39 results about "Second order moments" patented technology

The invention belongs to the technical field of target tracking, and discloses a maneuvering target tracking technology based on double-layer expectation maximization. The method comprises the steps that: firstly, N radar measurement vectors y<1><k> - y<N><k> of a maneuvering target are correspondingly obtained by real-time measurement of N radars, and the radar measurement vectors y include the distances from the maneuvering target to the radars, azimuth angles and change rates of the distances from the maneuvering target to the radars; secondly, a first layer expectation maximization algorithm is used on the N radar measurement vectors y<1><k> - y<N><k> to obtain an estimated set of maneuvering target state vectors x shown in the specification and an additive unknown interference pseudo measurement [theta] set shown in the specification, and the additive unknown interference pseudo measurement [theta] set is transmitted to a second layer expectation maximization algorithm; thirdly, after the second layer expectation maximization algorithm receives the additive unknown interference pseudo measurement [theta] set, mixed Gaussian distribution is utilized to fit first-order and second-order moment of the additive unknown interference pseudo measurement [theta] set, and the mean value [mu]<[theta]><k> and the covariance p<[theta]><k> of the additive unknown interference pseudo measurement [theta] set are obtained; and fourthly, by means of kalman filtering, the mean value [mu]<[theta]><k> and the covariance p<[theta]><k> of the additive unknown interference pseudo measurement [theta] set are utilized to obtain a state estimated value shown in the specification. By adopting the technology, the analyticity and convergence of parameter identification are ensured, and the technology is capable of improving the precision of target state estimation.

A method and system are disclosed for analyzing images of fiducials that provide an indication of the forces and/or torques applied to an orthodontic bracket. The mass of each of the pixels forming the fiducial image are multiplied by the square of the distance of the pixel along the image's x axis, the product of the distances of the pixel along the image's x and y axes, and the square of the distance of the pixel along the image's y axis. The second order moments of inertia about the centroid of the fiducial are calculated and used to form a first matrix. The first matrix is diagonalized into a second matrix, from which the fiducial 's first and second principal axes are determined. These axes are then used to measure the size of the fiducial in the image.

Method and apparatus for the power control system outer loop of a mobile communications systems in a cellular infrastructure that allows fulfilling a given Quality of Service (QoS) with the minimum power level necessary. This outer loop is in charge of setting the desired signal to interference target ratio SIR_tgt that fulfils the required quality of service in a radioelectric environment characterised by stochastic models. The proposed method is based on the application of the Newton-Raphson iteration method on numerical approximations of the various outage probability (QoS) probability density functions in various propagation environments, so that having established this probability and dynamically estimated the second order moments characteristic of each statistic considered, the margin over the SIR median is obtained and thereby the SIR_tgt corresponding to the aforementioned outage probability.

The invention discloses a stochastic robust optimization-based energy storage allocation method of a wind field system. A scenario method, stochastic programming, interval programming and an artificial intelligence method are widely used for energy storage planning of a renewable energy-containing system at present. These methods are based on accurate renewable energy output or accurate probability distribution and have certain limitations. The method comprises the steps of describing a wind power prediction error as a random variable meeting given second-order moment and fluctuation quantity; describing an energy storage allocation problem containing the wind field system by a probability distribution function set meeting the second-order moment characteristics of the random variable by adopting a probability distribution robust joint opportunity constraint optimization model; converting the probability distribution robust joint opportunity constraint optimization model into definitive linear matrix inequalities; and finally solving the definitive linear matrix inequalities by adopting a convex optimization algorithm. According to the stochastic robust optimization-based energy storage allocation method, an economical and optimal energy storage allocation scheme meeting the safe operation requirements of a power system under the worst distribution of wind power can be obtained.

The invention discloses a method for extracting video texture characteristics based on fuzzy concept lattice, which mainly solves the problems of large computation quantity, low efficiency and low real-time performance in a traditional method. The method comprises the realizing steps of: (1) dividing a video lens; separating the divided video lenses into video segments; using a first frame of thevideo segments as a key frame of the video segments; (2) separating an image of the key frame into blocks; computing a gray co-occurrence matrix of the image blocks; computing fourteen texture characteristic vectors of second-order moments, entropy and the like based on the gray co-occurrence matrix; (3) using the image blocks of the key frame as an object set; using the texture characteristic vectors of the image blocks as an attribute set to form a fuzzy form background for constructing the fuzzy concept lattices; (4) generating a texture related rule by the fuzzy concept lattices of the key frame; and (5) extracting the texture characteristics of all video frames in the video segments according to the texture related rule of the key frame. The method can be used for quickly and accurately extracting the video texture characteristics, and video processing fields of target identification, video search and the like.

