42results about How to "Solve a large amount of computation" patented technology

This invention relates to an array cross coupling proofreading and information source direction measuring method for homogeneous round array. This method uses array information disposing technique to estimate round array cross coupling error and information source AOA at the same time. Approaches are as follows: First collects data from each channel and saves it to the system memory. Then the data needs to be adaptive equalizing disposed. Next range the disposed data to a covariance matrix and disassemble it according to their character. After this can get noise subspace consisted of small characterized vector. By using subspace construction expense function, the azimuth angle and cross coupling errors can be figured out. Finally through the complexor from cross coupling error to homogeneous round array, finish the proofreading. This invention can universally apply to cross coupling proofreading and information source direction measuring in radar and communicating field. It is worth to wildly apply.

This invention relates to a method for testing directions of coherent signal sources under non-stable noise background including: collecting data received by channels and storing them in an EMS memory of the system, making adaptive uniform process to data received by the channels to form an array covariance matrix, utilizing a forward space smooth technology to preprocess it smoothly to constitute a forward space smooth covariance matrix and utilizing a forward and backward space smooth technology to smoothly pre-process the matrix to constitute a generalized covariance matrix based on the covariance matrix and a conjugated matrix and carrying out spectrum estimation to the generalized matrix with a sub-space class algorithm to identify a real incident direction of image false peak and signal source and output the real direction of the estimated signal source.

The invention provides a method, a device and a system for positioning a sound source. The method comprises the following steps: acquiring the signal of each microphone in a microphone array, wherein the microphone array is used to collect the sound of a sound source; acquiring controllable power responses of multiple microphone pairs composed of the microphones according to the framing of the signals; acquiring the sum of the controllable power responses of the multiple microphone pairs, and determining the direction angles of the sound source and the microphone array according to the maximum value of the sum of the controllable power responses; and determining the relative position relationship between the microphone array and the sound source according to the direction angles. The problem that the existing controllable power response technology is of low resolution and high computation burden is solved. The real-time performance, stability and accuracy of sound source positioning are improved.

The invention discloses a device and a method for detecting similar texts. The device and the method are used for recognizing the similar texts. The device comprises a Chinese text acquiring unit, a pinyin text acquiring unit, a fingerprint acquiring unit and a detecting unit, wherein the Chinese text acquiring unit is suitable for processing texts so as to acquire Chinese texts; the pinyin text acquiring unit is suitable for transforming Chinese characters in the acquired Chinese texts into pinyin so as to obtain pinyin texts; the fingerprint acquiring unit is suitable for extracting features of the pinyin texts, and forming the feature vector of the pinyin texts by using the extracted features; and the detecting unit is suitable for judging whether the texts to be detected are matched with records in a database or not according to the feature vector. By using the device and the method, the Chinese texts can be obtained by the texts to be detected, then the pinyin texts are obtained, the feature vector of the pinyin texts is formed, whether the texts to be detected are matched with the records in the database or not is judged according to the feature vector, and beneficial effects of reducing operand and accurately recognizing variety of similar texts are achieved.

The invention discloses a non-uniform array design and direction of arrival (DOA) estimation method and mainly aims at solving the problems that arrangement is inflexible and computation complexity isrelatively high in the prior art. A realization process of the method comprises the following steps: according to maximum freedom degree of a nested array, determining head and tail position coefficients of a non-uniform array; calculating position coefficients of all the virtual array element positions meeting the non-uniform array and contained in a differential synthetic matrix; according to the position coefficients, finally obtaining positions of array elements of the non-uniform array; according to received data, calculating a data covariance matrix and vectorizing, so that received data r of a virtual differential synthetic array is obtained; performing redundancy elimination on the r and sorting to obtain received data of a virtual array, and then obtaining a non-singular matrix vof the virtual array; constructing a linear operator, and obtaining a signal subspace by estimating the linear operator; and constructing a selection matrix to obtain a rotation matrix, and finally estimating a direction of arrival by virtue of the rotation matrix. The method disclosed by the invention has the advantages that array configuration is flexible, characteristic decomposition does notneed to be performed on the data covariance matrix and spectral peak search does not need to be performed on the whole airspace angle under the same conditions.

