196results about How to "Improve estimation efficiency" patented technology

The invention provides a power battery electric charge quantity estimation method. The method includes the following steps of firstly, obtaining the function relationship between the SOC and an open-circuit voltage through an open-circuit voltage method; secondly, measuring the initial value of the SOC; thirdly, sampling and obtaining the SOC estimated initial value of an unscented Kalman filter; fourthly, conducting Sigma point sampling of UT conversion of the unscented Kalman filter according to a battery state equation and an observation equation, obtaining an estimated value of the observation quantity, and estimating an SOC estimated value and a covariance of a power battery at the next moment. According to the method, the open-circuit voltage method and the unscented Kalman filter are used in cooperation for conducting SOC estimation, the estimation accuracy is high, the SOC initial value is obtained through the open-circuit voltage method, SOC estimation modification is conducted, the estimation accuracy is improved, and in the unscented Kalman filter non-linearization approximation process, errors are reduced, the calculation speed is high, and the SOC estimation efficiency is improved.

The invention belongs to the technical field of digital signal processing and provides a linear frequency-modulated parameter estimating method with high precision, low complexity, high speed and high efficiency and an implementing device thereof. The invention adopts a technical scheme that: by means of an energy barycentre interpolation estimation and Radon ambiguity transformation (RAT) based modulating frequency estimating method, the method mainly comprises the following steps of: for a given input signal s(n), calculating an ambiguity function AFs(tau, xi) of the input signal s(n); exchanging scanning straight lines xi=k tau continuously; figuring out the projection of AFs(tau, xi) on the scanning straight lines by means of Radon transformation; recording all projection values; constructing a panorama discrete spectrum; searching out the peak position of the panorama discrete spectrum; estimating the projection value of the actual peak value; obtaining the estimated value of thesignal modulating frequency; searching out the peak value spectrum of a fractional order Fourier spectrum; and figuring out the energy barycentre position of the spectrum so as to estimate the signalbarycentre frequency. The method is mainly applied to the linear modulating frequency signal parameter estimation in the digital signal processing.

The invention provides a method for inverting effective leaf area index by utilizing geometric projection and laser radar and belongs to the field of research on methods for acquiring forest canopy structure parameter. The method includes the following steps: acquiring and preprocessing three-dimensional laser point cloud data of a plant canopy layer, converting a coordinate system of point cloud data, utilizing different geometric projections to project the three-dimensional point cloud data into a two-dimensional plane space and convert the data into a grid image and further utilizing the linear least square inversion algorithm to conduct estimation of porosity and effective leaf area index. Compared with a traditional observation method, the method is small in work amount and free of contact type observation and damage to the canopy structure and radiative characteristics, has the advantages of being objective, high in efficiency and accurate. A method for extracting three-dimensional structure and biological physical diversity information from laser radar data is developed, and characterization is conducted on the horizontal and vertical distribution change rule of leaves.

The invention provides a two-stage linear weighted least-square power system state estimation method which is characterized by comprising the following steps of: forming a network model, and calculating a node admittance matrix and a branch-node relationship matrix; transforming a measurement vector and a state vector; forming an accurate linear measurement equation; performing the first stage of linear weighted least-square estimation to obtain the estimated value of the transformed state vector; performing inverse transformation, and performing the second stage of linear weighted least-square estimation to obtain the estimated values of the voltage amplitudes and phase angles of all nodes; and identifying bad data. According to the two-stage linear weighted least-square power system state estimation method provided by the invention, more scientific state estimation result can be obtained, the calculation efficiency is higher, and the engineering application prospect is good.

The invention relates to a hearing aid device and method, in particular to the hearing aid device and method for separating and positioning sound sources in noise environments. The hearing aid device comprises a microphone array, a sound source position displayer, a sound source separating and positioning module, a signal collector, an analog signal amplifier and a sound source selection keyboard. The sound source separating and positioning module adopts a cross-correlation method to process the collected microphone signals to obtain eight initial positions of the sound sources relative to the microphone array, the collected microphone signals are processed through a blind source separation method based on space search to obtain sound sources containing voices of a talker and other persons, a user selects out the sound sources containing voices of the talker through the sound source selection keyboard and computes the accurate position of the talker relative to the microphone array according to the selected sound source, and the position of the sound source is displayed in the sound source position displayer. By means of the hearing aid device and method, voice signals of two persons involving in the conversations in the noise environments can be separated automatically, and a positioning function of a sound signal source is added. Furthermore, the hearing aid device and method for separating and positioning sound sources in noise environments are convenient to use.