The invention discloses a radio frequency fingerprint identification method based on QPSK signal bispectrum energy entropy and color moments, relating to the field of wireless communication. A bit stream signal of a sending end is subjected to QPSK mapping to obtain a signal s(n). Through up conversion, a frequency modulation signal p(n) is obtained and is inputted into a power amplifier to output a signal Phi (n), an analog signal is obtained through digital to analog conversion processing, the analog signal is sent out and is added into AWGN in a sending process, a receiving end obtains a digital signal r(n) through analog to digital conversion processing, a baseband signal is obtained through down conversion, and radio frequency fingerprint characteristics including the bispectrum energy entropy, a first-order moment and a second-order moment are extracted from the baseband signal. Then through an SVM classifier, the classification training and testing of the radio frequency fingerprint characteristics are carried out, and a test category result is obtained. Through comparing the test category result and an actual category result, a classification accuracy rate Pc is obtained. According to the method, the radio frequency signals are effectively classified, and the identification accurate rate under a low signal-to-noise ratio is improved by nearly 20% compared with a traditional method.

Generally, the present invention provides a number of procedures to spatially profile proteins by using hydrophobic moments. In all procedures, a hydrophobicity distribution of a protein is shifted and normalized. In one procedure, a shape or profile of a curve of a second-order moment of hydrophobicity is determined. A second procedure involves determining one or more ratios, such as the ratio of a distance at which the second order moment of hydrophobicity vanishes to the distance at which a zero-order moment of hydrophobicity vanishes. The distance at which a peak occurs in a profile of the zero- or second-order moment of hydrophobicity can also be used for comparison. For many of these procedures, a surface or profiling contour can be chosen and used to accumulate hydrophobicities and to determine the moments. These procedures can be combined to provide a good mathematical determination of whether a protein belongs to a particular class of proteins.

The invention discloses a transmitting antenna number blind estimation method applicable to an MIMO (Multiple Input Multiple Output) system, and mainly solves the problem of low accuracy of identifying a number of transmitting antennas of the MIMO system in a time-variant fast fading channel environment and under the condition of a low signal-to-noise ratio. The method comprises the steps of: (1) constructing a received sample matrix by utilizing a received signal of a non-cooperative receiving machine, and implementing data acquisition of the non-cooperative receiving machine; (2) constructing a covariance matrix by utilizing the received signal sample matrix; (3) carrying out feature value decomposition on the covariance matrix; (4) setting a bilateral detection threshold, and initializing a counting variable; (5) calculating a second-order moment; (6) calculating a feature value judgment threshold; and (7) according to a feature value and a threshold, carrying out judgment to obtain the number of the transmitting antennas of the MIMO system. According to the transmitting antenna number blind estimation method disclosed by the invention, a correct identification rate in a fast fading channel under the condition of small sample received data and under the condition of the low signal-to-noise ratio is ensured, and applicability in military communication resistance and in the time-variant fast fading channel is ensured.

A simple and robust method for determining the orientation angle of a scanned image or the angular orientation of an object in an electronic image based on using descriptors of the image and systems that implement the method are disclosed. A system including means for acquiring the electronic image, means for determining image centroid coordinates, means for obtaining second order moments corresponding to the image, and, means for determining an orientation angle of a principal axis of the image implements the method.

The embodiment of the invention discloses a robustness spectrum sensing method and device based on differential characteristic values and a computer storage medium. The method can be applied to receiving end equipment with a plurality of receiving antennas at a cognitive user. The method comprises the following steps: acquiring all characteristic values corresponding to a received sample covariance matrix constructed by received data; constructing test statistics based on the maximum characteristic value in all characteristic values corresponding to the received sample covariance matrix and the rest characteristic values except the maximum characteristic value; obtaining a k-order moment corresponding to the maximum characteristic value; obtaining a first moment and a second moment of a trace of the received sample covariance matrix; determining a sensing threshold according to the k-order moment corresponding to the maximum eigenvalue and the first-order moment and the second-order moment of the trace of the received sample covariance matrix; and judging the working state of the authorized user according to the test statistics and the perception threshold.

The invention relates to a human-vehicle identification method based on four-dimensional information weight, and belongs to the technical field of radar target identification. The method comprises thefollowing steps: 1, caching tracking data of a target for X times; 2, calculating X normalized RCS values; 3, analyzing the spectrum of a radar target echo after MTD, finding out the maximum spectrumpeak position of the target, and calculating the number of other spectrum peaks of the target echo in the +/-N point of the position; 4, calculating a normalized RCS first-order moment M [sigma] anda normalized RCS second-order moment [upsilon] [sigma]; 5, multiplying the weights H1, H2, H3 and H4 by the normalized RCS first order moment, the normalized RCS second-order moment, a spectral peak number and a peak speed respectively, and performing calculation to obtain a probability P < person > of judging the current X times of tracking data as a person and a probability P < vehicle > of judging the current X times of tracking data as a vehicle; 6, judging that the target is a person if the P person value is greater than the P vehicle value; otherwise, judging that the target is a vehicle, and outputting a judgment result. According to the identification method, as long as the radar erection posture is correct and no shielding exists between the target and the radar, high identification probability can be realized, and stable and reliable identification can be realized.