The invention discloses a unite-domain positioning space-time two-dimensional self-adaptive processing method based on data fitting, and relates to radar technology. The method comprises the steps that 1, JDL dimensionality reduction echo data and space-time guide vectors are obtained; 2, a data basis matrix of a distance unit to be detected is constructed; 3, a data basis matrix with targets blocked is obtained; 4, the fitting coefficient of auxiliary echo data is obtained; 5, the minimum fitting error of data of the distance unit to be detected is obtained; 6, unit average constant false alarm rate detection is carried out on the minimum fitting error of the data of the distance unit to be detected. The unite-domain positioning space-time two-dimensional self-adaptive processing method mainly solves the problem that a traditional STAP method is huge in computation burden and strict in sample requirement, reduces the false alarm rate, improves movable target detection probability, and has the good application prospect in measured data processing and STAP performance improvement.

The invention discloses an extension factorization space-time two-dimensional self-adaptive processing method based on data fitting and relates to radar technology. The method comprises the specific steps that 1, dimensionality reduction echo data and space-time guide vectors are obtained; 2, a data basis matrix of a distance unit to be detected is constructed; 3, a data basis matrix with targets blocked is obtained; 4, the fitting coefficient of auxiliary echo data is obtained; 5, the minimum fitting error of data of the distance unit to be detected is obtained; 6, unit average constant false alarm rate detection is carried out on the minimum fitting error of the data of the distance unit to be detected. The extension factorization space-time two-dimensional self-adaptive processing method mainly solves the problem that a traditional STAP method is huge in computation burden and strict in sample requirement, and has the good application prospect in measured data processing and STAP performance improvement.

The invention discloses a quick pulse compression method on the basis of sparse inverse Fourier transformation. A step of inverse Fourier transformation of the traditional frequency-domain pulse compression method is replaced by sparse inverse Fourier transformation on the basis of sparse characteristics of pulse compression output time-domain signals, so that quick pulse compression can be carried out on large time-bandwidth product signals, and the pulse compression computational complexity can be lowered; the proposed quick pulse compression method can be improved when echo signals of targets are weak, Doppler filtering is carried out on the weak echo signals of the targets among pulses at first to improve output signal-to-noise ratios of the signals, then quick pulse compression is carried out on the signals on all Doppler units after Doppler filtering is carried out on the signals, and in other words, sparse inverse Fourier transformation is implemented during pulse compression. Compared with the prior art, the quick pulse compression method has the advantages that the computational complexity can be lowered to a great extent while the performance of the traditional frequency-domain pulse compression method is unchanged, and the weak signals of the targets can be correctly detected.

The invention provides a laser three-dimensional imaging radar ground target point cloud data processing method, which is used for carrying out ground target detection and identification on laser three-dimensional imaging radar point cloud data and outputting a suspected interested target, and comprises the following steps: S1, obtaining a point cloud data set of time and space registration; s2, filtering non-ground point data to obtain a ground point data set; s3, extracting, segmenting and summarizing the data of each ground target, and clustering and dividing the data into respective data subsets to obtain a ground target clustering set; and S4, performing interested target identification based on the ground target clustering set, and outputting the suspected interested target. The method is used for solving the problem of ground target detection and recognition in a complex scene, more three-dimensional information of the target is reserved, the operation speed is increased, and the method is more suitable for point cloud data real-time processing and engineering application.

The invention discloses an array element Doppler domain space-time two-dimensional self-adaptive processing method based on data fitting, and relates to radar technology. The method comprises the steps that 1, array element Doppler domain dimensionality reduction echo data and space-time guide vectors are obtained; 2, a data basis matrix of a distance unit to be detected is constructed; 3, a data basis matrix with targets blocked is obtained; 4, the fitting coefficient of auxiliary echo data is obtained; 5, the minimum fitting error of data of the distance unit to be detected is obtained; 6, unit average constant false alarm rate detection is carried out on the minimum fitting error of the data of the distance unit to be detected. The array element Doppler domain space-time two-dimensional self-adaptive processing method mainly solves the problem that a traditional STAP method is huge in computation burden and strict in sample requirement, and has the good application prospect in measured data processing and STAP performance improvement.

