106results about How to "Easy to implement in real time" patented technology

The invention discloses a double-spectrum night vision instrument vehicle-mounted system and a double-spectrum fusion design method. The system comprises an infrared double-spectrum imaging die set used for imaging of a visible spectrum and an infrared spectrum and for collection, processing, fusion and transmission of the image data, an image receiving system used for completing the receiving of the image data, a display terminal used for displaying the images for an observer, and a control terminal used for controlling the function and on-off of an imaging mode. Due to the adoption of the system and the method, the problem that coaxial imaging of the double spectrum image is slight bad is solved, the machining precision requirement of the imaging system is reduced, more clear images are provided for forward observation for a train; a fusion method based on a scene moving object provides a reference source for the double-spectrum imaging system, the computation load is reduced, the registering reliability is improved, the imaging on the hardware is convenient, and the real-time performance is possessed; a weight fusion method based on multi-scale bilateral filtering is simple and feasible, improves the imaging detail information and reduces the calculation ability.

An infrared gait dual-channel feature fusion recognition method, the steps are: infrared image preprocessing, firstly using the background subtraction method of the mixed Gaussian model to realize the detection of moving human body; then performing morphological processing, that is, using morphological filtering to eliminate binary values Noise in the image and fill in the lack of moving targets; infrared image feature extraction, first of all, it is necessary to divide the cycle of the gait sequence, and determine the gait cycle based on the periodicity of the contour width; determine the gait energy map; infrared pyroelectric features Extraction, first of all, data collection, then denoising processing on the collected voltage signal, and then performing Fourier transform on the time domain signal to obtain its spectrum, and then use PCA to reduce the dimension to obtain the feature vector; classification and identification. In the present invention, the one-dimensional voltage signal collected by infrared pyroelectricity during human movement is easy to realize in real time, and the infrared image is not sensitive to the shape change of the carrying objects such as bags, umbrellas, backpacks, etc. when people walk, and it can also be used at night working.

The invention relates to an interference pattern recognition technology of a frequency hopping system, belonging to the field of broadband wireless communication. The technology is mainly used for analyzing various interference types of the frequency hopping system. On the premise of not increasing frequency hopping bandwidth and frequency hopping speed, the recognition for various interference patterns can be realized. First, pretreatment for removing frequency hopping points is carried out on the received signals; then, characteristic parameters such as time domain, frequency domain, time-frequency domain and the like of interference signals can be extracted for mode recognition, so that classified recognition of the different interference types can be realized. The technology has better recognition effect for the various common interference types as well as stronger robustness and stability, and provides reliable basis for further interference suppression. In addition, the method has low computational complexity and is easy to realize in real time by the system.

The invention relates to a method for inhibiting MPSK narrowband interference of a direct sequence spread spectrum system (DSSS), and belongs to the technical field of anti-interference of communication. In the method, a main lobe and a side lobe of a MPSK narrowband interference signal are inhibited respectively by adopting a method of combining a frequency domain and a time domain. The method comprises the following steps of: by adopting a method of segmentation overlay processing, inhibiting the main lobe of the MPSK narrowband interference signal as many as possible, and simultaneously ensuring that the energy loss of the useful signal is reduced as much as possible by using the difference between the noise characteristics of the DSSS communication signal in the frequency domain and the energy focusing characteristics of the MPSK narrowband interference signal; and inhibiting the side lobe of the MPSK narrowband interference signal in the time domain so as to effectively separate the interference signal from the useful signal, achieve high performance of bit error rate and guarantee reliable communication of the DSSS by using the characteristics that the frequency spectrum of the side lobe of the MPSK narrowband shows an impulse form. In addition, the method has low computational complexity and is easily implemented by the system in real time.

