31results about How to "Stable estimate" patented technology

The invention relates to an airborne SAR radiation external calibration processing method based on weak arrangement of corner reflectors. The method comprises the following steps: obtaining original SAR image data of a calibration field; on the basis of a point target radar equation, reconstructing an radiation external calibration equation; performing stable estimation on calibrator image energy and geometric optical solution on a calibration RCS; carrying out fitting and correcting on a radar system transfer function to obtain preliminary radiation calibration SAR image data; carrying out the stable estimation on the calibrator image energy and the geometric optical solution on the calibration RCS; and estimating a system constant item so as to generate calibration data and obtain final radiation calibration SAR image data. According to the invention, on the basis of the point target radar equation, according to the characteristic of parameters of a radar system, the SAR radiation external calibration equation comprising a change system transfer function and a constant system constant item is reconstructed, the application process of radiation external calibration is simplified, and the problem is avoided that it is quite difficult for airborne SAR flight to obtain a large-scope homogeneous stable tropical rainforest area frequently used by similar spaceborne SAR radiation calibration.

The invention provides a physical code-channel activation and detection method based on channel estimation post-treatment and a device thereof. The method of the invention comprises the following steps: the power of all windows of the user is acquired; the window with the largest power amongst all windows and the position of the window with the largest power of the user are ascertained; activated windows amongst all windows of the user are ascertained according to the window with the largest power and the position of the window with the largest power; the actual total number of the activated physical code-channels of the user and the corresponding activated physical code-channels are ascertained according to the activated windows and the resource of the physical code-channels distributed to the user by the high level. The method and device of the invention effectively solve the problem of unreliability of estimation of key parameters, such as frequency deviation, etc. caused by lacking of data quantity, thus enhancing the performance of the system.

The invention provides a moving target positioning method which is used for arranging an active moving label on a moving node; a wireless signal sent by the moving label is collected through a readerarranged at a fixed node; information interaction between a server and each reader is carried out, and data preprocessing operation is performed to form a wireless signal gradual change model; specifically, the reader obtains a corresponding signal intensity value from the moving label through a radio frequency identification technology; the signal intensity value is fitted through a non-linear least square method, and an optimized curve after a different-end value is removed is obtained; the curve and the wireless signal gradual change model are subjected to cross-correlation matching to obtain a distance-signal intensity value relation; and the server works out a coordinate position through a weighted centroid positioning method, and then the coordinate position is accurately positionedaccording to non-trace kalman filtering, and a required coordinate point is obtained. By the adoption of the method, the position of the moving target can be stably and accurately estimated.

The invention provides a battery model parameter identification method based on a multi-innovation recursive Bayesian algorithm. The method comprises the following steps of: 1), measuring the terminalvoltage and load current data of a lithium ion battery in a certain period of time through an intermittent constant-current discharge method, and determining the function relation of an OCV-SOC of the lithium ion battery through a polynomial fitting method; 2) determining a dual-polarization equivalent circuit model of the lithium ion battery, and establishing a system equation representing a relation between a battery parameter identification vector and system output; and 3) constructing an identification process of the multi-innovation recursive Bayesian algorithm. According to the method of the invention, an ARX model for lithium ion battery parameter identification is established; the result of the previous moment is corrected by utilizing an innovation correction technology; an innovation length parameter is introduced based on the multi-innovation identification method, so that the influence of bad data on parameter estimation is overcome, and the parameter estimation precisionis improved; and the parameter identification result shows that the method is high in identification precision and has engineering value.

The invention discloses a method for predicting the dead stock column temperature of an iron-making blast furnace core and belongs to the field of metallurgical information processing. The method disclosed by the invention comprises the following steps of firstly, collecting and processing sample data; dividing the processed sample data into a training set and a test set; carrying out principal component analysis on the sample data of the training set, selecting variables according to the correlation between principal components and the variables, analyzing the correlation between sample features and target values by using a parson correlation coefficient, screening the selected variables, and carrying out ridge regression modeling according to the screened variables to obtain a ridge regression model; and then performing goodness-of-fit test on the ridge regression model, and verifying the effectiveness of the ridge regression model by using the test set. The method aims at overcomingthe defects that in the prior art, the calculation process of the furnace core dead stock column temperature of the large blast furnace is tedious and excessively depends on experience. The ridge regression model is established, so that the furnace core dead stock column temperature can be predicted. The calculation efficiency of the furnace core dead stock column temperature can be further improved.