The invention provides an object recognition method and device, wherein, the method comprises the following steps: acquiring a region of interest formed for each scanning depth; wherein the size of the region of interest on the imaging plane is smaller as the scanning depth is deeper; collecting road condition images of the road ahead; a region-wide scan is performed in each region of interest toobtain a recognition result. By using the method, different regions of interest can be formed for different scanning depths, the image range of object recognition can be reduced, the computation amount can be reduced, the object recognition speed can be improved, and the technical problems of large computation amount and long object recognition time caused by only one large region of interest in the prior art can be solved.

The invention provides a data processing method and a storage and calculation integrated chip, the method is applied to the storage and calculation integrated chip, the storage and calculation integrated chip comprises a calculation core, and the calculation core comprises a storage calculation array and a calculation module; the method comprises the steps that the storage and calculation array calculates data of a first neural network which is input into the storage and calculation integrated chip and has a first network attribute; and the calculation module is used for calculating data of asecond neural network which is input into the storage and calculation integrated chip and does not have the first network attribute. By means of the data processing method and device, the problems that in the prior art, in the process of processing the data through a storage and calculation integrated chip, all the data need to be stored in a calculation array for calculation, and consequently thestorage and calculation array is large in calculation amount and high in power consumption are solved.

The invention discloses an image enhancement method, which relates to the artificial neural network field. The method comprises the following steps: acquiring an original image; inputting the originalimage into a preset image enhancement network, and performing step-by-step enhancement on the original image to obtain an enhanced image corresponding to the original image, wherein the image enhancement network comprises at least two levels of sub-networks, the original image is used as input to a first sub-network of the image enhancement network, the first-level sub-network outputs a first-level node image, the node image output by each-level sub-network is used as an input of a next-level sub-network, the last-level sub-network of the image enhancement network outputs a last-level node image, and the last-level node image is used as the enhancement image. The first-level sub-network outputs a first-level node image, and the node image output by each-level sub-network is used as an input of a next-level sub-network. The image enhancement method provided by the invention can effectively improve the convergence of image enhancement operation, reduce the amount of operation required for image enhancement, and improve the operation efficiency and stability of image enhancement.

The invention provides a method for quickly imaging for a double-linear-array three-dimensional imaging synthetic aperture radar on the basis of self-adaption, which aims at the characteristic that an echo wave of an actual double-linear-array three-dimensional imaging synthetic aperture radar only comprises an echo wave signal of a specific curved surface in a three-dimensional space. A self-adaptive curved surface prediction technique is adopted to carry out curved surface prediction and imaging processing aiming at the specific curved surface in the three-dimensional space so as to better solve the problem of large computation workload of the prior imaging method of the double-linear-array three-dimensional imaging synthetic aperture radar. The method can be applied to the fields of the synthetic aperture radar imaging, the earth remote sensing, the geology surveying and drawing, and the like.

The invention provides an MMC capacitor voltage-sharing strategy with low switching frequency and complexity. The MMC capacitor voltage-sharing strategy comprises the steps of S1, rapidly monitoring acapacitor voltage value of each sub-module; S2, determining the number of input and removed sub-modules, and judging the charging and discharging conditions of the input sub-modules in the bridge arm; S3, continuing to use the sorting result of the last period, grouping the sub-modules in the input state and the cut-off state to perform insertion sorting correction for limiting the step number, the step number being determined by the maximum voltage difference, and the larger the difference value is, the larger the step number is; S4, according to the charging and discharging conditions, introducing a retention factor to the capacitor voltage of the corresponding sub-module; S5, merging the two sub-sequences in the input state and the cut-off state in two paths, and updating and recordinga sorting result; S6, generating the trigger pulse. According to the invention, dual optimization of the sorting algorithm operation speed and the device switching frequency is realized, and the problems of large sorting algorithm operation amount and high device switching frequency in the traditional sub-module capacitor voltage-sharing strategy are solved.

