459 results about "Oversampling" patented technology

The invention discloses a sampling implementation method and system suitable for motor protection quick response, belongs to the technical field of motor protection, and can increase the sampling frequency and improve the quick response of motor fault protection. Comprising the steps that motor phase current and bus voltage are collected, after anti-aliasing filtering is conducted, parallel sampling is conducted through a main ADC module and a redundant ADC module which are independently configured, and the following operations are synchronously executed based on a double-buffer-area framework: in a first buffer area, a compensation coefficient updating period is dynamically adjusted, and convergence is restrained; in the second buffer area, generating a voltage gradient prediction sequence, and compensating data abrupt change; when the harmonic frequency spectrum amplitude or the voltage gradient prediction sequence exceeds the limit, an oversampling mode is triggered, a redundant ADC module is allocated to load a multi-order digital filter, and an independent hardware acceleration unit is started to process harmonic compensation and gradient prediction in parallel; and generating a dynamic safety envelope, and if the gradient extreme value in the preset continuous window breaks through the safety envelope, generating an overvoltage fault signal.

An electronic interface device is configured for use with associated optics for employing coded light for illuminating a liquid, gaseous, or other analyte or target, such as for measuring or determining a composition or other property of the analyte or target. The arrangement can help enable a far higher level of performance, such as for spectral analysis, imaging, or both. A shared common clock on both the illumination and receive sides of the system can be included, such as together with one or more of reference detection, per-channel wavelength-dependent modulation, multiple concurrent feedback loops at different levels, orthogonal and circulant codes, phase-scrambling to better utilize ADC dynamic range, oversampling, and other signal processing can be provided.

The invention discloses a power transmission line fault reason identification method based on experience guidance, and belongs to the technical field of power transmission line fault diagnosis and artificial intelligence deep learning. Expanding the unbalanced sample through a synthetic minority class oversampling technology; implicit features in fault transient waveforms are fully extracted through a long short-term memory neural network, and a nonlinear mapping relation between fault recording and fault reasons is preliminarily established; and the engineering experience of the operation and maintenance personnel is sorted, and the expert knowledge base is combined and the expert experience is utilized to guide model training and output, so that an expert experience-embedded power transmission line fault identification model is formed. And storing the model and applying the model to an online fault identification task. The unbalanced samples are expanded through an SMOTE method, so that the influence of the sample imbalance problem on the model performance is relieved; and an expert knowledge base is introduced into a model decision process, so that the accuracy and interpretability of the fault identification model are improved, and operation and maintenance personnel can easily understand an internal working mechanism of the model.

The invention provides a multiphase filtering sampling method suitable for satellite communication. The method comprises the following steps: receiving an original modulation signal and converting the original modulation signal into a digital signal sequence; extracting a signal feature vector and generating a processing configuration parameter; performing orthogonal decomposition to generate I / Q signal pairs and performing oversampling; initializing a multi-phase filter and generating an optimal filter coefficient; carrying out phase calibration and filtering; determining an interpolation coefficient and executing multi-stage integer interpolation and mixed precision fractional interpolation; configuring a dynamic cache system; phase reordering and synthesis are executed; spectral analysis is performed and optimization parameters are generated. According to the invention, high-precision signal processing is realized, the adaptive capability and the efficient resource utilization characteristic are realized, and the performance of a satellite communication system is remarkably improved.

Disclosed in the present invention are an improved oversampling-based power transmission line fault classification system and method. The method of the present invention comprises: first, by using historical fault information of State Grid as a database, obtaining a plurality of sub-datasets by means of division based on fault types, each sub-dataset consisting of transient current traveling waves at power transmission line fault moments; then, using a K-means method to perform clustering operation on minority classes of a fault dataset, and using BSMOTE to perform oversampling, so as to achieve balancing of various classes, thus forming a balanced dataset; then, calculating time domain and frequency domain features of transient current traveling waves in the balanced dataset, so as to form a feature dataset; finally, on the basis of CNN and SVM deep learning algorithms, establishing a classification model and training same by using the feature dataset, so as to obtain a trained fault classification model; and using the trained fault classification model to classify and identify faults. The method is highly accurate and effective, and can effectively extract fault feature quantities and quickly and accurately classify faults.

