35 results about "Amplitude distortion" patented technology

The invention provides a baseband radio frequency signal data feedback processing method based on vector modulation, and the method comprises the steps: firstly receiving a baseband signal data set transmitted by a target radio frequency link in a preset frequency band, and the baseband signal data set comprises a plurality of signal frame original modulation parameters and corresponding radio frequency feedback signal waveforms; calculating a feedback error index composed of a phase offset, an amplitude distortion factor and a spectrum leakage factor according to a radio frequency feedback signal waveform, quantifying a modulation error, carrying out time-frequency domain conjoint analysis on the feedback signal waveform, extracting an error feature vector, inputting the error feature vector into a pre-training model for cross-frame correlation learning, and carrying out the correlation learning; according to the method, a dynamic adjustment parameter sequence containing a time sequence dependency relationship is generated, and finally a closed-loop feedback control link is constructed based on the dynamic adjustment parameter sequence and original modulation parameters, so that precise processing and optimal control of baseband radio frequency signals are realized, and the signal transmission performance is effectively improved.

The invention relates to a self-diagnosis method for a state terminal of a substation measurement system, which comprises the following steps of: comparing signal values at different sampling nodes of signals from the same physical source in each measurement channel through the state terminal, and judging that the channels have physical chain degradation or poor contact; performing perturbation modulation on a measurement sampling process based on a clock signal controlled by a crystal oscillator in the state terminal, and if response deviation abnormity is detected, judging that a sampling time base has drift, time sequence disorder or cache backlog so as to identify a time base health state of a sampling chain in the terminal; in the operation process of the transformer substation, response differences generated by the excitation in different measurement channels are collected, and if response delay, amplitude distortion or jitter starting point deviation is found, it is judged that the anti-interference capacity of the corresponding channel is degraded; and according to the electric energy change rhythm sensed by the terminal in real time, adaptively adjusting the sensitivity threshold value of the jump response, and if frequent misjudgment or slow response of the jump response is detected, marking that the behavior sensitivity of the terminal sampling system is abnormal.

The invention relates to the technical field of image recognition, and discloses an image recognition method for cross-domain access authentication, which comprises the following steps: acquiring a to-be-authenticated image uploaded by an image acquisition node; converting the to-be-authenticated image to a frequency domain, and extracting a plurality of response signals in multiple preset directions and scales; calculating a phase consistency measure by using the real part and imaginary part response components, and generating a phase consistency feature map; carrying out statistics on local phase distribution of the phase consistency feature map, determining a phase distribution entropy representing physical attributes of an access medium, and carrying out weight reduction suppression on the phase consistency feature map according to the phase distribution entropy; according to the method, phase interference introduced by an unnatural display medium is recognized and suppressed, in-vivo detection is achieved in identity verification, and the influence of heterogeneous imaging amplitude distortion on recognition precision is eliminated.

The invention relates to the technical field of signal processing, in particular to a pipeline guided wave signal processing method and system. The method comprises the following steps: acquiring a multi-channel ultrasonic guided wave signal through a sensor array circumferentially arranged around a pipeline, and converting the multi-channel ultrasonic guided wave signal into a frequency domain response matrix; calculating a circumferential amplitude distortion degree based on the power spectrum amplitude distribution of each channel; constructing a modal coupling matrix by combining the circumferential amplitude distortion degree and the theoretical wave number of the ideal pipeline; correcting the standard orthogonal modal matrix to generate a modal projection matrix; and decomposing the frequency domain response matrix by using the projection matrix, and separating a structure echo component and a defect signal component. According to the method, the influence of geometric defects such as ovality deviation is evaluated more accurately, energy exchange between modeling modes is accurately established, and orthogonality hypothesis is corrected; modal energy leakage is inhibited, and the decomposition accuracy is improved; signals are effectively separated, coherent noise interference is solved, and the accuracy and reliability of pipeline defect detection are improved.

The invention belongs to the technical field of seismic data processing in geophysical exploration, and relates to a Marchenko multiple suppression method for correcting wave field mismatch based on Wasserstein distance, which comprises the following steps: acquiring a pulse reflection sequence through preprocessing and deconvolution; a pulse reflection sequence is input, and Marchenko iteration initialization is carried out; and remodeled Marchenko iteration for correcting the wave field mismatch based on the Wasserstein distance is carried out. According to the method, the optimal transmission theory is systematically introduced into the Marchenko multiple wave suppression field for the first time, the adaptive capacity of the Marchenko method to actual data noise, defect and amplitude distortion is remarkably improved while the advantage that the Marchenko method does not need a speed model is kept, and therefore higher-precision multiple wave suppression and more reliable primary wave recovery are achieved, and the method is suitable for popularization and application. The method is used for high-precision seismic imaging in a complex land exploration environment. The method has remarkable advantages in the aspects of constraint mechanism, error control and global feature protection.