The invention discloses a wave beam Doppler domain space-time two-dimensional self-adaptive processing method based on data fitting, and relates to radar technology. The method comprises the steps that 1, wave beam Doppler domain dimensionality reduction echo data and space-time guide vectors are obtained; 2, a data basis matrix of a distance unit to be detected is constructed; 3, a data basis matrix with targets blocked is obtained; 4, the optimal fitting coefficient of auxiliary echo data is obtained; 5, the minimum fitting error of data of the distance unit to be detected is obtained; 6, unit average constant false alarm rate detection is carried out on the minimum fitting error of the data of the distance unit to be detected. The wave beam Doppler domain space-time two-dimensional self-adaptive processing method mainly solves the problem that a traditional STAP method is huge in computation burden and strict in sample requirement, improves movable target detection probability, reduces detection false alarm rate, and has the good application prospect in measured data processing and STAP performance improvement.

The invention provides a high efficiency FIR filter cascade DFT algorithm. Convolution definition is utilized, a calculation formula for R(M+N-1) and I(M+N-1) filtering coefficients of an M-order FIR filter cascade N-point DFT algorithm is derived, after a filtering coefficient after cascade is calculated in an off-line mode, two independent filters are integrated into one filter, calculation efficiency is improved, a problem of large operand caused by filter cascade is effectively solved.

The invention discloses an automatic parking path following processing method and system, a vehicle and a storage medium. The method comprises the steps: 1, planning an arc linear path needed by parking based on parking space information, and obtaining a control point Pi of path planning, i being equal to 0, 1, 2,... N; step 2, performing parametric solution based on a cubic spline interpolation function, and adopting a chord length accumulation method; for the coordinates (xi, yi) of the control point Pi on the plane, solving the accumulated chord length at each control point; step 3, parameterizing x and y into equations of x (s) and y (s) respectively, s being larger than or equal to si and smaller than or equal to si+1, si representing the accumulated chord length of the (i+1)th section, and si+1 representing the accumulated chord length of the (i+2) th section; to be specific, carrying out fitting based on the principle of a cubic spline interpolation function with s as a variableand x and y as functions, and deriving an equation of a chord length accumulation cubic spline curve and first-order derivation and second-order derivation equations of the equation; and step 4, adopting a constraint equation of a fixed boundary for boundary conditions, and solving a first-order derivative of a parameter equation. The problem that the curvature of an arc straight line path is discontinuous is solved.

The invention belongs to the technical field of low-altitude angle measurement engineering, and especially relates to a super-resolution high-precision low-altitude angle measurement method based on the rapid storage technology. The method comprises the steps: carrying out the pulse compression processing of the received radar echo data, carrying out one-to-two processing, carrying out the conventional processing of a radar echo pulse voltage signal, transmitting the processed signal to a rear-end terminal monitoring module, enabling the terminal monitoring module to give the distance and azimuth information of a detection target, and finding the corresponding distance unit data in an angle measurement processing module for angle measurement processing according to the distance and azimuth information of the detection target. According to the invention, the method solves a problem that a conventional super-resolution low-altitude angle measurement technology needs big transmission bandwidth and extremely strong processing capability, and needs to meet the requirements of the real-time performance of a radar. The method is better in popularization capability, and can be widely used for the fields of aviation detection and radar application.

The embodiment of the invention discloses an image processing method. The method comprises the steps of obtaining a first color parameter value of each pixel of a target image in a target color space;wherein the target color space is different from the RGB color space; obtaining a color mapping table of the target color space; and performing color mapping on the first color parameter value of each pixel based on a color mapping table of the target color space to obtain a second color parameter value of each pixel. The embodiment of the invention further discloses an image processing device, electronic equipment and a storage medium.