The invention discloses a human face pose estimation method. The method comprises the steps of inputting to-be-estimated human face pose images; according to a first classification model, performing coarse classification on the to-be-estimated human face pose images, thereby identifying whether the to-be-estimated human face pose images are full side face human face images; when the first classification model identifies that the to-be-estimated human face pose images are the full side face human face images, outputting the to-be-estimated human face pose images as full side faces; when the first classification model identifies that the to-be-estimated human face pose images are not the full side face human face images, performing fine classification on the to-be-estimated human face pose images according to a second classification model; and outputting human face pose values of the to-be-estimated human face pose images. The invention furthermore provides a human face pose estimation apparatus, a terminal and a storage medium. The human face pose estimation from the coarse classification to the fine classification is realized; the human face pose estimation efficiency is improved;and a relatively good human face pose estimation effect is achieved.

The invention provides a method for calculating the extinction coefficients of a three-dimensional forest canopy under any given incident ray by using a geometric algorithm, belonging to the research field of a method of acquiring the structural parameters of the forest canopy. The method for calculating the extinction coefficients of the three-dimensional forest canopy by using the geometric algorithm comprises the following steps: acquiring and preprocessing the three-dimensional laser-point cloud data of a plant canopy; carrying out three-dimensional gridding on the point cloud data; carrying out point cloud slice arithmetic based on a voxel data structure; carrying out linear sampling analysis on the point cloud slices; calculating an average projection coefficient of a kth layer of slices; and calculating the extinction coefficient of any given incident ray in each layer of slices and the extinction coefficient of whole canopy. Compared with the traditional observing way, the invention has the characteristics of being small in working amount, and free from the contact observation and the damage of the canopy structure and radiation, and has objectiveness, high efficiency and precision; a method of extracting the three-dimensional structures and biological and physical diversity information from the laser radar data is developed to characterize the horizontal and vertical distribution change rules of the leaves.

The invention relates to a step frequency inverse synthetic aperture radar (ISAR) imaging method based on coherent processing. The method mainly solves the problems in a traditional parameter estimation method of being low in calculating efficiency and having large effects of phase error on frequency synthesis after envelope compensation. The method includes the steps: building a step frequency ISAR echo signal model; conducting motion parameter estimation according to the echo signal model; constructing a penalty function and compensating a sub-pulse envelope of echo signals; conducting frequency synthesis based on coherent processing on the compensated echo signals; conducting inverse fast Fourier transformation (IFFT) on the synthesized echo signals, and obtaining a high-resolution range profile; and conducting direction imaging through an RD algorithm or an RID algorithm to obtain a directional high-resolution image. Experiments prove that the method has the advantages of being high in phase error compensation precision and calculation efficiency and can be used for achieving two-dimensional high-resolution ISAR imaging of a target.

The invention discloses a compressed sensing based sparse channel estimation method in a two-way relay network. The method includes: according to actual signals received in a second time slot by a current user terminal and a Gaussian random training sequence sent by each user terminal in the two-way relay network, subjecting an equivalent channel vector between the current user terminal and a relay node to channel iterative loop estimation to obtain a channel estimation value; and using a weighted least square estimation method during channel iterative loop estimation to continuously weaken influences of abnormal samples corresponding to positions with large residual values after the last iteration and enhance attention to favorable samples corresponding to positions with small residual values, so that precision and robustness in sparse two-way relay channel estimation can be effectively improved. Further, since the compressed sensing based sparse channel estimation method in the two-way relay network makes full use of potential sparse characteristics of two-way relay channels, the Gaussian random training sequences required by estimation can be greatly reduced, estimation efficiency is improved, and energy and bandwidth utilization rate is greatly increased.