The invention discloses a perturbation multi-Gaussian fitting-based space object tracking method which comprises the following steps: perturbation force applied on a space object is modeled as unknown interference coupled with an object state; under a double layer EM framework, perturbation mean value and covariance are fitted via multi-Gaussian distribution; at a first layer EM, combined state estimation and identification of first order moment of perturbation can be realized; at a second layer EM, first and second order moment of perturbation is identified via mixed multi-Gaussian fitting, and space object state estimation and covariance are fed back and corrected in a combined manner via use of the perturbation mean value and covariance through design of a combined correction filter. The method disclosed in the invention can help solve a problem that poor tracking precision is caused due to strong non-linear perturbation force coupled to the state via technologies of the prior art.

The embodiment of the invention discloses a SAR image speckle reduction method and a system based on an anisotropic diffusion equation, the method comprising: reading second-order moment data of the SAR image; performing comprehensive calculation on the second-order moment data to obtain a total power image and local statistical data; correspondingly covering previous data with the total power image and the local statistical data; performing Gaussian smoothing processing on the total power image, and calculating partial derivatives in the x and y directions; correspondingly covering previous data with the partial derivatives in the x and y directions; calculating structure tensor function based on the partial derivatives in the x and y directions; calculating the total power image to obtain a diffusivity function value; calculating diffusion tensor function; performing a diffusion on the second-order moment data, separately; updating the number of diffusion to complete speckle reduction. The technical solution provided by the SAR image speckle reduction method and system based on an anisotropic diffusion equation, is suitable for full-polarization and single-polarization SAR images. There is no crosstalk between polarization channels, when performing speckle reduction on a full-polarization SAR image, and can keep the positive and negative of each second-order moment data in the image.

The invention discloses an image focusing measure implementation method based on a second-order moment function, and belongs to the technical field of information processing. The method comprises thefollowing steps: firstly, preprocessing an image, then partitioning the processed image, and calculating a moment function of each sub-image; And selecting a low-order moment function of each sub-image to construct definition information of the image. And finally, solving the variance of a set formed by the definition information of all the sub-images, and taking the variance value as the focusingmeasurement value of the whole image. According to the invention, on the basis of dividing the image into blocks; a moment function is adopted to construct detail information of the image, the methodis advantaged by simple principle and low computation complexity; Meanwhile, through implementation of the steps, interference of noise on image detail information is reduced to a great extent, so that the focusing measure obtained through the method has high noise robustness, and the method is suitable for a passive imaging system of a camera, especially for high noise resistance under the low-contrast imaging condition, and is suitable for popularization and application.

Provided in the invention is a detection-based OFDM signal gain control method. The method comprises: step one, on the basis of a preset initial gain control parameter and a second-order moment signalpower of an OFDM signal, estimating and calculating error tracking signal EA1 of the gain control, detecting leading symbol data yP (n) of the OFDM signal and a receiving signal y(n); step two, according to the leading symbol data yP (n) obtained at the step one, calculating an error tracking signal EA2 of time-domain gain control; and step three, according to the receiving signal y(n) obtained at the step one, calculating an error tracking signal EA3 of frequency-domain gain control.

There is described a method of characterizing a short laser pulse, the method comprising the steps of obtaining root-mean-square widths of the pulse through second order moments of the pulse; obtaining a spectral width of the pulse using the root-mean-square widths; obtaining a root-mean square temporal width of the pulse; and defining a Pulse Quality Factor proportional to a product of the spectral width and the temporal width. This approach does not require complete characterization of laser pulses and eliminates the need of any assumption to interpret autocorrelation traces. The method can be applied to pulses of arbitrary shape.

The invention relates to an adaptive threshold signal detection method with a known duty ratio. The method comprises the following steps: firstly, performing low-pass filtering smoothing on a signal envelope; secondly, calculating a mean value and a second-order moment of the filtered signal envelope; and finally, reverse reasoning a high level and a low level of a signal according to the mean value and second-order moment, thereby determining an optimal detection threshold of the signal, realizing the detection of the presence or absence of the signal, and determining the arrival time of thesignal and performing signal duration estimation at the same time. According to the method provided by the invention, the weak signal detection probability with a low signal-to-noise ratio in the presence of a plurality of interference signals is improved, and at the same time, the false alarm probability is reduced; and the method can be applied to the signal detection of anti-radiation unmannedaerial vehicles, and can also be applied to all other cooperative signal detection fields, such as communication multi-user detection, radar signal detection, cognitive radio and the like.

The invention discloses a Rician factor estimation method and system. The method comprises the steps of: modeling main path components of a received sample by utilizing Nagakami distribution, thereby obtaining a received sample model; according to the received sample model, calculating a second-order moment, a fourth-order moment and a sixth-order moment of the received sample, building and solving an equation set of estimation parameters, thereby obtaining numerical values of the estimation parameters; and estimating a Rician factor according to the numerical values of the estimation parameters. The system comprises a first calculation module, a second calculation module and a third calculation module. According to the Rician factor estimation method and system, the main path components of the received sample are modeled by utilizing the Nagakami distribution, and the second-order moment, the fourth-order moment and the sixth-order moment of the received sample are calculated in order to build the equation set of the estimation parameters and establish a likelihood function of the received sample, so that estimation precision of the Rician factor can be effectively improved.