The invention provides a bus protection surge disturbance identification method and device and a differential protection method and device. The surge disturbance identification method comprises the following steps: when disturbance occurs in an electric power system, sampling each phase of small-difference differential current of each section of bus in an in-situ bus protection system, sampling period being smaller than the period of the small-difference differential current, and the number of sampling points in each sampling period being a first set value; and if the number of sampling points, meeting open criterion, in the sampling points of some phase of small-difference differential current is not larger than a second set value, judging that the disturbance occurring in the system is surge disturbance, wherein the condition that the sampling points meet the open criterion means that the small-difference differential current corresponding to the sampling points is larger than a third set value. According to the technical scheme, the method can judge whether the disturbance occurring in the in-situ system is the surge disturbance only by sampling the small-difference differentialcurrent within one period, is short in data extraction time and small in operation amount, and can solve the problem of large operation amount when carrying out surge disturbance identification.

The invention discloses a quick pulse compression method on the basis of sparse inverse Fourier transformation. A step of inverse Fourier transformation of the traditional frequency-domain pulse compression method is replaced by sparse inverse Fourier transformation on the basis of sparse characteristics of pulse compression output time-domain signals, so that quick pulse compression can be carried out on large time-bandwidth product signals, and the pulse compression computational complexity can be lowered; the proposed quick pulse compression method can be improved when echo signals of targets are weak, Doppler filtering is carried out on the weak echo signals of the targets among pulses at first to improve output signal-to-noise ratios of the signals, then quick pulse compression is carried out on the signals on all Doppler units after Doppler filtering is carried out on the signals, and in other words, sparse inverse Fourier transformation is implemented during pulse compression. Compared with the prior art, the quick pulse compression method has the advantages that the computational complexity can be lowered to a great extent while the performance of the traditional frequency-domain pulse compression method is unchanged, and the weak signals of the targets can be correctly detected.

A method and device for evaluating the influence of grid harmonics, wherein the method for evaluating the influence of grid harmonics includes: obtaining at least one random harmonic sample of a harmonic source in the grid; calculating the power grid based on the random harmonic sample Harmonic power flow data; determine the probability density function of the harmonic power flow data; determine the influence of the harmonic source on the power grid according to the probability density function, and solve the problem that the existing harmonic probability evaluation method has a large amount of computation, The problem of low timeliness.

The invention discloses an automatic parking path following processing method, system, vehicle and storage medium, comprising: step 1, planning out the arc-line path required for parking based on the parking space information, and obtaining the control point P of the path planning i , i=0,1,2,...n; step 2, based on the cubic spline interpolation function to solve parametrically, using the method of chord length accumulation; for the control point P on the plane i The coordinates (x i ,y i ), find the accumulated chord length at each control point; Step 3, parameterize x, y into the equations of x(s), y(s), where s i ≤s≤s i+1 ,s i Indicates the cumulative chord length of segment i+1, s i+1 Indicates the cumulative chord length of the i+2 section; specifically: use s as a variable, x, y as a function to fit based on the principle of cubic spline interpolation function, and derive the equation of chord length cumulative cubic spline curve and its first order Derivative and second-order derivative equations; step 4, the boundary condition adopts the constraint equation of fixed boundary, and solves the first-order derivative of the parametric equation. The invention solves the problem of discontinuous curvature of the arc straight path.

This invention relates to a method for testing directions of coherent signal sources under non-stable noise background including: collecting data received by channels and storing them in an EMS memory of the system, making adaptive uniform process to data received by the channels to form an array covariance matrix, utilizing a forward space smooth technology to preprocess it smoothly to constitute a forward space smooth covariance matrix and utilizing a forward and backward space smooth technology to smoothly pre-process the matrix to constitute a generalized covariance matrix based on the covariance matrix and a conjugated matrix and carrying out spectrum estimation to the generalized matrix with a sub-space class algorithm to identify a real incident direction of image false peak and signal source and output the real direction of the estimated signal source.