The invention specifically relates to a method and a system for detecting a high-resistance grounding fault of a power distribution network, and belongs to the technical field of power distribution network fault detection. According to the method, the amplitude difference of the zero-sequence current is converted into the angle difference through the Grubby angle field coding, so that weak current distortion is amplified into a remarkable spatial stripe in the Grubby angle field image, and the abrupt change characteristic in the fault transient process can be effectively represented. Meanwhile, due to the symmetry and translation invariance of the Grubrum angle field matrix, the time domain dependency relationship of the zero-sequence current waveform of the high-resistance grounding fault is completely reserved, and the fault feature extraction capability can be effectively improved. According to the method, a traditional standard convolution kernel is improved according to polar coordinate characteristics of the Grubrum angle field image, time evolution characteristics are extracted by using radial branches of the multi-axis variable neural network, amplitude distortion characteristics are extracted by using angular branches of the multi-axis variable neural network, diagonal characteristics are extracted by using deformable convolution in a self-adaptive manner, and the expression ability of the extracted characteristics is effectively improved.

This invention provides a method for selecting strong scattering points in space-based ISAL systems by incorporating multi-dimensional features, relating to the field of ISAL image processing. This invention employs a multi-stage fusion processing strategy to form a complete link from image preprocessing to the final output of strong scattering points: pixel replication and extension are used to process convolutional boundary regions, significantly reducing boundary amplitude distortion caused by traditional zero-padding or periodic extension, and improving the signal-to-noise ratio of edge regions in the filtered amplitude map; the dynamic threshold generation process works synergistically with the preceding Gaussian kernel convolution preprocessing to suppress speckle noise while preserving the true amplitude characteristics of weakly scattering targets; amplitude-weighted averaging is used to calculate the centroid coordinates within the connected domain, overcoming the energy diffusion problem caused by the ISAL system's point spread function; transient interference points are eliminated based on the peak-to-mean ratio of multi-frame amplitude sequences, and the spatial distribution characteristics of the centroid position's spatial amplitude value and density constraints are combined to ensure that the output set of preferred scattering points simultaneously satisfies temporal stability, spatial saliency, and uniform distribution.

The application provides a baseband radio frequency signal data feedback processing method based on vector modulation, which first receives a baseband signal data set transmitted by a target radio frequency link in a preset frequency band, which contains multiple signal frame original modulation parameters and corresponding radio frequency feedback signal waveforms, then calculates feedback error indicators composed of phase offset, amplitude distortion and spectral leakage factor according to the radio frequency feedback signal waveforms, quantizes the modulation error, analyzes the feedback signal waveforms in the time-frequency domain, extracts error feature vectors, inputs the pre-trained model for cross-frame correlation learning, generates a dynamic adjustment parameter sequence containing time sequence dependence, and finally constructs a closed-loop feedback control link based on the dynamic adjustment parameter sequence and the original modulation parameters, so as to realize accurate processing and optimized control of the baseband radio frequency signal and effectively improve the signal transmission performance.

The present application relates to the technical field of signal processing, and particularly relates to a pipeline guided wave signal processing method and system. The method comprises the following steps: acquiring multi-channel ultrasonic guided wave signals through a sensor array arranged circumferentially around a pipeline, and converting the signals into a frequency domain response matrix; calculating a circumferential amplitude distortion degree based on the amplitude distribution of the power spectrum of each channel; constructing a modal coupling matrix in combination with the circumferential amplitude distortion degree and an ideal pipeline theoretical wave number; generating a modal projection matrix by correcting a standard orthogonal modal matrix; and decomposing the frequency domain response matrix by using the projection matrix to separate a structure echo component and a defect signal component. The present application more accurately evaluates the influence of geometric defects such as ellipticity deviation, accurately models the energy exchange between modes and corrects the orthogonality assumption, suppresses modal energy leakage, improves the decomposition accuracy, effectively separates signals, solves the interference of coherent noise, and improves the accuracy and reliability of pipeline defect detection.

