24 results about "Spectrum function" patented technology

The invention provides an anti-noise enhanced power distribution network cable fault detection and positioning method. Multi-period test signals are injected, reflected signals are collected, m-sequence denoising characteristics and self-adaptive wavelet transform are combined, denoising and normalization processing is carried out on the multi-period reflected signals, and the signal quality is improved. The power spectrum functions are averaged after multi-cycle quadratic cross-correlation weighting, and anti-noise enhanced fault positioning is realized through IFFT processing. Meanwhile, filtering signal time domain features (such as amplitude, phase and envelope) of a first period are extracted and fused with a final power spectrum function IFFT value after secondary cross-correlation weighting into a high-dimensional feature vector, and the high-dimensional feature vector is input into a deep learning model based on a convolutional neural network, LSTM and an attention mechanism. The attention mechanism is used for weighting the IFFT value of the power spectrum function after quadratic cross-correlation weighting, extracting peak value characteristics, and improving the positioning precision. The method realizes accurate classification and positioning of cable faults, has high precision and anti-interference capability, is suitable for cable fault detection in a complex environment, and provides technical support for stable operation of a power system.

This invention provides an automated testing device for UAV data links, including an industrial control computer, a display, a spectrum analyzer, a programmable DC power source, a programmable adjustable attenuator, a fixed attenuator I, a fixed attenuator II, a power divider I, a power divider II, an RF switch, a shielded box I, and a shielded box II. The software of the industrial control computer includes a system management module and an automated testing module. The advantages of this invention are: it uses general-purpose testing equipment, is based on a computer-automated program, and controls the settings of each testing device via a bus to simulate remote control, telemetry, image data transmission and reception, and bit error rate statistics; it achieves automated testing of core functional performance indicators of UAV data links such as power consumption, transmit power, spectrum, functionality, receiver sensitivity, bit error rate, and latency.

The present invention discloses a method for direction finding of incoherently distributed sources under strong impulse noise. The method comprises the following steps: first, obtaining snapshot sampling data, performing de-impact preprocessing, and constructing a generalized Capon space spectrum function; second, initializing the quantum position of each arrow and setting parameters to construct a fitness function; third, dividing the arrow group into sub-arrow groups, and performing fitness function evaluation on all arrows. The quantum position of the arrow with the best fitness in each sub-arrow group is selected as the optimal quantum position; fourth, updating the quantum position of each arrow according to the shooting mechanism; fifth, mapping the updated quantum position of each arrow to a position, calculating the updated fitness function value, and updating the optimal quantum position of each sub-arrow group; and sixth, returning to step three, looping and iterating until the maximum number of iterations is reached, outputting the optimal quantum position set, and transforming it into the central azimuth and angular spread estimates of the incoherently distributed source through mapping. The method is robust and high-performance under strong impulse noise conditions.

The invention discloses a cable joint damp degree assessment method and device and a storage medium. The method comprises the steps of obtaining a target reflection coefficient spectrum function corresponding to a target cable; b envelope peaks corresponding to the target reflection coefficient spectrum function are determined; b cable joints corresponding to the b envelope peaks in the a cable joints are determined; converting the target reflection coefficient spectrum function from a frequency domain to a time domain by adopting a preset time-frequency domain conversion algorithm to obtain a target time domain function; determining pulse peak pairs in the target time domain function to obtain b pulse peak pairs; and according to the b envelope peaks and the b pulse peak pairs, determining the damp degrees corresponding to the b cable joints to obtain b damp degrees. According to the embodiment of the invention, the detection precision of the damp degree is improved.

A data generation device is a device for generating data to control an SLM for shaping a light pulse for laser processing, and comprises at least one processor configured to: set information regarding a plurality of mutually different temporal-intensity waveforms each including a plurality of light pulses; generate each of a plurality of sets of an intensity spectrum function and a phase spectrum function based on each of the plurality of temporal-intensity waveforms; generate each of a plurality of pieces of data based on each of the plurality of sets of the intensity spectrum function and the phase spectrum function; and calculate a generation efficiency in the SLM for each of the plurality of temporal-intensity waveforms based on each of the plurality of pieces of data and determine data for controlling the SLM from among the plurality of pieces of data based on the generation efficiency.