The invention provides a VCO digital circuit control method and system with temperature compensation, and relates to the technical field of circuit control, and the method comprises the steps: obtaining VCO output frequency and real-time temperature, and calculating an initial frequency deviation; correcting the frequency deviation based on the temperature compensation coefficient, and generating a temperature-frequency deviation characteristic curve; an optimal compensation factor is determined through Monte Carlo sampling; calculating a compensation parameter adaptive weight by using Bayesian iteration, and dynamically adjusting a compensation factor; and a control signal is generated through the digital integrator to realize frequency calibration. According to the invention, the high-precision frequency stability of the VCO under the temperature change condition is realized, and the circuit reliability is improved.

The invention discloses a data transmission method, a server system, equipment and a medium, and relates to the technical field of data transmission, and the method comprises the steps: determining a sampling pulse corresponding to first target data, obtaining a plurality of sampling pulses in a segment through the segmentation processing of the sampling pulse, and taking the plurality of sampling pulses as target sampling pulses, so as to improve the accuracy of collecting effective data. According to the method, interference signals caused by corresponding jitter instability conditions under serial port hot plugging are avoided, and the target sampling pulses obtained after segmentation processing are used for keeping data stability and avoiding high possibility of doping of the interference signals at the same time. And determining the second target data based on the target sampling pulse, and improving the anti-interference performance of the second target data under the bit. The technical problems that normal serial port use cannot be maintained when jitter interference occurs in the hot plug process, and even the whole machine crashes can be solved, and the technical effect of improving the anti-interference performance of data is achieved.

The invention discloses a TIADC mismatch calibration method and circuit based on a frequency domain cross correlation coefficient. According to the method, after ADC output of each sub-channel is converted to a frequency domain, a cross correlation coefficient between adjacent channels is solved, so that a sampling moment mismatch parameter is estimated and obtained, then a calibration module is controlled to carry out data calibration through the sampling moment mismatch parameter, and sampling moment mismatch compensation is finally completed through repeated iteration. And RLT design is carried out on the FPGA, so that a mismatch calibration circuit is obtained. Compared with the prior art, the method is suitable for a multi-channel TIADC system, an auxiliary channel is not needed, and calibration can be completed only through fewer sampling points and first-order differential compensation. A simulation result shows that under the input of any signal, the overall performance is superior to that of an existing sampling moment mismatch calibration algorithm.

The invention belongs to the technical field of cognitive radio, and particularly relates to an open set modulation identification method based on time-frequency domain feature learning and fusion. The method comprises the following steps of: receiving a signal by adopting a receiving antenna through electromagnetic spectrum monitoring equipment, capturing a space electromagnetic radiation signal, converting the space electromagnetic radiation signal into an electric signal, amplifying the signal through a low-noise amplifier, performing frequency conversion and filtering through an analog receiver, and converting the received signal into an intermediate-frequency signal. Then, the signal is digitalized through AD sampling, and the intermediate frequency signal is converted into a baseband complex signal through frequency mixing and digital filtering in a digital receiver. Then performing time domain characterization calculation and frequency domain characterization calculation on the signal sampling data to form a plurality of time domain characterization vectors and a plurality of frequency domain characterization vectors; and then the vectors are sent to a trained deep neural network model, reasoning is carried out by using the network model, a reasoning result is post-processed, and a signal modulation identification result is finally obtained. According to the invention, the recognition accuracy of unknown signals is improved.

The invention discloses a low-complexity MSK coded modulation system phase synchronization receiving system and method, and relates to the technical field of continuous phase modulation. On one hand, an original message is coded and modulated by constructing a pre-coding mode, a receiving end realizes optimal sampling point extraction at the minimum intersymbol crosstalk moment after phase decoupling frequency conversion processing, MSK is converted into BPSK-like modulation, oversampling processing is not needed, modulation phase components of a receiving synchronization section can be offset, and the modulation efficiency of the receiving synchronization section is improved; therefore, accurate estimation of Doppler phase and frequency is realized, and the anti-Doppler capability is improved. On the other hand, coherent demodulation soft information is directly output after the real part of the signal subjected to Doppler frequency offset and phase offset compensation is obtained, the complexity of the demodulation algorithm is low, the performance of the demodulation algorithm is equivalent to that of BPSK, the demodulation algorithm is remarkably superior to that of an MSK optimal demodulation receiver in a low signal-to-noise ratio region, and the demodulation algorithm is particularly suitable for a bit interleaving coding modulation system combined with channel coding and has a wide application prospect. And reliable transmission under a low signal-to-noise ratio can be realized.

