The method comprises: a terminal device receiving first information sent by a network device, the first information being used for triggering receiving or sending of a target signal, the target signal comprising one or more of the following: an uplink reference signal; a downlink reference signal; a CSI; wherein the first information is sent by the network equipment in an uplink random access process; or the first information is sent by the network equipment in the process that the auxiliary cell is activated or quits the dormant state. The first information used for triggering the uplink reference signal, the downlink reference signal or the CSI is transmitted in advance to an uplink random access process, an auxiliary cell activation process or an auxiliary cell quit a dormant state, so that the signals are transmitted as early as possible, the transmission delay of the signals is reduced, and the transmission efficiency is improved. And the time delay from the state switching of the terminal equipment to the channel detection is shortened, so that the network decision is facilitated.

The invention provides a current sensor. According to the current sensor, four identical magnetic sensing parts are arranged at corresponding positions on the upper side and the lower side of a current guide row, the sensing centers of the four magnetic sensing parts are symmetrical about the current guide row in pairs, and the sensing direction is parallel or antiparallel to the row width direction of the current guide row. The current guide bar is a flat metal conductor so as to counteract the influence of current on any two magnetic sensitive parts symmetrical about the current guide bar. In cooperation with the hardware setting, target signals capable of representing the magnitude, the phase and the frequency of the current in the diversion bar are obtained through corresponding sensing signal processing, meanwhile, the influence of constant interference fields in all directions is eliminated, and three-dimensional interference resistance is achieved. In addition, according to the current sensor provided by the invention, the four magnetic sensing parts and the signal conditioning unit are arranged on the PCBs stacked on the upper side and the lower side of the diversion row, so that the current sensor is compact in structure and small in size.

The invention discloses a dynamic filtering and beamforming method for improving the anti-interference capability of a secondary radar. The method comprises the following steps: initializing original data; periodically monitoring the interference congestion degree of the downlink response signal of the secondary radar system in the current radio environment, and judging the interference intensity; dynamically adjusting the transmitting power and the PRF of an uplink interrogation signal of the secondary radar system; notifying the air target responder to reduce the sending rate and the transmitting power of a downlink response signal through the downlink control instruction; the general orientation of the interference source is determined in combination with external monitoring information, adaptive beamforming is performed based on the array antenna, and null is formed in the general direction of the interference source to realize interference suppression of a spatial domain; and performing dynamic filtering processing on the receiving signal after beam forming processing, extracting an effective target response signal sequence, and reconstructing the effective target response signal sequence into complete target response information data according to a predetermined protocol format. According to the invention, the accuracy and reliability of target signal detection and the anti-interference performance of the system are improved.

The invention particularly relates to an airborne SAR distance compressed domain sea clutter suppression method based on generalized gamma distribution, and the method comprises the steps: carrying out the range pulse compression processing of an echo signal received by an airborne SAR, and extracting a pure sea clutter sample from compressed data through employing a non-local sampling strategy; then, a generalized gamma distribution model is quickly fitted for the clutter samples by using an analytical method based on a second type logarithmic cumulant, and a self-adaptive detection threshold is solved through an incomplete gamma function based on the model and a set false alarm probability. And finally, according to the threshold value, carrying out judgment and filtering on distance compressed domain data, suppressing clutter regions lower than the threshold value, and meanwhile, retaining potential target signals, thereby realizing efficient and steady clutter suppression under complex sea conditions.

The invention relates to the technical field of data processing and intelligent environment control, in particular to a sleep environment feedback control data processing method based on cognitive behavior therapy logic, which comprises the following steps: a reference model construction step: acquiring a non-contact multi-mode time sequence signal, and reconstructing a reference signal balance curve to construct a target signal manifold model; a simulation flow generation step of converting the preset interference characteristics into signal modulation operators and injecting the signal modulation operators into the model to generate a simulation signal flow; a double-track difference calculation step: executing double-track difference operation to respectively extract residual features representing system deviation and theoretical interference; a similarity judgment and control step: calculating the topological similarity of the residual features in a time-frequency domain, judging a deviation dominant type, generating a corresponding control instruction, and driving an execution mechanism to act; according to the method, psychological anxiety and environmental discomfort are effectively distinguished by using a double-track differential mechanism, and accurate attribution analysis of sleep interference sources is realized.