The invention belongs to the technical field of radar moving target detection, and particularly relates to a space-time adaptive processing method for airborne forward-looking array radar. The method includes the specific steps of obtaining a data vector xnk1, received by the kth pulse of the nth line of array elements of a receiving array of the airborne forward-looking array radar, of a first distance door, obtaining the data vectors, recorded by the nth line of array elements of the receiving array of the airborne forward-looking array radar, of selected distance doors recorded within the time period of [KT, (K+1)T], obtaining the estimation (please see the specifications) of the dimensionality reduction pitching covariance matrix of the first distance door of the nth line of array elements of the receiving array of the airborne forward-looking array radar, obtaining the dimensionality reduction self-adaption weight vector omega E of the first distance door of the nth line of array elements of the receiving array of the airborne forward-looking array radar, obtaining the data vector ynk1, received by the kth pulse of the nth line of array elements of the receiving array of the airborne forward-looking array radar, of the first distance door after pitching pre-filtering is conducted, and obtaining the signal of the kth Doppler channel of the first distance door of the airborne forward-looking array radar through the orientation-Doppler space-time adaptive processing method after the space-time adaptive processing is conducted.

The invention discloses a full-frame electronic image stabilization method based on feature matching, which belongs to the technical field of digital image processing and aims at eliminating influences on a video sequence by jitter such as camera translation and rotation and generating stable full-frame video output. The method comprises steps: firstly, an ORB feature descriptor is adopted to extract feature points in each frame, a two-level matching strategy with minimum and second minimum Hamming distance ratio judgment in combination with coordinate and direction angle difference test is used for matching feature points in adjacent frames; then, a motion parameter estimation method with triangle area similarity test in combination with RANSAC is used for estimating and accumulating inter-frame affine transformation parameters; and finally, an image mosaic technique is used for acquiring a motion compensation mosaic image, subjective motion parameters of the camera are estimated through Kalman filtering, a display window with the same size as the video frame is set on the mosaic image sequentially, and complete motion compensation frame output is obtained. Translation and rotation jitter in the original video sequence are effectively removed, and the stable full-frame output is obtained.

The invention relates to a textural feature-based no-reference image quality evaluation method. The method comprises the following specific steps of: dividing a graphic database into a training image set and a test image set; constructing images uder different scales for each image; solving normalized brightness images for the images under different scales; solving normalized gray-level co-occurrence matrixes in four directions for the normalized brightness images; calculating energy, entropies, contrast ratios and dependencies of the normalized gray-level co-occurrence matrixes to combine a feature vector; sending the feature vector and a subjective MOS score to a support vector machine to carry out training; and predicting test images by using the trained support vector machine so as to obtain an objective image quality evaluation result. According to the method, image quality evaluation is carried out by utilizing textural features; compared with the existing algorithms, the method is lower in calculation complexity and convenient to realize in real time, and has the effect of improving the prediction precision through extracting the textural features by utilizing the gray-level co-occurrence matrixes with a plurality of scales and a plurality of angles.

Disclosed in the invention is an underwater multi-target tracking method. A wireless sensor network positioning system comprises a plurality of sensor nodes, a cluster head node and a control system. For the system positioning, an improved resampling non-augmented tasteless particle filtering algorithm is used to realize target positioning based on sensor network configuration. Because the algorithm fully utilizes information measured at current time at the current orientation to estimate a particle posterior probability density function, a defect that particle selection has blindness according to a PF algorithm is overcome, so that the approximate and better positioning precision can be realized under the circumstances that a few particles exist. Moreover, there is no need to expand the state dimension in a vector, so that the calculation complexity can be substantially reduced, the calculation time is improved, and the system can be realized in real time.

The invention belongs to the technical field of radar echo simulation, and particularly relates to a radar echo real-time simulation method based on an FPGA and a DSP. The method comprises the following steps that 1, the following data of the position coordinate of a radar at each direction moment, the coordinate and grey value of each pixel point in a rectangular face object scene and the conjugate item of a distance direction matching function are prestored in an FPGA chip, and according to the data prestored in the FPGA chip, the distance unit serial number corresponding to each pixel point in the rectangular face object scene at each direction moment and direction echo data are obtained; 2, the FPGA chip transmits the two parts of data calculated and obtained in the step 1 to a DSP chip, the DSP chip carries out data integration on the data from the FPGA chip, and a matrix H is obtained; 3, the DSP chip transmits the matrix H to the FPGA chip, and a radar echo data matrix is obtained by the FPGA chip according to each line of elements of the matrix H and the conjugate item of the distance direction matching function.