The invention provides a GNSS satellite clock error real-time estimation quality control method aimed at characteristics that real-time clock error estimation has high requirement on observation data quality and cannot perform post residual error edition. The method comprises two aspects: first step, before parameter estimation, preprocessing original observation data, including gross error rejecting and cycle slip detection; second step, after update of filter observation, based on a posttest observed value residual error, analyzing and processing a gross error and cycle slip which are not detected in a previous step, specifically including steps of establishing a square root information filtering algorithm model, processing noise; smoothing square root information; and based on square root information filtering, performing real-time quality control. The method can realize preprocessing of real-time clock error data and efficient quality control, and can efficiently find out problematic observed quantity, prevents filter divergence, so as to realize real-time clock error stable estimation and satisfy real-time high-precision positioning requirement.

Provided is an apparatus and a method for controlling a motor which stabilizes the estimation of a rotor position even when a control for lowering the applied voltage to the motor is performed. The apparatus for controlling the motor estimates the position of the rotor (31) based on the induced voltage of non-energizing phase of a brushless DC motor (29) to be driven by an inverter (32), outputs a PWM switching signal pulse-width-modulated based on this estimated result to the inverter (32), and controls the applied voltage to the brushless DC motor (29). When the switching signal having the duty ratio corresponding to the applied voltage is generated, the apparatus includes a controller (34) for regulating the carrier frequency of the PWM switching signal so that the pulse width of the switching signal becomes a predetermined pulse width or more.

The invention provides a high-resolution low-sidelobe deconvolution spectrum estimation method based on space-time processing, and belongs to the field of signal processing. The method is suitable forthe high-resolution power spectrum estimation of a received array signal at frequency and azimuth under the condition that the data sample is limited. According to the invention, a deconvolution algorithm is used for the multi-dimensional deconvolution operation of an array signal power spectrum with the limited length and a multi-dimensional window function power spectrum, so the method can completely eliminate the impact caused by a window function under the ideal conditions, and obtains a real power spectrum of a signal. Based on the conventional convolution technology, the method can greatly improve the frequency resolution and angle resolution of a power spectrum estimation result, can greatly inhibit the sidelobe caused by the limited length of data, provides an additional signal tonoise ratio, and provides a new idea for the multi-target detection and recognition and weak signal extraction in the array signal processing. In addition, the method is high in operability, is moderate in calculation burden, is stable in calculation result, and is very wide in application range.

The invention discloses a display image processing method and device. The method comprises the following steps: carrying out direction clustering on straight lines in a display image to obtain two straight line sets containing the largest number of straight lines; Calculating a blanking point corresponding to each straight line set in the two straight line sets; Performing data processing on blanking points corresponding to the two straight line sets respectively to obtain a perspective transformation matrix; And correcting the display image based on the perspective transformation matrix to obtain a corrected image of the display image on the orthographic projection surface. The technical problem that perspective transformation with high precision cannot be obtained in the image correctionprocess in the prior art can be solved.

The invention discloses a stratum structure curvature estimation method that combines a gradient structure tensor with multi-window analysis; the method comprises the following steps: 1, gathering three dimensional post-stack seismic data, and converting the data so as to obtain a complex seismic trace of each seismic signal; 2, calculating a three dimensional instantaneous phase data volume and an instantaneous phase gradient vector; 3, selecting adjacent analysis windows nearby each sample point; 4, calculating a visual dip angle and similarity in each adjacent analysis window; 5, selectingthe analysis window with the maximum similarity from all adjacent analysis windows, and appointing the corresponding visual dip angle as the visual dip angle of the analysis sample point; 6, determining whether the visual dip angles of all sample points are calculated or not; 7, calculating a partial derivative of the three dimensional visual dip angle data volume; 8, calculating the stratum structure curvature. The method can solve the stability and anti-fault interference problems in the three dimensional growl seismic data stratum structure curvature estimation, is easy to realize, and simple in operation.