The invention discloses a metasurface-assisted multi-channel super-resolution DOA (direction of arrival) estimation method based on off-grid sparse Bayesian learning. The implementation mode of the method is as follows: giving an incoming wave signal, and establishing a signal model for the incoming wave signal to reach a metasurface array element; according to the transmission amplitude and the transmission phase of the transmission type metasurface, establishing a signal model of an incoming wave signal transmitting out of the metasurface; establishing a signal model of a receiving end of the receiving antenna according to the position relationship between the receiving antenna and the metasurface; grid division is carried out on the airspace, and a sparse flow pattern array is constructed; according to a Bayesian learning algorithm, carrying out hyper-parameter initialization by utilizing the collected signal sample value, and carrying out iteration on hyper-parameters according to the idea of an expectation maximization algorithm; and finally, constructing a power spectrum function, and visualizing a calculation result to obtain a direction of arrival estimation result. Compared with an existing DOA estimation method, the method has better estimation performance and higher resolution under the condition that the number of receiving channels is the same. According to the invention, high-precision target estimation and super-resolution capability are guaranteed, the number of receiving channels is reduced, the complexity of a receiving system is reduced, and the system cost is saved.

A half-spectrum search low-complexity azimuth estimation method for sound pressure and vibration velocity combined dimension reduction processing relates to the field of array signal processing, and comprises the following steps: acquiring output signals of a vector hydrophone array under N snapshots, and establishing a far-field target sound signal model; constructing a sampling covariance matrix for the output signal, and separating the sampling covariance matrix into a real part and an imaginary part; the vibration velocity signals in the vector array are synthesized in the guide angle direction through Givens transformation, a synthesized vibration velocity signal is constructed, and the synthesized vibration velocity signal and the sound pressure signal are jointly processed to construct a joint covariance matrix; constructing a DOA estimation model by using the real part of the joint covariance matrix, and constructing a spatial spectrum function based on the DOA estimation model and the real part of the joint covariance matrix; and searching a spectral function peak value in a half interval of a scanning angle space, and judging a real target angle according to a MUSIC algorithm. According to the method, the calculation amount is reduced while the estimation performance is ensured, and the problem that a traditional DOA estimation method is high in calculation complexity is solved.

This invention discloses a signal amplitude deviation compensation method and system, applied to a spectrum analysis system that uses a rectangular window to truncate a single-frequency sinusoidal signal. The method includes: acquiring the true frequency of the input signal, the sampling frequency of the spectrum analysis system, and the number of Fast Fourier Transform (FFT) sampling points; calculating the normalized frequency offset of the true frequency relative to the FFT discrete grid; determining whether the normalized frequency offset is zero; if it is non-zero, calculating an amplitude deviation compensation value based on the normalized frequency offset and the spectrum function model of the rectangular window; acquiring the original signal amplitude value obtained after FFT calculation of the input signal; and compensating the original signal amplitude value using the amplitude deviation compensation value to obtain the compensated signal amplitude value. This invention achieves automated, high-precision integrated modeling from device to system.

The invention discloses a metro track irregularity evaluation method based on characteristics of a wheel-rail system, and the method comprises the steps: S1, collecting the actually measured irregularity data of a metro track, and carrying out the power spectrum density estimation through a Welch method; fusing the medium-long wave irregularity spectrum and the short wave irregularity spectrum to form a joint spectrum; performing high-order polynomial fitting on the joint spectrum to obtain a joint spectrum function expression; s2, carrying out numerical inversion on the joint spectrum by adopting an inverse fast Fourier transform method, and generating an orbit irregularity sample containing medium-long wave and short wave characteristics; s3, calculating the vertical vibration acceleration of a vehicle body and the dynamic response of the vertical force of a wheel track based on the vehicle-track coupling dynamic model; s4, in combination with the double-weight curve, calculating a wavelength weight coefficient of track irregularity through transfer function frequency domain integration; and S5, superposing all frequency band weighting results, and outputting a metro track irregularity weighting quality index. The method has the advantage that a quantitative basis is provided for maintenance and repair of the subway track.