Disclosed in the present invention is a high‑linearity, high‑power GaAs HBT power amplifier having a power detection function, characterized in that: the GaAs HBT power amplifier comprises a radio frequency path, a bias module and a power detection circuit. The radio frequency path is used to perform power amplification on a radio frequency signal, a negative feedback network is used to improve the stability and expand the bandwidth, and second harmonic suppression improves the overall linearity. The bias circuit is used to provide, to a three-stage amplification circuit, a bias voltage that dynamically changes along with an input power, so as to solve the problems of linearity degradation and current instability caused by a self-heating effect in a GaAs HBT transistor under high-power input, thereby mitigating amplitude-amplitude distortion and amplitude-phase distortion of the power amplifier. The power detection circuit is used to output a direct current voltage that is positively correlated with an output power, so as to achieve accurate control of the output power of the power amplifier. By fully integrating negative feedback, dynamic biasing and harmonic suppression techniques, the present invention effectively improves the overall linearity of the amplifier.

The application belongs to the technical field of signal processing, and specifically discloses an anti-deception interference method and system based on dynamic weight and timing constraints, wherein the method comprises the following steps: using a field programmable logic gate array to perform hardware-level real-time preprocessing on synthetic aperture radar original echo data, and triggering hardware-level adaptive routing truncation according to an amplitude distortion gradient, and outputting preprocessed data after algorithm power deployment; based on the preprocessed data, multi-modal features are extracted in parallel, and the multi-modal features comprise image domain incoherent topology features, local phase dispersion degree features and spatial geometric constraint features; the application aims to solve the problems of single feature source representation, poor environmental adaptability of fusion mechanism, not using deception interference timing physical contradictions and large model calculation overhead in existing synthetic aperture radar anti-interference schemes, which leads to limited real-time performance.

The invention discloses an offshore microwave signal time-frequency joint equalization method, system and device based on a Transform model and a medium, and belongs to the technical field of deep learning models and signal processing, and the method comprises the steps: collecting and preprocessing offshore microwave radio frequency signal data, and obtaining a complex baseband signal sequence; generating a time-frequency spectrum matrix; constructing an auxiliary feature vector sequence; dividing the auxiliary feature vector sequence into time frequency units to form a token sequence; the token sequence is input into an improved Linformer-Transformer model, and a hidden representation sequence is obtained; outputting a combined equalization coefficient vector; carrying out amplitude-phase correction to obtain a balanced complex baseband signal sequence; and obtaining an equalized time-frequency spectrum matrix and a reconstructed complex baseband signal sequence. According to the invention, time-frequency joint equalization of signals is realized, the transmission reliability and signal quality of offshore microwave communication are improved, and the problems of amplitude distortion and phase distortion caused by multipath propagation, frequency selective fading and phase random drift in an offshore microwave channel are effectively solved.

The present invention belongs to the field of specific radiation source identification technology, specifically an algorithm for radiation source identification based on differences in amplitude probability distributions. This algorithm addresses the problems of existing common algorithms, such as their limited targeting of amplitude distortion and high complexity, low recognition rates under small sample sizes, and sensitivity to prior information on the signal-to-noise ratio. The proposed scheme includes the following steps: S1: performing amplitude mean normalization preprocessing on the real signal, evenly dividing the real signal amplitude into intervals, and calculating the probability distribution of the sample points in each amplitude interval; S2: performing a Hilbert transform on the real signal to obtain an analytic signal, performing amplitude mean normalization preprocessing on the analytic signal, evenly dividing the analytic signal constellation into circular intervals, and calculating the probability distribution of the sample points in each circular interval. The algorithm is insensitive to prior information on the signal-to-noise ratio and can achieve a high recognition rate without requiring an estimation of the signal-to-noise ratio. Furthermore, compared with comparable algorithms, the proposed algorithm has lower computational complexity.

The application discloses a gradient precondition-based image domain least square reverse time migration method and belongs to the field of deep-sea oil and gas field exploration and development. The method aims to solve the problems of imaging amplitude distortion, resolution decline and slow convergence caused by the traditional gradient optimization method due to the neglect of the second-order curvature information of the Hessian matrix. The technical scheme points are as follows: an image domain least square reverse time migration objective function is constructed; the Hessian matrix is approximated based on a point spread function; a training pair of the gradient and the migration gradient is constructed by using the Born scattering theory; an improved U-Net network with a channel-space double attention mechanism is built to learn the mapping relationship of the Hessian inverse matrix in an unsupervised manner; and the trained network is embedded into the optimization framework of a fast iterative shrinkage threshold algorithm as a gradient precondition operator to correct the model updating direction. The application effectively improves the imaging quality of uneven illumination areas and improves the amplitude fidelity and inversion convergence speed.