The invention discloses a fast-locking low-jitter sub-sampling phase-locked loop structure. The sub-sampling phase-locked loop comprises a sub-sampling Bang-Bang phase discrimination circuit, a self-adaptive variable step size digital filter circuit, a delta sigma digital-to-analog conversion circuit and an oscillator circuit. The sub-sampling Bang-Bang phase discrimination circuit generates a phase discrimination output digital control signal according to an input reference signal and a feedback oscillator signal phase error, the adaptive variable step size digital filter circuit adaptively adjusts a filtering gain according to the phase discrimination output digital control signal, and the output of the filter circuit realizes digital-analog conversion after oversampling modulation. And the output analog signal controls the voltage-controlled oscillator to realize rapid low-jitter phase locking of the output and the reference signal.

The invention relates to the technical field of digital playing equipment, and provides a lossless control method for the volume of a digital player and the digital player. The method comprises the following steps of: after receiving a target volume parameter, executing dynamic multiplying power oversampling and high-order noise shaping on an input digital audio signal, and injecting preset jitter to suppress in-band quantization distortion so as to generate an optimized digital audio stream; meanwhile, a high-resolution digital reference current control instruction corresponding to the target volume is independently generated, output of a reference current source is adjusted according to the high-resolution digital reference current control instruction, and a high-precision differential current signal is obtained by combining nonlinearity, temperature excursion and quantization errors of a closed-loop feedback compensation device through a multi-bit current segmentation network; performing bias stabilization processing on the signal, and converting the signal into a differential voltage signal for suppressing common-mode noise through a precision differential resistance network; and finally, low-distortion differential analog audio signals capable of directly driving a load are output through low-distortion gain, impedance conversion and power driving, so that low-distortion, high-signal-to-noise-ratio and wide-dynamic-range output in a full-volume range is realized.

The invention relates to a current-to-voltage acquisition circuit for suppressing common-mode interference. The current-to-voltage acquisition circuit comprises a current amplification module, a current transformer, a high-pass filter, an interference acquisition module, an interference analysis module and a suppression execution module, by means of the design, the common-mode interference suppression effect is better than that of a traditional sampling circuit, errors caused by sampling signal deviation generated by interference are avoided to the maximum degree, the common-mode interference suppression circuit is particularly suitable for interference scenes or occasions where interference sources change, the changed interference sources can be calculated in a sampling statistics mode, and the interference source suppression effect is improved. Therefore, the suppression ratio of common-mode suppression is adjusted, and the environment condition is dynamically tracked to obtain an accurate sampling effect.

The invention relates to the technical field of pulse acquisition, in particular to a high-speed ADC (Analog to Digital Converter) and FPGA (Field Programmable Gate Array) coordinated extremely-narrow pulse signal acquisition system, which comprises a phase identification monitoring module, a phase lock reference updating module, a sampling permission control module, a prohibition feedback identification module and a synchronous trigger adjustment module. According to the method, a beat tolerance judgment mechanism is introduced, hyper-bound phase deviation trend statistics and frequency vector extraction are combined, beat correction is carried out by utilizing a directional hopping cumulant and a period adjustment amount, a sampling permission judgment and keeping window alignment mechanism is introduced in a multi-frame period, and a two-way judgment means of a sampling starting trigger value is adopted, so that the beat tolerance of the multi-frame period is judged. And meanwhile, centralized extraction and frequency directivity statistics are carried out on the hopping direction in the sampling prohibition time sequence, the synchronous mismatch trend is distinguished, and the initial beat position is adjusted, so that the time domain characteristics of the narrow pulse waveform are kept continuous, the edge response is prevented from deviation, the trigger structure is stable and reliable, and the overall sampling judgment is more accurate and efficient.

The invention relates to the technical field of flow metering, in particular to an anti-flow-fluctuation metering method of a multichannel ultrasonic flowmeter. The method comprises the following steps: dividing the measurement of each sound channel into a plurality of measurement periods, calculating the weight proportion of each sound channel in the overall measurement based on a multi-factor weighting model, and introducing a real-time compensation mechanism of a fluid dynamic working condition to correct the weight proportion; when the fluid passes through the measuring pipe section, sound wave transmitting and receiving signals are sampled, the transmission time of sound waves in the fluid is calculated through sampled data, and the effective transmission time of each sound channel is recorded; and judging the effectiveness of sound channel sampling based on the sampled data and the effective transmission time of the sound channel, and establishing a multi-sound channel weighted average flow rate model. According to the invention, by introducing a multi-factor weighting model and a fluid dynamic working condition real-time compensation mechanism, the weight in the whole measurement can be dynamically adjusted according to the signal quality of each sound channel.