The invention belongs to the technical field of target tracking, and particularly relates to a vehicle-mounted radar false target efficient judgment method, which comprises the following steps that S1, a vehicle-mounted radar detects a target trace point, and enters a target track tracking state after track initiation, track association and track matching; s2, the current positions xfilter and yfilter, the running speeds vxfilter and vyfilter and the running accelerations axfilter and ayfilter of the target are obtained through tracking by means of a Kalman filtering algorithm, and the current positions xfilter and yfilter, the running speeds vxfilter and vyfilter and the running accelerations axfilter and ayfilter of the target are obtained; s3, the traveling speed of the target is directly estimated by means of the multiple frames of trace points; and S4, comparing the filtering values vxfilter and vyfilter with the estimated value Speeded, and if the filtering values vxfilter and vyfilter meet a preset condition, determining that the current target is a false target. According to the method for efficiently judging the false target of the vehicle-mounted radar, the vehicle-mounted radar tracks the target continuously and stably, and the algorithm implementation process is simple and efficient; therefore, the method not only can effectively improve the false target judgment efficiency, is high in implementation applicability and simple to implement, but also can effectively improve the radar target tracking accuracy.

The invention discloses a scatter matrix feature-based second order partial differential equation remote sensing image denoising method, and belongs to the field of image processing. Firstly, a control function of diffusion terms is established by introducing a 45N degree rotation module value invariance operator, so that diffusion is performed in a gradient direction and a vertical gradient direction in a smooth region and is performed in a curvature direction only in an edge region; and secondly, a better distinguishing capability for feature regions of an image is realized through a scattermatrix, and based on this, fidelity terms are created, so that the denoising effects of a sharp corner region and the smooth region are improved, and the over-smoothness effect of an MCM at a targetsharp point and the "blocky" effect generated by a PM model are effectively relieved.

The invention provides a hotspot grid identification method and device, electronic equipment and a readable storage medium. The method comprises dividing a specific area into a plurality of grids; forthe grids, acquiring AOD concentration data based on satellite inversion, and acquiring surface feature information of each grid; calculating difference data of the surface feature information and difference data of the AOD concentration data based on satellite inversion; performing learning through a machine learning method to obtain a correlation model of the difference data of the surface feature information and the difference data of the AOD concentration data based on satellite inversion; according to a correlation model, calculating a pollution emission influence weight for each of theone or more types of surface feature information; and screening hotspot grids by utilizing the pollution emission influence weight and the surface feature information. According to the method, the problems of data instability and insufficient availability caused by cloud shielding in the existing hotspot grid screening technology can be solved, and hotspot grids can be accurately, objectively andstably screened.

In various embodiments, methods and systems are disclosed for the real time detection of network conditions in conjunction with a remote presentation protocol. The link quality may represent the quality of the end-to-end connection between client and server with upper and lower bounds on the injection of additional traffic used for measurement. In some embodiments, the measurement technique may be selected based on the type of measurement that is desired. Accuracy may be maintained by selecting the type of measurement used based on current and previous network conditions. In one embodiment, a state model is used to determine the frequency of measurement and to determine when the measurements have produced a stable estimate of the link quality.

The invention belongs to the technical field, and particularly relates to a DOA estimation system and an estimation method based on software radio equipment. The system comprises a clock source, at least one signal source, at least four pieces of software radio equipment, a uniform linear array and a processor, wherein the uniform linear array comprises at least four array elements; each array element is arranged at a receiving end on the software radio equipment and is in communication connection with the corresponding software radio equipment through radio frequency lines with the same length; each signal source corresponds to at least four pieces of software radio equipment, the signal source is located on one side of the at least four pieces of software radio equipment, and the clock source is located on the other side of the at least four pieces of software radio equipment, is in communication connection with each piece of software radio equipment through a clock synchronization line and provides the same clock pulse signal; the at least four pieces of software radio equipment are in communication connection with the processor; and the processor is used for carrying out direction of arrival estimation on the calibrated receiving data matrix by adopting a MUSIC algorithm.