The invention relates to a big data environment-oriented summary information dynamic constructing and querying method and a device. According to the method, based on a Count-Min Sketch method, data scale is described by a first norm of a dataflow, and the distribution situation of data is described by a cardinal number value of data; the method comprises the following steps of distributing a smaller space of Count-Min Sketch structure to streaming big data; along with the continuous loading of data, establishing a new Count-Min Sketch structure for receiving subsequent new data when a data item number recorded by the Count-Min Sketch structure reaches a threshold value and a numerical value space cardinal number reaches a threshold value. By utilizing the method, the new Sketch structure can be established automatically according to data size and the numerical value space cardinal number, so as to count data with higher precision, and effectively support high-precision real-time counting and analysis of the streaming big data.

The invention discloses a cardinality estimation method aiming at streaming big data. The method is characterized in that cardinality estimation efficiency is increased by lowering calculation precision; partition calculation is performed on the intermediate statistical information needed by as HyperLogLog Counting algorithm, an efficient Hash algorithm and an optimal bucketing number are selected, an improved bucketing method is used to evenly map hashed data into different bucket numbers, increment maintenance is performed, and combination is then performed to obtain the final intermediate statistical information so as to calculate a cardinality estimation value. The method has the advantages that historical data is effectively utilized, repeated calculation is avoided, and the cardinality estimation efficiency is increased greatly; high-precision cardinality estimation is achieved, and the efficient bucketing method is provided as compared with a traditional algorithm; the algorithm is quite low in space complexity, and calculation resource consumption is lowered.

The invention discloses a method for estimating two-dimensional human gestures and a device for estimating the two-dimensional human gestures. The method comprises: firstly, detecting human areas in a two-dimensional image, determining hunting zones of each body part in the two-dimensional image, and then respectively searching optimal locations of each body part in the hunting zones of each body part according to the similarity degree between each location and body part templates in the hunting zones of each body part and the constraint relation between prearranged neighboring body parts. Compared with the prior art, the invention does not need to use a large amount of parameters which are obtained through training in advance and does not need to search the location of each body part in the whole two-dimensional image, and thereby the efficiency of estimating the two-dimensional human gestures is improved.

Embodiments of the invention disclose a data processing method and apparatus, a storage medium and an electronic apparatus. The method comprises the steps of obtaining a target sample, wherein the target sample comprises feature data of a target media file during current exposure and historical information associated with the feature data, the feature data is used for determining a probability ofexecuting target operation on the target media file, multiple characteristics comprised in the feature data have a nonlinear relationship, and the historical information is used for indicating information of the target media file corresponding to the feature data in a past predetermined time period; performing deep learning training on a predetermined model by using the historical information to obtain a trained target model; and through the target model and the feature data of the target media file during the current exposure, determining a probability of executing the target operation on thetarget media file after the current exposure. The technical problem of low efficiency of estimating the operation on the media file in related technologies is solved.

The invention discloses a candidate PDCCH priority determining and monitoring method and device, a storage medium, a base station and a terminal. The candidate PDCCH priority determining method comprises: for search space sets of the same type, determining the first priority of the search space sets according to the number of non-overlapping CCEs in each search space set; and for the search spacesets with the same first priority, determining a second priority of the search space set according to the size of the identifier of each search space set and / or the format of the downlink control information in each search space set. According to the technical scheme, the priorities of the PDCCHs in the same type of search space set can be configured, so that the UE monitors the PDCCHs according to the configured priorities, and the blind detection success rate is increased.

The invention discloses a radiation source time difference positioning method having a passive detection observation station position error. The radiation source time difference positioning method is characterized in that (1) a time difference is extracted; (2) a time difference positioning direct linear equation system is constructed; (3) a linear mapping matrix of a passive detection observation station position error disturbance is constructed; (4) a linear mapping matrix of a time difference measurement error disturbance is constructed; (5) a linear mapping matrix of an error disturbance is constructed; (6) a radiation source position is estimated. A time difference positioning direct linear model is adopted, and the position error of the passive detection observation station is considered, and the radiation source time difference positioning method is used for the radiation source passive positioning of the passive detection observation station.