The invention discloses a single-channel double-gain high-precision measurement method, system and device and a medium, and the method comprises the steps: setting an oversampling rate, and achieving a signal-to-noise ratio of a preset high value when an analog input signal is oversampled based on the oversampling rate; correlation mapping exists among the oversampling rate, the signal sampling frequency and the Nyquist frequency; combining the two analog-to-digital converter channels to sample the same analog input signal; the channels of the two analog-to-digital converters are provided with programming gain amplifiers which are configured to receive input signals with different numerical values and expand the signal capture range of the analog-to-digital converters by using different gain levels; when signal sampling is executed, signal sampling operation is carried out based on the oversampling rate and the signal input ranges of different numerical values; according to the invention, the nominal condition and the fault condition of the signal can be measured at the same time, a wider signal measurement range is provided, and the signal analysis precision is improved.

The invention belongs to the technical field of wireless communication, and particularly discloses a high-dynamic stable tracking method for non-spread-spectrum continuous wave signals. The method comprises the following steps: obtaining a digital signal based on ADC sampling, and carrying out digital frequency conversion on all sampling points of a current symbol according to a current estimated frequency result to obtain a digital baseband signal; a digital baseband signal under 4 times of oversampling is obtained through multi-stage downsampling, matched filtering processing is carried out on the digital baseband signal under 4 times of oversampling, and an output result of a preset position in matched filtering output is determined as an optimal sampling point to serve as output of a tracking loop; and performing timing error estimation according to an output result of the matched filtering, adjusting the sampling deviation of the next section of data by using a timing error estimation result, solving a phase discrimination value according to the optimal sampling point, and adjusting the digital frequency conversion of the next section of data by using the phase discrimination value. According to the scheme, the technical problem that the non-spread-spectrum continuous wave signal cannot be continuously and stably tracked in a high-dynamic scene is solved.

A circuit and method for data recovery comprises clock generation, data reception, data oversampling, and data selection circuits; wherein, clock generation circuits are used to output data reception clock signals and data processing clock signals; data reception circuits are used to receive original transmission data from the data transmitter in accordance with the data reception clock signals, and transmit data based on its output; data oversampling circuits are used for multiple oversampling of at least one bit of transmission data corresponding to at least one data processing cycle according to the data processing clock signal and outputting corresponding parallel sample data; data selection circuits are used for transition detection on the corresponding parallel sample data for each data processing cycle and selecting sample data from the corresponding parallel sample data to output based on the transition detection results. The embodiments of the present application use a simple structure to implement data recovery, reducing layout area and circuit power consumption.

The invention discloses a power quality composite disturbance detection classification and time positioning method based on MS-TCN + +. According to the method, composite disturbance category codes are designed for sampling points, an electric energy quality identification model comprising a prediction generation stage and a plurality of refining stages is constructed on the basis of MS-TCN + +, and multi-time-scale disturbance signal features are extracted by using double expansion layers in the prediction generation stage. And smooth loss is added in model training to avoid sudden change of categories of sampling points in a time sequence, and finally category identification and time positioning of disturbance signals are completed through a classification result of the sampling points, so that powerful support is provided for treatment of power quality disturbance.

A rotating machine rotating speed self-adaptive estimation method based on harmonic energy and a maximum proportion criterion comprises the steps that firstly, multi-channel vibration signals are obtained through sampling, a channel signal with the maximum effective value is obtained to serve as a target signal for rotating speed estimation, and the target signal is pre-processed in a self-adaptive mode according to the signal type; secondly, Fourier transform is carried out on the preprocessed signals, a maximum value method is adopted to search for main spectrum peaks and frequency positions of the main spectrum peaks in an amplitude spectrum, and harmonic energy and proportions of all frequencies are calculated; and finally, searching the frequency corresponding to the maximum harmonic energy and proportion, performing frequency correction to obtain an accurate rotating frequency, and performing conversion calculation to obtain the rotating speed. The method effectively overcomes the defect that a traditional rotating speed estimation method is easily influenced by the power frequency amplitude, achieves accurate measurement of the steady-state rotating speed of equipment in a rotating speed sensor-free mode, can be suitable for displacement, speed, acceleration and other vibration sensors, and has the advantages of being simple in logic, wide in application range, high in estimation precision and the like.