The embodiment of the invention discloses a water-fat separation method, device and equipment based on a magnetic resonance image and a storage medium. The method comprises the following steps of obtaining each pixel point to be processed in a magnetic resonance image, respectively calculating a phase factor candidate solution of the pixel point, and respectively dividing each phase factor solution in the phase factor candidate solution into a first solution set and a second solution set; based on the phase factor solutions in the first solution set and the second solution set, determining a water lipid conversion area, and calculating a target phase factor solution of each pixel point to be processed in the water lipid conversion area; determining a target phase factor solution of each ofthe rest to-be-processed pixel points based on the water-fat conversion region and the target phase factor solution in the water-fat conversion region; and extracting a water map and a fat map in themagnetic resonance image according to the target phase factor solution of each pixel point to be processed in the magnetic resonance image. According to the technical scheme provided by the embodiment of the invention, the field diagram can be rapidly and stably estimated, and the correct estimation of water and fat components is completed on the basis.

In various embodiments, methods and systems are disclosed for the real time detection of network conditions in conjunction with a remote presentation protocol. The link quality may represent the quality of the end-to-end connection between client and server with upper and lower bounds on the injection of additional traffic used for measurement. In some embodiments, the measurement technique may be selected based on the type of measurement that is desired. Accuracy may be maintained by selecting the type of measurement used based on current and previous network conditions. In one embodiment, a state model is used to determine the frequency of measurement and to determine when the measurements have produced a stable estimate of the link quality.

The invention discloses a space channel characteristic prediction method and system based on an m sequence and a storable medium, and belongs to the technical field of underwater acoustic channel communication, and the method comprises the steps: setting an array parameter and a transmitting signal parameter; sampling signals are intercepted according to the set array parameters and emission signal parameters; carrying out delay summation beam forming on the intercepted sampling signal; capturing data formed by the delay summation beam to obtain a capturing result; generating a delay angle distribution diagram according to a capture result, and predicting signal delay and an incident angle; and performing Doppler analysis on the path signal according to a signal delay and incident angle prediction result to complete spatial channel characteristic prediction. According to the method, the problems of traditional direction-of-arrival prediction, time delay and Doppler are solved, so that the prediction performance of spatial channel characteristics is improved.

The invention discloses an LDoS attack detection method based on an EMDR-WE algorithm, and belongs to the field of computer network security. The method comprises the following steps: in view of the characteristic of high complexity of a TCP flow sequence under the LDoS attack, quantifying the TCP flow sequence complexity of an attack window and a normal window by combining four characteristic entropies, namely approximate entropy, sample entropy, fuzzy entropy and permutation entropy; constructing a preprocessing model for empirical mode decomposition and reconstruction of a TCP flow sequence, filtering noise components of the TCP flow sequence through the model, obtaining a sliding window sequence of TCP flow, and extracting four feature entropies of each window; giving a higher weight to the feature entropy with the large information contribution degree by using an entropy weight method to obtain a comprehensive score of the complexity of each TCP flow window. comparing with a threshold value obtained by logistic regression training, and judging that the window with the comprehensive score higher than the threshold value has the LDoS attack. According to the LDoS attack detection method based on the empirical mode decomposition, reconstruction and entropy weight method, the LDoS attack can be accurately detected, and the performance is stable.

The invention discloses an intelligent sensing method and device for a binocular camera capable of adaptively adjusting a baseline, and the method comprises the following steps: detecting a target object from an image, and obtaining the pixel position of the target object; according to the currently set baseline B1 and the internal and external parameters of the camera, calculating the depth and depth uncertainty of the target object through a binocular depth estimation algorithm; judging whether the current depth uncertainty is too large or not: if the current depth uncertainty is larger than the expected depth uncertainty, calculating an expected baseline B2 through the expected depth uncertainty; automatically adjusting the baseline to an expected baseline B2; extracting feature points from the environment through a binocular camera online calibration technology, and performing feature matching in left and right images to obtain new external parameters; according to the new external parameters and the base line B2, recalculating the depth and depth uncertainty of the target object. According to the invention, the base line can be automatically adjusted according to the distance of the measured object, and it is ensured that the depth estimation error meets the expectation.