The invention discloses a nonlinear control method of a Buck-Boost converter system. The nonlinear control method of the Buck-Boost converter system is characterized by comprising the following steps that first, an input voltage, an inductive current, a capacitor voltage and a state average model of a Buck-Boost converter main circuit are obtained; then, the cooperative control law of the Buck-Boost converter system is obtained; afterwards, the expectation value of the inductive current is obtained; at last, the cooperative passive control law of the Buck-Boost converter system is obtained, and therefore nonlinear control over the Buck-Boost converter system is achieved. By means of the nonlinear control method of the Buck-Boost converter system, the transient overshoot of the inductive current of the Buck-Boost converter system can be effectively removed, the steady state error of the capacitor voltage is reduced, and thus the stability of the Buck-Boost converter system is improved.

The invention discloses an equivalent space vector carrier modulation multilevel converter control method, belonging to the technical field of control and adjustment of converters. The method comprises the following steps of: for a k level converter space vector equivalent carrier mode, adopting k-1 heavy no-phase shift carriers for modulation, wherein the interval of the heavy carriers and the per-unit value are as shown in the specification, and a unified form of a zero-sequence component as shown in the specification is acquired; for a three-phase reference modulation wave, comparing the values according to an effective output time to obtain the maximum value, intermediate value and minimum value of the three-phase reference voltage; calculating the direct current offset in the zero-sequence component according to the three-phase reference modulation wave, adding the three-phase reference modulation wave to the zero-sequence component to obtain an equivalent space vector reference modulation wave; modulating by selecting the corresponding carrier according to the reference voltage, and outputting a waveform equivalent to the space vector carrier modulation. The invention has the beneficial effects of quickly and accurately solving the zero-sequence component, simultaneously, greatly simplifying the calculated amount, and being easy to realize in real time.

The invention provides a method for compensating and enhancing a dynamic shielded image in real time, solves the real-time compensation and enhancement problems of the dynamic shielded image and improves the quality of the dynamic shielded image. The technical proposal comprises the steps of estimating the motion vector between two adjacent images by a moderate method based on a video image output by a camera, combining motion compensation with a time domain Kalman filter technique of a pixel gray value, performing time domain filtering treatment for all pixels so as to compensate the image information of a dynamic shielded area, and finally performing self-adaptive grey widening and edge enhancement treatments for the compensated image.

The invention discloses an infrared image sea-sky-line self adaption detection method which includes the following steps that (1) an original infrared image Forg is obtained; (2) edge detection is conducted on the original infrared image through a Canny operator, and an edge image Fedge is obtained; (3) a sliding window model MWin, the sea-sky-line length and a model LEN sum <j> are built; (4) full-figure traversal is conducted on the edge image Fedge through the sliding window model MWin, and the sum of lengths of sea-sky-lines of different lines is solved; (5) the length of the sea-sky-lines and the line with the maximum LEN sum are defined to be the positions of the current image sea-sky-lines; (6) smoothing is conducted on the current image sea-sky-lines, and the filter value Lineseasky <p+1> of the p+1th frame of the sea-sky-lines is output.

The invention relates to a single-frame infrared image based real-time detection method of a point target, which handles each pixel through the steps that: (1) whether a pixel is the maximum point in an adjacent area or not is judged by comparing the gray between the pixel and other pixels in the 3*3 adjacent area; (2) the average gray value of a 3*3 adjacent area which takes the pixel as the central pixel is calculated; the proportion of the difference between the gray value of the central pixel and the average gray value, in the average gray value filter of the sum of the differences between the all pixels with the gray values being more than the average gray value and the average gray value, is calculated, the determination result of the point is set to be 1, and otherwise, the determination result of the point is set to be 0; (3) the proportion of the pixel in four directions is respectively calculated; if the proportion in each direction is more than a set edge detection proportion threshold, the determination result of the point is set to be 1, and otherwise, the determination result of the point is set to be 0; and (4) the determination results of Step (2) and Step (3) are summated as the value of the point in a final binarization value.