A method for motor voltage reconstruction by Analog to Digital Converter (ADC) oversampling and averaging includes measuring a first phase voltage with an ADC, the first phase voltage proportional to a first duty cycle of a first Pulse Width Modulation (PWM) signal. A second phase voltage is measured with the ADC, the second phase voltage proportional to a second duty cycle of a second PWM signal, wherein the first PWM signal and the second PWM signal control consecutive phases of a three-phase motor. A third duty cycle of a third PWM signal of the three-phase motor is reconstructing from the first phase voltage and the second phase voltage.

The invention relates to a hybrid beam forming anti-interference method for a millimeter wave large-scale array, and the method comprises the steps: S1, enabling a far-field signal to enter a linear antenna array which is uniformly distributed, and enabling the linear antenna array to form an analog receiving matrix through the received snapshot data; s2, the linear antenna array is divided into sub-arrays, each sub-array reconstructs a covariance matrix of interference and noise by using the data received in the step S1, and then an analog beam forming weight coefficient is obtained; s3, the analog beam forming weight coefficient in the S2 is quantized, the analog beam forming weight coefficient is quantized into a discrete value according to the precision of a phase shifter, and analog beam forming output is obtained according to the discrete value; and S4, acquiring an analog beam forming output signal at a digital port through an analog-to-digital converter, solving a digital beam forming weight through a sampling covariance matrix inversion algorithm, and obtaining a final output. Compared with the prior art, the method has the advantages of effective and remarkable anti-interference performance and the like.

The invention discloses a multi-scale epileptic seizure cross-object detection method based on power spectral density. The method comprises the following steps: acquiring multi-channel electroencephalogram signal data of an epileptic and preprocessing the multi-channel electroencephalogram signal data; carrying out regularization processing on the preprocessed electroencephalogram signal data; constructing self-adaptive power spectrum density; according to the power spectral density characteristics, balancing the electroencephalogram signal data by using an SMOTE oversampling method to form a balanced data set; building and training a multi-scale space-time deep convolutional network model; dividing data in the balanced data set into a training set and a verification set, and inputting the training data and the verification data into the multi-scale space-time deep convolutional network model for training. According to the method, the dependence on a large amount of marked data can be reduced, the complexity and the calculation cost of the model are reduced, and meanwhile, the applicability of the model among different patients is improved.

The invention relates to the technical field of electromagnetic valve internal resistance adjustment, in particular to an electromagnetic valve state monitoring device and method.The electromagnetic valve state monitoring device comprises a controller, an RC filter circuit, a sliding filter circuit, a drive circuit and an ADC sampling circuit, and the controller is connected with the RC filter circuit, the drive circuit and the ADC sampling circuit; the ADC sampling circuit is respectively connected with the driving circuit and the sliding filter circuit; wherein the sliding filter circuit maintains three historical data thresholds to form a sliding window, new sampling data is compared with each historical value in the window, sampling noise is eliminated, then the new sampling data is transmitted to the controller through the ADC sampling circuit, the controller collects the sampling data through the ADC sampling circuit and carries out data preprocessing, and therefore the on-off state of the electromagnetic valve is judged; according to the invention, the transient response characteristics of the driving voltage of the electromagnetic valve are fully utilized, the dynamic model solution and the adaptive filtering algorithm are matched, the effective signal reflecting the internal resistance change is separated, and high-precision state recognition and fault early warning are realized.

The invention discloses an anti-high-frequency bias sampling device and method. The sampling position of the next beat is updated in real time by comprehensively considering the hopping condition and the sampling position of the data to be oversampled of the previous beat, the data to be oversampled of the current beat is sampled based on the latest sampling position, and finally the sampled data with the dynamic bit width is output with the fixed bit width. Compared with the prior art, the method has the advantages that higher frequency offset can be tolerated by updating the sampling position in real time; the logic is simple, and does not need to calculate source and sink end frequency offset like a traditional method, so that more resources can be saved; the method is high in universality, and can be applied to bearer networks such as Ethernet, optical transport networks and the like, and even all places needing oversampling in digital communication.