The invention discloses an electromagnetic pulse coupling signal separation method based on optimized variational mode decomposition, and belongs to the field of signal processing. The method comprises the following steps: carrying out injection test on an engine rotating speed control system shielding wire harness, and constructing an electromagnetic pulse coupling signal data set; a population initialization process of a parrot algorithm is improved by adopting spatial pyramid matching chaotic mapping, population diversity is improved by utilizing uniform ergodicity and initial value sensitivity of a chaotic sequence, and premature convergence is avoided; a mirror reflection learning strategy is introduced to improve the optimization precision and convergence speed of the parrot algorithm; optimization is carried out by using input parameters of improved parrot optimization variational mode decomposition, and mode decomposition is carried out on electromagnetic pulse coupling signals of a rotating speed control system; and calculating a kurtosis factor of each intrinsic mode function, and selecting a reconstruction target signal of the intrinsic mode function with the minimum kurtosis factor. According to the method, efficient and accurate electromagnetic pulse coupling signal separation can be realized, and the stability and reliability of the system in a strong electromagnetic interference environment are improved.

The invention discloses a method and system for detecting the insulation state of power transmission and transformation equipment based on photoelectric sensing, and relates to the technical field of insulation state detection, and the method comprises the steps: continuously monitoring a baseline optical signal and a baseline electrical signal of the power transmission and transformation equipment through a photoelectric sensor which is arranged in a wide area; starting a targeted signal acquisition mode, and obtaining a high-precision optical signal and a high-precision electrical signal of the target area; performing logic correlation analysis, evaluating the matching degree of the optical features and the electrical features, and generating a fusion diagnosis result and a confidence level thereof; and matching and determining an insulation state detection result from a preset equipment aging state mapping table. The technical problems that in the prior art, power transmission and transformation equipment insulation state detection is insufficient in accuracy, low in efficiency and difficult to comprehensively and accurately judge the equipment insulation state are solved, and the technical effects of achieving accurate and efficient detection of the power transmission and transformation equipment insulation state and improving the detection reliability are achieved.

The invention relates to the technical field of chips, and provides a power-on control method and system, a chip, equipment and a storage medium, and the method comprises the steps: controlling a first power domain to be powered on, maintaining a second power domain to be in a power-off state, and driving a signal processing circuit to process an external input signal and output a target signal, the first power domain supplies power to the signal processing circuit, and the second power domain supplies power to a post-stage logic circuit; after determining that the target signal is in a stable state, controlling the second power domain to be powered on so as to start the post-stage logic circuit; wherein the started post-stage logic circuit carries out sampling processing on the target signal in a stable state. According to the invention, power domain division is carried out on the signal processing circuit and the post-stage logic circuit and time-sharing power-on of the signal processing circuit and the post-stage logic circuit is controlled, so that stable and effective signals can be always sampled by the post-stage logic circuit when the post-stage logic circuit is started, and the power-on reliability of a chip and the stability of a system are improved.

The invention relates to the technical field of echo signal analysis, and discloses a radar radiation source signal identification method based on multi-task learning under physical feature constraint, which comprises the following steps of: 1, establishing a data set by a two-dimensional tensor and a physical feature tag; 2, the identification model comprises a feature extraction network and a multi-task learning network, and the multi-task learning network comprises a frame prediction branch, a classification branch, a parameter regression branch and a frequency spectrum prediction branch; 3, training the recognition model to obtain a trained recognition model; and step 4, inputting a two-dimensional tensor to be recognized into the trained recognition model, and outputting predicted physical characteristics, probability distribution of signal categories, predicted values of parameters and a remodeled two-dimensional STFT spectrogram. Physical priori knowledge and multi-task cooperative constraint are introduced, the physical nature of radar signals can be accurately captured, the interpretability and anti-noise capability of the model are improved, the expression capability of the model for key features is enhanced, and the method is suitable for scenes with sparse feature distribution or weak target signals.