The present invention provides a method of estimating a frequency offset. The method comprises receiving a wireless signal timed according to a first frequency; generating a local signal timed according to a second frequency; and performing a plurality of synchronization searches, each search comprising obtaining a set of correlation results indicative of a correlation between the wireless signal and the local signal at different timing offsets of the wireless signal relative to the local signal. The method the no comprises finding a series of results, with a result from each of a plurality of the synchronization searches, for which the difference in; timing offset between results from adjacent searches in the series is within a maximum specified value. A frequency off set between the first and second frequencies can be determined from the series.

The invention discloses a method for estimating terrain by the polarization interference of the data of a synthetic aperture radar and a software thereof, which relate to synthetic aperture radars. The method comprises the following steps of: (A) filtering polarization interference data; (B) distinguishing different land types by utilizing a polarization classification technique; (C) dividing the data into the land types to form a plurality of simple subblocks; (D) estimating the terrain interference phase of each subblock respectively; (E) processing the terrain interference phase of each subblock in parallel and estimating the terrain of each subblock; and (F) combining the terrain of each subblock and calculating an integral terrain result. The method and the software introduce the polarization classification technique, divide the data into the land types to form a plurality of simple subblocks for processing, adopt different polarization interference methods according to the difference of the land types contained in the subblocks to estimate the terrain interference phases and then calculate the terrain of each subblock. The method not only lowers the difficulty of estimating the terrain of the complicated areas formed by the land types but also enhances the estimation efficiency of the terrain of this class of areas.

The invention provides a microwave photon array-based ultra wideband signal direction of arrival estimation method, so as to solve the technical problems of low ultra wideband signal direction of arrival estimation efficiency and low estimation precision existing in the prior art. The method comprises steps: 1) a first-order sideband signal E0(t) is acquired; 2) a microwave photon array D is built; 3) the light power Pm of an ultra wideband signal Em outputted by the microwave photon array D is acquired; 4) a light power ratio vector Q is defined; 5) an M*Ntheta-dimension matrix as described in the specifications related to an array flow pattern vector as described in the specifications is defined; 6) the phase phim of the ultra wideband signal Em outputted by the microwave photon array Dis acquired; and 7) the direction of arrival thetam of the ultra wideband signal Em outputted by the microwave photon array D is calculated.

The invention relates to a joint estimation method of frequency offset, DC (Direct Current) and imbalance of an orthogonal frequency division multiplexing system, is suitable for the field of digital signal processing, especially the joint estimation of carrier frequency offset (CFO), DC offset (DCO) and I / Q imbalance (I / Q imbalance) of the orthogonal frequency division multiplexing (OFDM) system of a direct conversion receiver. The invention provides an estimation method of CFO, DCO and I / Q imbalance of an eigen-decomposition based estimator (EDE). Compared with the previous estimation method, the estimation method provided by the invention does not depend on specific lead code and pilot frequency, and is suitable for more general situations in the OFDM system, the bandwidth is not occupied, and the estimation efficiency is higher.

The present invention is applicable to the field of information push, and provides a method and device for estimating the click-through rate of an advertisement. The method includes: obtaining user characteristics and advertisement characteristics of advertisement information to be pushed, and encoding to obtain user characteristic vectors and advertisement characteristic vectors; The limited BFGS algorithm uses interactive fixed parameters to iteratively calculate the weight vector in the logistic regression algorithm; estimates the click-through rate of the advertisement information according to the weight vector, user feature vector and advertisement feature vector. Compared with the prior art, the method of iterating through interactive fixed parameters in the present invention can effectively constrain the parameters and avoid the over-fitting problem in the logistic regression algorithm, thereby improving the efficiency of estimating the click-through rate of advertisements and improving the accuracy of estimating .