The invention discloses a non-linear structure frequency and vibration mode coefficient identification method based on a sliding window power spectrum and Polymax. The method comprises the following steps: 1, testing to obtain an acceleration response of an engineering structure; 2, calculating an auto-power spectrum and a cross-power spectrum of each moment signal in the acceleration response signal of the engineering structure; 3, for each instant, selecting an instant power spectrum function of a specific time period by using a sliding window with a certain length; 4, calculating to obtain a mean power spectrum function of the instantaneous power spectrum functions in the selected time period range; and 5, taking the mean power spectrum function as input of polymax, and combining the stability diagram and clustering analysis to obtain an instantaneous modal frequency and a vibration mode coefficient. According to the non-linear structure frequency and vibration mode coefficient identification method based on the sliding window power spectrum and the Polymax, the outstanding advantages of the Polymax in conventional conditions, large damping and dense modal analysis can be effectively played, and the defects of an existing method in the aspects of analysis parameter selection and model overfitting can be overcome.

The invention discloses a MUSIC spatial spectrum calculation method and device based on an FPGA, and relates to the technical field of signal process.The method comprises the steps that firstly, a subspace formed by signal steering vectors in a two-dimensional search spectrum function in a MUSIC algorithm is converted into a steering vector calculation formula, the steering vector calculation formula is divided into four operation formulas according to mathematical operation, and the four operation formulas are used for calculating the spatial spectrum of the MUSIC; calculating the four operation formulas to obtain values of A, B, C and D, obtaining a subspace spanned by a signal steering vector based on the values of A, B, C and D, deforming a two-dimensional search spectrum function in the MUSIC algorithm based on the subspace spanned by the signal steering vector to obtain sum operation for solving an absolute value, and calculating the sum of the absolute value. And accumulating numerical calculation results based on sum operation of absolute values to obtain a spatial spectrum value under the current search angle. The operation speed of the MUSIC algorithm is improved by redesigning a calculation process suitable for FPGA architecture characteristics, the change can be responded more quickly by adopting the FPGA, and an instant and accurate direction estimation result is provided.

This invention discloses a satellite navigation multi-interference source localization method and related apparatus, comprising: acquiring received signals from each observation station in the observation system; acquiring the acquisition covariance matrix of each observation station in the observation system; constructing a power spectrum function based on the received signals and acquisition covariance matrix of each observation station; constructing a target cost function based on the power spectrum function; solving the target cost function based on the power spectrum function to obtain a global maximum; drawing a target cost function plane diagram based on the global maximum; and locating multiple interference sources based on the target cost function plane diagram. This method and related apparatus can locate multiple interference sources and have the characteristics of low computational complexity, high positioning accuracy, and high speed.

The application provides a power distribution network cable fault detection and positioning method with anti-noise enhancement. By injecting a multi-cycle test signal and collecting the reflected signal, combining the m sequence denoising characteristics and the adaptive wavelet transform, the multi-cycle reflected signal is denoised and normalized to improve the signal quality. The multi-cycle secondary cross-correlation weighted power spectrum function is averaged, and the anti-noise enhanced fault positioning is realized through IFFT processing. At the same time, the time domain features (such as amplitude, phase, envelope) of the filtered signal of the first cycle are extracted, and the final secondary cross-correlation weighted power spectrum function IFFT value is fused into a high-dimensional feature vector, which is input into a deep learning model based on convolutional neural network, LSTM and attention mechanism. The attention mechanism weights the secondary cross-correlation weighted power spectrum function IFFT value, extracts the peak value feature, and improves the positioning accuracy. The method realizes accurate classification and positioning of cable faults, has high precision and anti-interference ability, and is suitable for cable fault detection in complex environments, providing technical support for stable operation of the power system.

The present application relates to a kind of CZT frequency estimation methods, comprising the following steps: S1: the signal to be estimated is sampled, and the maximum spectral line value of the FFT spectrum function is extracted from the frequency index of the FFT spectrum function obtained by the N-point fast Fourier transform of the discrete time domain signal after sampling;S2: the frequency interval of the CZT transform is determined according to the value of the frequency index, and the maximum spectral line value of the CZT spectrum function is extracted from the CZT spectrum function obtained by the discrete time domain signal and the left and right two spectral line values of the CZT spectrum function;S3: the relationship parameter between the maximum spectral line value and the left and right two spectral line values is calculated;S4: error is calculated from the relationship parameter;S5: the estimated frequency of the signal to be estimated is calculated according to the relationship parameter and error.