The present invention discloses a dark and dim point target detection method in an infrared image. 8 structure elements with 5*5 dimension of a direction are employed to extract all possible targets with different scales; obtaining a target interest area, through adaptive threshold processing so as to effectively improve the target signal to noise ratio; employing the decision criterion of distribution of a background edge point-to-point target at a local neighborhood, and rejecting residual background edge points; and rejecting noisy points according to an interframe matching relation and obtaining a target movement locus. The dark and dim point target detection method in the infrared image is not high in algorithm complexity and satisfies timeliness requirements; and the target detection probability is high, the false alarm rate is low, and the dark and dim point target detection method in the infrared image has important application values.

The invention discloses an infrared image detail enhancement and noise adaptive inhibition method. The method comprises the following steps of (1) acquiring an original infrared image Forg; (2) utilizing a differential operator to calculate a filter component Fd of the original infrared image; (3) calculating the background complexity of the original infrared image, and determining a noise inhibition threshold value T1; (4) calculating a region variance V of the original infrared image, performing binaryzation on a region variance image according to an initial threshold value T2, and utilizing a matrix BW to express the binarized image; (5) calculating a weighting matrix Coe of the filter component Fd; and (6) outputting a detail enhancement image Fout. Compared with the prior art, the infrared image detail enhancement and noise adaptive inhibition method has the following advantages that (1) the infrared image detail enhancement and noise adaptive inhibition method is particularly used for processing a signal-to-noise ratio image, and can effective inhibit the noise amplification of the image while the image detail is enhanced.

The invention discloses a gray scale and gradient segmentation-based infrared target detection method. The method comprises the following steps: 1) calculating a gradient image Phi(x, y) by utilizing an original image Forg; 2) carrying out non-maximum value inhibition on the Phi(x, y) to obtain an image Phi1(x, y); 3) carrying out edge linking and edge closing judgement by utilizing the Phi1(x, y), and calculating a candidate target area Pos1; 4) selecting a local image Floc according to the Pos1 and segmenting the Floc to obtain a candidate target area Pos2; and 5) calculating an optimum target area Pos according to a formula (as shown in the specification).

The invention, which belongs to the field of radar technology, discloses an actual-value ESPRIT non-circular signal angle estimation method for a single-base MIMO radar. Matched filtering is carried out on array element receiving data and a transmitted signal to obtain an observation data vector; dimensionality reduction preprocessing is carried out on the observation data to obtain a low-dimensional space receiving data vector; on the basis of a non-circular characteristic of the signal and an Euler formula, an actual-value receiving data vector with array aperture doubling is constructed; arotation invariance relationship of a virtual array with aperture extending is constructed; a covariance matrix of the extended receiving data is calculated and feature value decomposition is carriedout on the matrix, an actual-value signal sub space is estimated; new actual-value signal sub space is defined and a rotation invariance equation of the new actual-value signal sub space is calculated; and a DOA estimation value of the target is calculated. Therefore, the DOA estimation accuracy is improved obviously and the computational complexity of the ESPRIT algorithm is reduced substantially. The estimation method is suitable for the low-signal-to-noise-ratio and low-fast-beat-number occasions.

The invention discloses a weighting LMS detection method for harmonic currents. The method comprises aspects that (1) cost functions are defined to be weighted square sums of posteriori errors, so that interference of harmonic currents on filter weight coefficients is eliminated; (2) updating increments of the filter weight coefficients are achieved through iteration, so that the calculation complexity is reduced; (3) conditions for guaranteeing stability are given. Compared with an LMS algorithm and a recursive least square (RLS) algorithm, the weighting LMS detection method has the advantages of being small in steady-state error and high in jump occasion tracking capacity to load currents. The calculation amount of the method is slightly larger than that of the LMS algorithm but smaller than that of the RLS algorithm, so that the method is applicable to detection of harmonic currents.