Methods, systems, and devices for wireless communications are described. A user equipment (UE) may receive, from a transmitting device, an indication of an instantaneous gain associated with an amplitude distortion associated with frequency division multiplexed downlink communications to the UE from the transmitting device. The UE may receive the frequency division multiplexed downlink communications from the transmitting device over frequency resources allocated to the UE, wherein receiving the frequency division multiplexed downlink communications comprises applying a digital post distortion model to the frequency division multiplexed downlink communications according to the instantaneous gain.

The application discloses a kind of narrowband communication equipment detection equipment and detection method. Among them, the method includes: obtaining pre-established wireless channel model data set, the data set contains attenuation value and interference intensity distribution data under different environments;According to the attenuation value and interference intensity distribution data, a multipath propagation simulation model is constructed, a time delay spread range value is obtained by time domain analysis, and an amplitude distortion range value is obtained by frequency domain analysis;Environment noise measured data and the time delay spread range value, amplitude distortion range value are input into adaptive filtering algorithm, and signal quality evaluation data after filtering processing is generated, etc.The method of the present application analyzes and simulates the channel model data under different environments, combines various test methods and algorithms, comprehensively evaluates the performance of the equipment under various conditions, including signal quality, bit error rate, stability and risk, etc., so as to ensure the reliability of the equipment in practical application.

The invention discloses a pulse signal wireless transmission and calibration method based on cloud-edge cooperation, and relates to the technical field of signal transmission, and the method comprises the steps: an edge node collects reference noise in a transmission environment, generates estimated noise through an adaptive filter, carries out the denoising of a received pulse signal with noise, and carries out the amplitude distortion detection and preliminary correction; edge nodes exchange timestamps through a self-organizing network to realize initial time synchronization, and a cloud absolute time signal is combined, a local clock is finely adjusted by adopting a PI control algorithm, and time unification of the whole network is realized; the edge nodes detect the actual feature points of the pulse signals through a sliding window, align the actual feature points with the standard feature points, adjust window parameters, and perform local calibration in combination with local initial calibration parameters; the cloud end issues initial calibration parameters to the edge nodes, the edge nodes carry out secondary calibration and upload local optimization parameters, the cloud end carries out weighted fusion to generate global optimal parameters, iterative optimization is carried out until calibration errors are stable, and the real-time performance and accuracy of signals are remarkably improved.

The application relates to the technical field of oil exploration, and particularly discloses a multi-seismic-source aliasing seismic data decoupling separation method, which comprises the following steps: inputting aliasing seismic data and establishing a mathematical model, converting a separation problem into a signal recovery problem with constraints; reorganizing the data into a common offset domain, constructing a cascade shift embedded Hankel matrix to form a low-rank prior; designing an energy-aware modulation function based on spectral component values to adaptively distinguish effective signals and crosstalk; fusing a weighted spectral norm and a transform domain sparsity constraint to construct a joint structured penalty optimization model; and adopting a variable splitting iteration framework to decompose a sub-problem, alternately solving and adaptively updating weights. The application protects effective signals by relying on an adaptive weight strategy, separates crosstalk by combining low-rank and sparse double characteristics, overcomes signal leakage and amplitude distortion problems, improves waveform fidelity and separation signal-to-noise ratio, and takes into account convergence stability and calculation efficiency, so that the application has important application value in complex geological oil and gas exploration and high-precision seismic imaging.

Disclosed implementations determine transient distortions, amplitude distortions, and / or periodic distortions present in a voltage signal measured from an electrical circuit at a location and use those distortions to determine a device type of a device operating on the electrical circuit at the location. In some examples, the voltage signal may be filtered into a plurality of sub-bands and one or more two-dimensional representations generated based on transient distortions, amplitude distortions, and / or periodic distortions determined in each sub-band. The one or more 2D representations may be provided to a deep neural network to determine a device type that generated the distortions on the electrical circuit.