The present invention relates to a refined frequency estimation method based on an ESPRIT algorithm, comprising the following steps: S1 searching for M0 peak points of the FFT spectrum function amplitude of a signal to be estimated, obtaining a frequency index at each peak point, and obtaining an initial frequency estimation value of each peak point of the signal to be estimated; S2 determining the current refined frequency interval of the ESPRIT algorithm for each peak point; S3 performing complex modulation on the signal to be estimated within the current refined frequency interval to obtain a frequency shift signal; S4 performing digital low-pass filtering on the frequency shift signal to obtain a frequency band sequence to be analyzed; S5 estimating the number of real signals within the current refined frequency interval of each peak point to obtain an optimal refined frequency interval for each peak point; S6 using the ESPRIT algorithm to estimate the frequency of each signal within the optimal refined frequency interval of each peak point to obtain a final frequency estimation value of each signal at each peak point.

The application particularly relates to a simulation method of a completely non-stationary wind field of a mountain bridge, which comprises the following steps: obtaining an evolution power spectrum function of a completely non-stationary wind field of a bridge to be simulated; determining representative interpolation nodes based on the evolution power spectrum function; the interpolation nodes comprise time domain interpolation nodes and frequency domain interpolation nodes; performing Cholesky decomposition on the interpolation nodes to obtain corresponding node Cholesky decomposition values; then further decomposing the node Cholesky decomposition values into a series of time and frequency function products by a non-negative matrix decomposition method; applying a Hermite interpolation method to establish global time and frequency interpolation functions; and generating a simulation high-efficiency calculation expression of the corresponding completely non-stationary wind field of the bridge based on the global time and frequency interpolation functions, so as to realize the simulation of the completely non-stationary wind field of the mountain bridge. The simulation method in the application can adapt to the completely non-stationary wind field, can take into account the time-varying frequency characteristics and spatial correlation of the wind speed field simulation, and can improve the practicability and efficiency of the bridge wind field simulation.

The embodiment of the invention provides a shear wave velocity prediction method and device for a heterogeneous fractured reservoir and electronic equipment. The method comprises the steps of performing two-dimensional Fourier transform on a spatial autocorrelation function to obtain a corresponding power spectrum function; performing phase randomization on the power spectrum function to generate a frequency domain random field; performing inverse Fourier transform on the frequency domain random field to generate a spatial random field; the mean value and the standard deviation of the initial fracture density are determined based on the logging data, the spatial random field is converted into a fracture density random field based on the mean value and the standard deviation of the initial fracture density, and the fracture density random field represents spatial distribution of fractures in the horizontal direction and the vertical direction; and constructing a saturated fracture rock physical model based on the fracture density random field and predicting the shear wave velocity. Meanwhile, the heterogeneous characteristics in the horizontal direction and the vertical direction are considered, more accurate parameters are provided for rock physical modeling, more real fracture density distribution is provided, and therefore prediction is closer to the actual value.

The invention discloses a terahertz dust observation radar echo noise reduction method, which comprises the following steps of: 1, acquiring a power spectrum function, eliminating a leakage signal in the power spectrum function to obtain the power spectrum function of which the leakage signal is eliminated, and estimating a mean value and a standard deviation of background noise; 2, dividing the power spectrum function for eliminating the leakage signal by adopting the mean value and the standard deviation of the background noise, and endowing an initial value to a power spectrum mask corresponding to the power spectrum function for eliminating the leakage signal; and step 3, identifying and eliminating the ground clutter in the power spectrum mask to obtain a power spectrum mask for eliminating the ground clutter and a power spectrum for eliminating the ground clutter corresponding to the power spectrum mask for eliminating the ground clutter. And step 4, performing multi-scale spatial domain filtering on the power spectrum function of which the ground clutter is eliminated, eliminating random noise by updating a power spectrum mask, and converting the updated power mask into a denoised power spectrum function to calculate intensity distribution information of the sand and dust meteorological target.

The invention discloses a direction of arrival estimation method and device, electronic equipment, a medium and a program product. The method comprises the following steps: acquiring a noise subspace matrix and a pseudo-spectral function when an antenna array receives a target signal; determining an angle estimation interval of the target signal based on the spectrum characteristics of the noise subspace matrix; and determining a final incident angle of the target signal in the angle estimation interval based on the extreme point of the pseudo-spectral function. According to the method, the final incident angle is determined in the angle estimation interval, so that the search range of the target signal angle is reduced, search in a full-angle range is avoided, the calculation amount is reduced, and the determination accuracy of the final incident angle is improved.