The present invention discloses a real-time recovery method of moving-target in high frame frequency infrared image sequence. The method includes steps as follows: inputting high frame frequency infrared image frame, confirming sporting direction and distance parameter of moving-target in image frame, processing median filtering in sporting direction, confirming membership degree of seed pixel and neighborhood pixel according with given membership degree function, confirming pixel value of seed pixel according with judgement criterion, outputting image frame recoveried by moving. The method reduces noise effect by median filtering to input image sequence; has no strict request for size and moving speed of target, and has efficient in working; the median filtering, convolution operation and confirming membership degree operation of seed pixel and neighborhood pixel are processed in air space, and not need global properties of noise which makes arithmetic simply, no ringing effect and hardware realized real-time.

The invention discloses an oil production data frequent pattern mining method based on weak wildcard, and relates to the field of data mining. The oil production data frequent pattern mining method based on the weak wildcard comprises the steps that 1, oil field daily fluid production time series data is converted into a coding sequence; 2, the coding sequence is mined to obtain different types of frequent sequence patterns, and an oil well is comprehensively depicted from various angles. The method has the advantages that the mining problem of three frequent sequence patterns is defined, the different types of frequent patterns can be mined from actual oil well production data, and the oil well is comprehensively depicted from the different angles; an algorithm is simple and efficient, a pruning algorithm is achieved, the time complexity is low, and the method is conveniently achieved in real time; a pattern filter technique is proposed, the different types of frequent patterns such as the powerful pattern, the special pattern and the popular pattern can be obtained through filtration for the different requirements; the method can be widely applied to various time series data.

The invention discloses a low-voltage power distribution short-circuit current peak prediction method. On the basis that short-circuit fault early-stage diagnosis of a low-voltage power distribution system is realized, and based on a grey prediction model GM (1, 1), the invention provides an improved GM (1, 1) prediction model used for short-circuit current peak prediction. The model is capable of accurately predicting the developing trend and the peak of a short circuit current by using a small amount of collected current data and a voltage initial phase angle in a short current case. The low-voltage power distribution short-circuit current peak prediction method has the advantages that the prediction precision is high, the data processing amount is small, the operation amount is small, the program operation speed is high, etc; in addition, real-time realization of the method on a hardware system is facilitated, and after peak prediction is utilized to realize early-stage global selectively protection over front and rear circuit breakers of the low-voltage power distribution system, the damages of the short circuit to lines and equipment are substantially reduced, so that the safety and the continuity of power supplying lines are further improved.

The invention discloses a real-time tracking method for an infrared image target with multi-feature fusion. The real-time tracking method comprises the following steps of: initializing a target tracking point position; initializing a target model; calculating a target candidate model; calculating a coefficient of unified feature Bhattacharyya and weight coefficients between feature; calculating a new tracking position of a current frame target; estimating the coefficient of the unified feature Bhattacharyya at the new position; and comparing the two coefficients of the unified feature Bhattacharyya and outputting results. The real-time tracking method can be used for adaptively calculating the weight coefficients between multiple features, enhances the robustness of target tracking, ensures the stability of target tracking, solves the problem of tracking point drifting caused by unstable single feature, and effectively improves the accuracy of target tracking.

The invention provides a secondary radar answer code extracting and confidence interval marking algorithm, synthetically using position of answer pulse, sigma and Delta information and adjacent answer information, adopting an idea of establishing a pulse information list for each answer pulse, convenient to implement software programming. It has the characters of high processing efficiency, strong self-adapting ability, convenience for real-time implementation, etc. It can be used in processing answer signals for secondary radar, enemy-self identifier, and civil aviation management system.

The invention relates to the field of access control in a wireless communication technology, in particular to an opportunistic channel accessing and switching method and device. The method comprises the following steps of: receiving, by a receiving end, an RTS (Request To Send) data packet comprising a training sequence transmitted by a transmitting end through a detected idle channel; acquiring a channel state of the idle channel according to the training sequence; judging whether the channel state is greater than or equal to optimal threshold k*; and if the channel state is greater than or equal to the optimal threshold k*, accessing to the idle channel to perform transmission of a data stream, and otherwise, switching the channel by the transmitting end and the receiving end according to a shared channel detection sequence, and searching and detecting a next idle channel. According to the method and the device, a user can obtain the channel state according to the training sequence, adjust the accessing and the switching of the channel and maximally utilize the instantaneous transmission opportunity of the channel in time-frequency two dimension, so that the utilization efficiency of the channel is improved; diversity utilization is performed on a link layer; and compared with the conventional physical layer diversity technology, extra accessory hardware is not required, and the conventional communication equipment is favorably applied.