The present invention provides a method and system for detecting the modulation sideband frequency of gears in a complex transmission system. The method comprises: a vibration sensor, a multi-channel data acquisition device, a computer, and data analysis software installed on the computer. The vibration sensor is used to sense the vibration of the integrated transmission device and convert it into an electrical signal for input. The vibration sensor is connected to the multi-channel data acquisition device, which converts the electrical signal into a digital signal and performs anti-aliasing filtering. Data transmission and communication with the computer are achieved via a network cable. The data analysis software installed on the computer is used to detect the modulation sideband frequency of the gears in the integrated transmission device and provide the detection results of the gear modulation sideband frequency. The detection results of the present invention are not affected by amplitude distortion caused by speed changes, are insensitive to speed changes, and can effectively avoid interference with the detection results caused by non-Gaussian noise and resonant frequency.

The invention relates to an electrostatic loudspeaker, a moving-coil loudspeaker and a device for processing audio signals, and belongs to the technical field of electroacoustics. According to the technical scheme provided by the invention, the amplitude distortion of the loudspeaker can be effectively reduced; for an electrostatic loudspeaker, the amplitude distortion of the loudspeaker can be reduced by carrying out first-order, second-order or third-order derivative solving operation on an input audio signal before the input audio signal is transmitted to two fixed polar plates of the loudspeaker, and the effect is the best when the second-order derivative solving operation is carried out; for a moving-coil loudspeaker, the amplitude distortion of the loudspeaker can be reduced by carrying out first-order, second-order, third-order, fourth-order or fifth-order derivative solving operation on an input audio signal before the input audio signal is transmitted to a voice coil of the loudspeaker, and the effect of carrying out the third-order derivative solving operation is relatively good; the technical scheme provided by the invention can be used for reducing the amplitude distortion of the loudspeaker in all equipment related to the loudspeaker so as to improve the sound restoring effect of the equipment.

The invention discloses an edge detection filter based on a TANH function and an inclination angle, which determines Bouguer gravity anomaly data by obtaining gravity observation data and topographic data of each gravity point of a research area, calculates Gaussian envelope gravity gradient data according to the Bouguer gravity anomaly data, and obtains the edge detection filter based on the TANH function and the inclination angle. A corresponding filter is calculated based on a TANH function, an inclination angle algorithm and Gaussian envelope gravity gradient data, so that amplitude responses from different depth anomalous bodies can be effectively balanced, and edge signals generated by shallow and deep geologic bodies are more balanced in strength; the problem that amplitude distortion or concealment is easy to generate when a traditional method is used for processing multi-scale and multi-depth targets is solved; the geological boundary is clearly and accurately depicted under the complex geological condition, background noise interference is effectively suppressed, the recognition capability of edge details is remarkably enhanced, misjudgment caused by false edges and noise is effectively reduced, and the reliability of data interpretation and the accuracy of geological detection are improved.

The invention relates to the technical field of signal processing, and provides a laser ultrasonic longitudinal wave signal processing method and device and electronic equipment. Comprising the following steps: preprocessing a laser ultrasonic original signal; filtering and noise reduction are carried out on the preprocessed signals; carrying out discrete wavelet decomposition on the filtered and denoised signal by adopting a wavelet basis function matched with the target longitudinal wave feature; and reconstructing a target longitudinal wave signal based on detail components in discrete wavelet decomposition. The overall trend drift of signals is eliminated in the preprocessing stage, so that amplitude distortion caused by reference position drift is corrected, and high-frequency noise is preliminarily suppressed in the filtering noise reduction link to prevent signal confusion in follow-up processing. The wavelet basis selection of feature matching ensures that discrete wavelet decomposition can effectively distinguish same-frequency-band interference components in target longitudinal waves and aliasing signals, transient abrupt change features of the longitudinal waves are reserved to avoid effective information loss caused by global frequency analysis, and the detection precision of the near-edge position of a small-size complex sample is improved.

The application discloses a pulse signal wireless transmission and calibration method based on cloud edge cooperation and relates to the technical field of signal transmission.The edge node collects reference noise in a transmission environment, generates estimated noise through an adaptive filter, denoises a received noisy pulse signal, and performs amplitude distortion detection and preliminary correction;the edge node exchanges time stamps through a self-organizing network to achieve preliminary time synchronization, combines an absolute time signal in the cloud, fine-tunes a local clock by adopting a PI control algorithm, and realizes time unification of the whole network;the edge node detects actual characteristic points of the pulse signal through a sliding window, aligns the actual characteristic points with standard characteristic points, adjusts window parameters, and performs local calibration in combination with local initial calibration parameters;the cloud issues initial calibration parameters to the edge node, the edge node performs secondary calibration and uploads local optimization parameters, the cloud performs weighted fusion to generate global optimal parameters, and iterative optimization is performed until calibration error is stable, so that the real-time performance and accuracy of the signal are significantly improved.