The invention discloses a two-dimensional DOA estimation method and system based on a V-shaped semi-symmetric co-prime array, and the method comprises the steps: forming a VSSCA array structure receiving signal through the optimization design of a VCA, and obtaining an axis of the VSSCA array structure and a receiving signal corresponding to the axis; secondly, covariance matrixes of the received signals are calculated respectively, and corresponding virtual arrays are obtained after vectorization processing, sorting and redundancy elimination operation are carried out; then continuous virtual arrays are extracted from the virtual arrays, and covariance matrixes corresponding to the continuous virtual arrays are calculated respectively; and finally, respectively carrying out eigenvalue decomposition to obtain corresponding noise subspaces, constructing a MUSIC spectral function based on the noise subspaces, obtaining a joint DOA estimated value through one-dimensional spectral peak search, and calculating a DOA estimated value of an information source. According to the structure provided by the invention, when two-dimensional parameter estimation is realized, more signal sources can be analyzed with a smaller number of physical array elements, and the estimation precision and stability are remarkably improved.

The invention provides an aircraft riding quality evaluation method and system, an electronic product and a medium thereof, and aims to establish an aircraft normal overload turbulence response function, establish an aircraft turbulence frequency spectrum function, establish an aircraft normal overload frequency spectrum function based on the aircraft normal overload turbulence response function and the aircraft turbulence frequency spectrum function, and then establish a normal overload frequency weight function to evaluate the riding quality of an aircraft. And establishing an aircraft riding quality frequency spectrum function by using an aircraft normal overload frequency spectrum function and a normal overload frequency weighting function, calculating the aircraft riding quality according to common frequency integral, and evaluating the aircraft riding quality, so that a more reliable means is provided for evaluating the aircraft riding quality, and the aircraft design can be better served.

The application discloses a kind of DOA estimation methods of coherent sources under symmetric array mutual coupling condition, comprising the following steps;With central symmetry MCM is split into several partial matrix difference form;Obtain the reconstruction matrix corresponding to each partial matrix uniquely;Through array flow matrix, the projection matrix of signal subspace is calculated, then the orthogonality of noise subspace and signal subspace is used to construct spectrum function to search spectrum peak and realize preliminary estimation to DOA;The preliminary angle value estimated is used to carry out iterative search to estimate MCM, then the array flow of next iteration is calculated by the MCM estimated, and the projection matrix of signal subspace is constructed to carry out DOA estimation again;Iterative search is carried out multiple times until the termination iteration condition is satisfied.The application not only realizes the purpose of improving the estimation accuracy of DOA and MCM under the condition of low signal-to-noise ratio and snapshot number, but also can achieve good estimation effect when estimating DOA of similar coherent sources.

The application provides a signal arrival angle estimation method and device for a mixed field source, the method comprising: for a mixed field source in an indoor single base station scenario, constructing a fourth-order cumulant matrix that has eliminated the influence of the distance of the source; constructing a MUSIC spectrum function based on the fourth-order cumulant matrix, and applying the MUSIC spectrum function to obtain an estimated value of the signal arrival angle of the mixed field source to the antenna array for 5G positioning. The application can be effectively applied to an indoor single base station positioning scenario, and can estimate the signal arrival angle of the mixed field source containing the mixed field source in the far field region and the near field region of the antenna array, can improve the reliability and effectiveness of the signal arrival angle estimation process of the mixed field source, and can effectively improve the estimation accuracy of the signal arrival angle in the mixed field source scenario.

The application discloses a kind of single-channel track angular momentum modal spectrum estimation methods based on time modulation, comprising the following steps;Step 1: establish the OAM modal spectrum estimation mathematical model based on time modulation array, obtain modulation function;Step 2: single-channel signal is carried out digital filtering, and harmonic signal is obtained;Step 3: it is reconstructed to equivalent multi-channel receiving signal by least square method;Step 4: based on multi-channel receiving signal, the signal covariance matrix is calculated;Step 5: the eigenvalue decomposition of matrix is carried out to signal covariance matrix, and signal subspace and noise subspace are orthogonal;Step 6: modal spectrum function is constructed and modal search is carried out, high-resolution estimation is realized;Step 7: the amplitude of each modal spectrum is calculated, and the final result is the energy distribution of the carrying modal spectrum of target signal.The application has the characteristics of high resolution, low hardware complexity, without array special structure, can simultaneously estimate any type of multi-modal OAM wave.