The invention discloses a parameter estimation range expansion method of a sea clutter Pareto distribution model. The method mainly solves the problem of effective estimation range limitation during the sea clutter shape parameter estimation in the prior art, and uses the realization scheme of 1, building a Pareto distribution model f<N>(z) of the sea clutters according to the composite model theory of the sea clutters; 2, using the Pareto distribution possibility density function of the sea clutters in N times of observation to deduce the r-odor origin matrix estimation expression <z<r>> of the practical observation value z of the sea clutters; 3, enlarging the value range of the r to the negative number range; estimating the sea clutter shape parameter alpha to obtain the estimated expression of the alpha; 4, when the observation times N is greater than 2, estimating the Pareto distribution parameter of the shape parameter in the range that alpha is an element of a set from 0 to positive infinity. The parameter estimation range expansion method has the advantages that the shape estimation range of the sea clutters is effectively enlarged; the estimation efficiency is improved; the method can be used for target detection.

The invention discloses a millimeter-wave system channel estimation method low in complexity. The method includes the following steps: firstly, a receiving end uses a first-order codebook to estimatea pair of azimuths AOA and AOD, and then establishes a set on the basis of the defined quantization precision estimated the second time and the number of quantization angles estimated the second time;secondly, the receiving end uses the set obtained in the first step and also a second-order codebook to conduct azimuth estimation at the second-order precision; and thirdly, the receiving end utilizes a least square method to estimate fading of channels corresponding to the azimuths, and determines whether channel estimation is carried out according to a result. Through utilization of sparsity of a millimeter-wave system channel and redundancy of a sparse dictionary in a compression sensing technology, a channel estimation process is quantified through angles to be decomposed into two-complexity channel estimation processes. According to the method, the number of searching of the sparse dictionary is reduced, the millimeter-wave system channel estimation efficiency is increased, and thechannel estimation complexity of channel estimation is reduced effectively while the estimation precision is guaranteed.

The invention relates to a method for improving base station location success rate. By means of the method, location information of a base station and a list of neighbor base stations are loaded when a mobile locating system loads base station information, for any base station with unknown location, the location information of the base station is estimated through location information of neighbor base stations in the neighbor base station list, the estimated location information is used in location calculation of the mobile locating system, the neighbor base station list for estimating the location information of the base station with unknown location is composed of part of or all of base stations with known location of the neighbor base stations of the base station with the unknown location, and the estimation method can be a centroid method, an outer center method and the like. In addition, direction information and / or height information of the neighbor base stations can be loaded for further improving the estimation accuracy, and requirements for high location accuracy can be met. By means of the method, the location of the base station can be estimated through the location information of the neighbor base stations under the condition that the location information of the base station is not timely loaded or updated, and accordingly the success rate of mobile location can be effectively improved.

The invention provides a method for utilizing an aviation laser point cloud to calculate an effective leaf area index, and belongs to the research field of a forest canopy structure parameter obtaining method. The method comprises the steps of: obtaining and preprocessing three-dimensional laser point cloud data of a vegetation canopy; obtaining quadrat scale point cloud data having no ground point cloud data but having a ground height by means of a digital landform model; carrying out three-dimensional meshing on the point cloud data; under different scanning angles, respectively obtaining directional porosities directional extinction coefficients and directional effective leaf area indexes; and according to the effective leaf area index obtained under each scanning angle and the weight of the angle, obtaining the forest canopy effective leaf area index. Compared with other leaf area index calculating methods, the influences of scanning angle information on the directional porosities, the extinction coefficients and the effective leaf area indexes are fully considered; the canopy structure and the radiation characteristics are not destroyed, and the method is objective, effective and precise; in addition, the method for extracting a three-dimensional structure and biophysical diversity information from laser radar data is further developed.

The invention provides a method for estimating SOC of a lithium iron phosphate battery pack using a BP neural network. The BP neural network adopts a hidden layer, three inputs, and one output networkstructure, and the number of nodes of the hidden layer is 11. The estimation method comprises the following steps: adjusting a connection weight adjustment link of the BP neural network, inserting aninertia coefficient, using smooth weighted calculation to improve the connection weight adjustment, increasing an original connection weight item when performing the connection weight adjustment calculation, and giving a heavier weight. The method uses the current integral correction method to change the parameters of the BP neural network, which reduces the influence of the capacity decay of thelithium iron phosphate battery pack on the SOC estimation accuracy.