The invention provides a communication radiation source individual identification method based on time domain and time sequence coding constellation diagram feature fusion. The method is used for realizing stable identification of different transmitters under non-ideal conditions of carrier frequency offset, noise interference and the like. The method comprises the following steps: firstly, carrying out normalization and fixed-length interception on a received I / Q signal, and calculating an oversampling multiple according to a symbol rate and a time resolution; then, a time domain and time sequence coding constellation diagram double-branch feature extraction network is constructed, a time domain structure feature is extracted from a time domain branch by adopting a one-dimensional modified ResNet18, and a constellation diagram with time information is generated from a time sequence coding constellation diagram branch through a time sequence coding constellation module and the feature that the phase changes along with time is extracted; and carrying out joint modeling on the two types of features through a trainable weighted fusion mechanism. In the training stage, the performance of the model is improved by adopting cross entropy loss, an Adam optimizer, learning rate scheduling and an early stop strategy. In the reasoning process, input signals are classified by using the model weight with the highest verification accuracy, and a communication radiation source individual identification result is output. Experimental results show that the method can effectively enhance the frequency offset robustness and generalization ability of the model, realizes high-precision identification of the individual communication radiation source, and is suitable for the fields of security access of the Internet of Things, spectrum monitoring, electronic countermeasures and the like.

The invention relates to the technical field of broadband signal synthesis and high-speed digital-to-analog conversion, in particular to an oversampling-based real-time frequency interleaving digital-to-analog conversion system aliasing suppression method and system, and aims to solve the problem of spectrum aliasing caused by non-ideal characteristics of a digital sub-band decomposition filter and an analog filter under a real-time architecture of the system. In the invention, the sub-band decomposition is completed by adopting the linear phase complementary filter bank, so that distortion introduced by a transition band of a digital filter is avoided; by restraining system parameters such as passband and stopband frequencies and local oscillation frequency of a sub-band decomposition filter, a protection band is set by an oversampling mechanism, a frequency margin is reserved for a transition band of the filter, and aliasing components are suppressed. According to the method, extraction aliasing of a digital domain and mirror image aliasing of an analog domain are avoided at the same time from the system architecture, the frequency spectrum purity of output signals is improved, the method is suitable for a real-time system for processing continuous data streams, and technical support is provided for achieving a high-performance broadband signal source.

An electronic interface device is configured for use with associated optics for employing coded light for illuminating a liquid, gaseous, or other analyte or target, such as for measuring or determining a composition or other property of the analyte or target. The arrangement can help enable a far higher level of performance, such as for spectral analysis, imaging, or both. A shared common clock on both the illumination and receive sides of the system can be included, such as together with one or more of reference detection, per-channel wavelength-dependent modulation, multiple concurrent feedback loops at different levels, orthogonal and circulant codes, phase-scrambling to better utilize ADC dynamic range, oversampling, and other signal processing can be provided. Modulation codes can optionally employ a clock divider, such as which can be configured to satisfy one or more specified constraints.

The invention provides a multiplexed signal parallel demultiplexing method based on an FPGA and a demultiplexing equalizer. The method comprises the following steps: receiving multiple paths of serial multiplexed signals from a high-speed link, performing oversampling processing on the received multiple paths of serial multiplexed signals, and performing parallelization processing on each path of serial multiplexed signals subjected to oversampling processing; inputting each path of parallelized signal into a butterfly equalization demultiplexing module, performing equalization processing on the input by using a periodically updated tap coefficient of the butterfly equalization demultiplexing module, and performing demultiplexing processing by using a CMA algorithm to obtain a received output signal for demultiplexing a multiplexing signal; sequentially selecting output signals of the butterfly equalization demultiplexing module at intervals according to a preset proportion, and calculating a tap coefficient accumulative error vector by combining the selected output signals and the corresponding input signals; and according to the iteration step length of the CMA algorithm, the tap coefficient of the butterfly equalization demultiplexing module is updated based on the tap coefficient accumulative error vector.

The invention provides a dual-channel high-sensitivity signal power estimation method and device and a storage medium, and the method comprises the steps: obtaining first signal data and second signal data, the first signal data being collected through a first data collection device, and the second signal data being collected through a second data collection device; determining a correlation peak detection result and an oversampling multiple according to the cross-correlation condition of the first signal data and the second signal data; and calculating target signal power according to the correlation peak detection result and the oversampling multiple. The signal data is acquired through the two data acquisition channels, and power estimation is performed according to the signal data of the different data acquisition channels, so that the power of the weak signal hidden in the environmental noise can be estimated, and a better frequency spectrum monitoring effect is provided.