The application relates to the technical field of image recognition, and discloses an image recognition method for cross-domain access authentication, which comprises the following steps: acquiring an image to be authenticated uploaded by an image acquisition node; transforming the image to be authenticated to a frequency domain, and extracting complex response signals under multiple preset directions and scales; calculating a phase consistency measure by using real and imaginary response components, and generating a phase consistency feature map; statistically analyzing local phase distribution of the phase consistency feature map, determining phase distribution entropy representing physical properties of an access medium, and accordingly reducing the weight of the phase consistency feature map; extracting geometric topological relations of structure anchor points in the feature map after the reduction, constructing an identity representation vector, and comparing the identity representation vector, the application recognizes and suppresses phase interference introduced by non-natural display media, realizes live body detection in identity authentication, and eliminates the influence of heterogeneous imaging amplitude distortion on recognition accuracy.

A method, a system, and a related device are provided. The method includes: A controller may determine a first optical channel between an optical transmitting device and an optical receiving device in a first slot based on a data transmission request, and then send configuration information to the optical transmitting device or the optical receiving device, to indicate the optical transmitting device or the optical receiving device to transmit data in the first slot based on an amplitude compensation coefficient of the first optical channel. This helps compensate for amplitude distortion caused by the first optical channel and reduce a bit error rate.

The invention relates to the technical field of signal processing, in particular to a real-time processing method for distortion correction of a radio frequency signal of communication equipment, which comprises the following steps of: dynamically extracting a reference signal fragment from a communication data stream, and acquiring an equipment identifier corresponding to the reference signal fragment; extracting a distortion feature vector based on the reference signal segment and the ideal reference signal template; dividing an equipment association group according to the long-term average received signal strength indication value and the channel pulse response information, and calculating statistical feature data of equipment in the equipment association group according to the historical distortion feature vector; on a time domain scale, acquiring change characteristic information of each device based on the distortion characteristic vector; and classifying the phase distortion component and the amplitude distortion component according to the historical distortion feature vector, the statistical feature data and the change feature information to obtain a distortion type, and generating a final correction parameter based on the distortion type, so that the method has real-time performance, adaptability and reliability, and can adapt to a complex dynamic environment.

The invention discloses an amplitude distortion automatic calibration method and device, and a medium, which are applied to an upper computer, and the method comprises the steps: obtaining an in-band dot frequency signal generated by a signal source, and converting the in-band dot frequency signal into a digital signal; digital signal power is calculated, and a digital power vector is generated; according to the order of the filter and the bandwidth parameter, determining the order of the compensation filter and a transition band range; calculating a compensation vector based on the digital power vector, generating a phase vector according to the filter order and the interpolated digital power vector point number, and calculating the compensation vector and the phase vector to obtain a compensation frequency response; performing time-frequency conversion on the compensation frequency response, and determining a compensation filter coefficient; and carrying out normalization processing on the compensation filter coefficient, and loading the coefficient to the compensation filter to complete the automatic calibration of the amplitude distortion of the receiving channel. According to the invention, the flexibility is improved, the resource consumption of a hardware multiplier is reduced, and the problem of amplitude response distortion caused by in-band fluctuation is solved.

The invention provides a two-level electromagnetic bearing digital switch power amplifier PI control strategy based on steady-state control quantity feedforward. According to the strategy, the dependence on an integration link is reduced structurally, and the problems of phase margin reduction, overshoot, medium-frequency band amplitude distortion and the like caused by overlarge integration gain in traditional PI control are avoided while the dynamic performance of the system is ensured. Firstly, a steady-state control quantity calculation model under a given current instruction is established according to a system mechanism model and dynamic characteristics, then a proportional gain is determined according to a relationship between a closed-loop bandwidth index and the proportional gain, and finally, a small integral gain is introduced to enhance the suppression capability of the system on the uncertainty of the model. Theoretical analysis and experimental results show that the provided strategy is effective, compared with a PI controller, the dynamic performance and the phase margin are better, response is fast, overshoot is avoided, amplitude distortion is avoided in medium-frequency-band sinusoidal current tracking, and stable and reliable operation of an electromagnetic bearing rotor system is facilitated.