The present invention provides a battery model parameter identification method based on multi-innovation recursive Bayesian algorithm, comprising the following steps: Step 1) measuring the lithium-ion battery terminal voltage and load current within a certain period of time by intermittent constant current discharge method Data, determine the functional relationship of its OCV-SOC by polynomial fitting method; step 2) determine the dual-polarization equivalent circuit model of lithium-ion battery, establish the system equation that represents the battery parameter identification vector and system output relationship; step 3) construct multiple The identification process of the innovation recursive Bayesian algorithm. The beneficial effect of the present invention is: the present invention establishes the ARX model of lithium-ion battery parameter identification, uses the innovation correction technology to correct the result of the previous moment, and introduces the innovation length parameter based on the multi-innovation identification method to overcome bad data The impact on parameter estimation improves the accuracy of parameter estimation. It can be seen from the parameter identification results that this method has high identification accuracy and has engineering value.

The invention relates to an airborne SAR radiation external calibration processing method based on weak arrangement of corner reflectors. The method comprises the following steps: obtaining original SAR image data of a calibration field; on the basis of a point target radar equation, reconstructing an radiation external calibration equation; performing stable estimation on calibrator image energy and geometric optical solution on a calibration RCS; carrying out fitting and correcting on a radar system transfer function to obtain preliminary radiation calibration SAR image data; carrying out the stable estimation on the calibrator image energy and the geometric optical solution on the calibration RCS; and estimating a system constant item so as to generate calibration data and obtain final radiation calibration SAR image data. According to the invention, on the basis of the point target radar equation, according to the characteristic of parameters of a radar system, the SAR radiation external calibration equation comprising a change system transfer function and a constant system constant item is reconstructed, the application process of radiation external calibration is simplified, and the problem is avoided that it is quite difficult for airborne SAR flight to obtain a large-scope homogeneous stable tropical rainforest area frequently used by similar spaceborne SAR radiation calibration.

A control apparatus for estimating the flux, the current, and the speed of an AC motor using the current and the voltage, and controlling the vector of an AC motor using the estimated speed, a flux command, and a torque current command. The speed is estimated by adding a product of the deviation between the actual value and the estimated value of a magnetization current, the level of a torque current correspondence value, the sign correspondence value of a primary frequency command value, and a gain to an outer product of an estimated current deviation and an estimated flux. Thus, a stable speed estimating operation can be performed to successfully operate the motor in a low speed area in which a voltage frequency applied to the motor is extremely low.

Provided are a motor control device and a motor control method that enable stable estimation of a rotor position even if control is performed to reduce the voltage applied to the motor. The motor control device estimates the position of the rotor (31) based on the induced voltage of the non-energized phase of the brushless DC motor (29) driven by the inverter (32), and converts the pulse width modulated PWM switching signal according to the estimation result. It is output to the inverter (32) to control the applied voltage to the brushless DC motor (29). The motor control device includes a control unit (34) that adjusts the carrier frequency of the PWM switching signal so that it has the ability to respond when generating When a switching signal with a voltage duty cycle is applied, the pulse width of the switching signal is equal to or greater than a predetermined pulse width.

The invention provides a physical code-channel activation and detection method based on channel estimation post-treatment and a device thereof. The method of the invention comprises the following steps: the power of all windows of the user is acquired; the window with the largest power amongst all windows and the position of the window with the largest power of the user are ascertained; activatedwindows amongst all windows of the user are ascertained according to the window with the largest power and the position of the window with the largest power; the actual total number of the activated physical code-channels of the user and the corresponding activated physical code-channels are ascertained according to the activated windows and the resource of the physical code-channels distributed to the user by the high level. The method and device of the invention effectively solve the problem of unreliability of estimation of key parameters, such as frequency deviation, etc. caused by lacking of data quantity, thus enhancing the performance of the system.

The invention discloses a second-order partial differential equation remote sensing image denoising method based on the characteristics of the scatter matrix, which belongs to the field of image processing. First, the control function of the diffusion term is established by introducing an operator with a constant 45N degree rotation modulus, so that the diffusion is The smoothing area is performed along the gradient direction and the vertical gradient direction, and only along the curvature direction in the edge area; secondly, the characteristic area of ​​the image is better resolved through the scatter matrix, and the fidelity item is constructed to improve the sharp corner The denoising effect of the area and smooth area effectively alleviates the over-smoothing effect of the MCM model at the sharp point of the target and the "blocky" effect produced by the PM model.