The invention relates to the field of signal processing, and provides a frequency domain-based Doppler compensation method for I-OFDM MIMO radar signals. The method includes the steps of firstly, establishing an MIMO radar mathematics model; secondly, sampling continuous waves obtained by a receiving end; thirdly, solving DFT of an echo signal obtained from the previous step; fourthly, calculating a Doppler compensation matrix; fifthly, estimating a Doppler frequency value; sixthly, calculating the compensation matrix through the obtained frequency estimation value; and seventhly, multiplying the signal frequency spectrum obtained from the step 3 by the compensation matrix, and performing IDFT. The Doppler frequency value of the echo signal is estimated, so FFT and IFFT calculation through multiple branches for many times in a conventional method is avoided, and the calculation workload is reduced. Moreover, through combination of the characteristics of DFT and IDFT transformation of reception signal, the compensation matrix is derived creatively in a matrix form, so calculation of the compensation matrix is simplified, and the speed of Doppler compensation is increased.

The invention belongs to the technical field of accelerated life tests (ALT) and particularly relates to a simplified MLE method for parameters in Weibull distribution comprehensive constant-stress accelerated life tests. The simplified MLE method for Weibull distribution comprehensive constant-stress accelerated life test data is given against the problems that the test cycle of a single-stress ALT is long and it is difficult to solve maximum likelihood estimation of Weibull distribution parameters, and the feasibility and effectiveness of the given simplified MLE method for the Weibull distribution comprehensive constant-stress accelerated life test data and reliability assessment are verified by performing statistical analysis on Monte Carlo simulation failure time of the comprehensiveconstant-stress accelerated life tests of an aerospace electric connector.

The present invention provides a channel estimation method and apparatus based on implicit training sequences for use in wireless communication systems, characterized in that stationary training sequences are superimposed with information sequences for transmission at the transmitting side and channel estimation is performed at the receiving side by using the uncorrelated characteristic between the training sequences and the information sequences, that is, channel estimation is done based on the principle that the estimation result of channel parameter converges to a Wiener solution under the condition that the training sequences and information sequences in the transmission signals are uncorrelated.; The method of the invention comprises steps of: obtaining a set of training sequences comprising a plurality of subsets of training sequences, each of the plurality of subsets is generated based on a known initial training sequence and a predetermined channel order; calculating the cross-correlation matrix for the subsets of training sequences and the corresponding inverse matrix; calculating the cross-correlation matrix for the set of training sequences and the received signals; and estimating channel parameters based on the inverse cross-correlation matrix for the subsets of training sequences and the cross-correlation matrix for the set of training sequences and the received signals.

The invention belongs to the field of lithium batteries, and discloses a distributed battery pack state of charge estimation algorithm. Through designing a distributed state of charge estimation method, the calculation amount for estimating the state of charge of a single cell in the battery pack is reasonably distributed. Through the cooperation of a master controller and several slave controllers, the states of charge of all battery cells in the battery pack can be quickly acquired, and substantially, the battery pack state of charge estimation calculation efficiency and the reliability areimproved.

The invention discloses a phase estimation method for a short-interval sinusoidal signal and an experimental device thereof. The CiR (cycles in record) of the tested sinusoidal signal is less than 1. The method comprises the following steps: sampling an inputted sinusoidal signal x(n)=Acos(2pif0+theta0) at an equal interval to obtain 2N-1 discrete sample sequences x(n); carrying out analytic transformation on the x(n) to obtain a complex sequence x1(n), and carrying out triangular window weighting and shift superposition to generate a sequence y(n) of which the length is N; computing the inner product of the sequence y(n) and a known sequence to obtain a complex value Q; and calculating the phase angle value of the complex value Q to obtain a phase measurement estimated value. The experimental device comprises a signal conditioning circuit, an A / D (analog-to-digital) conversion circuit, a digital signal processor (DSP), and an output drive and display unit. Compared with the prior art, the invention fills the gap of the short-interval sinusoidal wave phase estimation method within one cycle, has the advantages of high phase estimation precision, low computation quantity, high estimation efficiency and low resource consumption, and greatly saves hardware cost.