The invention discloses an infrared image noise time domain filtering method based on registration. The method comprises the following steps of: acquiring an original infrared image, and calculating an initial noise threshold value Fth(0) of different coordinate positions of the original infrared image; acquiring the original infrared image of the kth frame Forg (k), and calculating the noise threshold value Fth(k) of the original infrared image of the kth frame; carrying out the low-pass filtering on the original infrared image Forg (k) of the kth frame and the time dome filter image Ffilt (k-1) of the (k-1)th frame to obtain a relative displacement (delta x, delta y) between the low-pass image calculated low-pass images for showing the relative displacement of Forg(k) and Ffilt (k-1); and outputting a time domain filter image Ffilt (k) of the kth frame.

The invention relates to a recursive filtering modulating method of a transient broadband excitation signal of parametric array sonar. The method comprises the following steps: performing recursive filtering for a signal to be processed through a recursive filtering device to obtain X(n+1); obtaining an envelope E(n+1); performing up-sampling for the envelope E(n+1) through an interpolation filter; performing double-sideband amplitude modulation together with a digital carrier signal; performing D / A conversion to obtain an analog signal, and thus obtaining the excitation signal of a parametric emitting system. The method applies to both parametric array sonar and an air acoustical parametric array system; the application scope of acoustical parametric array is widely expanded, and a predictable huge potential market value is brought.

The invention provides a selective cognitive access method on the basis of the quality of channels. The selective cognitive access method includes steps of acquiring the optimal threshold of a cognitive radio system; enabling a cognitive terminal to sequentially perceive and detect the various channels when the cognitive terminal needs to transmit data, and judging whether the real-time state of a detected channel Ci meets conditions or not; enabling the cognitive terminal to access the channel Ci if the real-time state of the channel Ci meets the conditions; sequentially transmitting the data via the channel Ci; enabling the cognitive terminal to monitor the real-time state of the channel Ci; enabling the cognitive terminal to instantly release the current channel Ci if the cognitive terminal detects that the real-time state of the channel Ci is lower than or equal to the optimal threshold; and perceiving and detecting the channels again. The conditions include that the channel Ci is an idle channel, and the link quality of the channel Ci is superior to the optimal threshold. The selective cognitive access method has the advantages that a channel access and release decision is made for the cognitive terminal under joint consideration of the availability and the instantaneous link quality of the channels, and the frequency spectrum utilization efficiency can be greatly improved.

The invention relates to a multicomponent fluorescence lifetime and component proportion estimation method applied to TCSPC (time-correlated single photoncounting). Firstly, acquired histogram data are combined to form a new histogram with the smaller interval, so that the influence of partial noise is eliminated, and the computation burden of the algorithm is greatly reduced. Autocorrelation computation is performed on interval data of the new histogram, and an autocorrelation matrix is smoothed according to characteristics of TCSPC. Eigenvalue decomposition is performed on the autocorrelation matrix, and signal subspace is obtained. According to the possible fluorescence life span, a search vector is formed, the fluorescence lifetime is estimated according to a searched spectral peak position, and content of various components is estimated with the least square method. With the adoption of the method, fluorescence lifetime information of all the components can be computed in one step without knowing general fluorescence lifetime information and general component content information of the multiple components.

The invention discloses a space intersection control method of two-stage constant thrust, which is used for solving the technical problem that the engine is opened and closed frequently during the intersection process when the prior intersection control method of constant thrust is achieved. The technical solution is that the minimum opening-closing time Tmin constraint of the engine is introduced to the intersection control problem of the two-stage constant thrust engine; and the optimal intersection thrust under quadratic optimization function index is designed by rolling forecast principle. Because of considering the minimum opening-closing time constraint of the engine, the problem that the engine is opened and closed frequently is solved and the design difficulty of the engine is reduced; and the optimal design method has good robustness for design model error, measurement error and intersection thrust error.