37results about How to "Improve target detection probability" patented technology

The present invention provides a pulse Doppler radar polarization anti-jamming method under a complicated interference environment. By utilizing the method of the present invention, the inhibition capability aiming at various interference, such as chaffs, active suppression, cheat, etc., can be improved substantially, and the targets can be detected effectively. The method is realized by the following technical scheme of inputting a radar dual polarization echo signal, determining whether the active suppression-type interference exists, when the suppression-type interference exists, carrying out the polarization cancellation; then calculating the target signal walking time between the front and back pulses, and carrying out the range walking correction on a pulse sequence; and then carrying out the phase-coherent accumulation on a dual polarization channel, shifting the zero to a frequency spectrum center in a frequency shift manner, identifying the channel number of a target in a Doppler-range two-dimensional matrix, setting a two dimensional tracking gate of the target, and carrying out the two dimensional constant false alarm detection in the tracking gate; finally, carrying out the target polarization ratio detection determination, and outputting a signal passing the detection determination as a target signal after the interference inhibition, thereby improving the correct detection probability of the target.

The invention discloses a method for detecting an infrared motion target in real time for background adaptive estimation. The method comprises the following steps of: (1) initializing a background model BG (0); (2) inputting a kth-frame original infrared image Xorg (k), wherein k is equal to 1, 2 to K; (3) restraining a space domain non-uniformity noise and a time domain random noise of the kth-frame original infrared image Xorg (k), and outputting an image Xdeal (k) which is subjected to noise restraint; (4) registering the image Xdeal (k), and outputting a registered kth-frame infrared image Xreg (k); (5) updating the background model, namely updating a background model BG (k) of the kth-frame infrared image by using an adaptive forgetting factor method; (6) performing difference operation on the kth-frame infrared image Xorg (k) and the background model BG (k), and outputting a difference operation result Xout (k); and (7) calculating the optimum segmentation threshold value Thopt of a target and a background in the Xout (k) according to a maximum inter-class variance theory to finish detection of the motion target. The method has the advantages that: by image pro-processing, the problem of over-sensitivity in noise and scene change in the conventional background difference method is effectively solved, and the detection probability of the target is improved.

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 a low-altitude target detection method for a frequency diversity array radar, belonging to the field of phased array radar low-altitude target detection. According to the method, due to the scanning characteristics of an FDA radar, the beam direction of the radar is related to a radial distance and a frequency difference, by introducing a frequency difference between different transmitting elements, a signal-to-noise ratio loss brought by a multipath effect in a low-altitude target environment can be effectively suppressed. Then, a generalized likelihood ratio test (GLRT) method is used to derive an FDA radar low-altitude target detector, and a target detection probability can be effectively improved under a certain false alarm rate. Finally, through the design of sub modules of matrix multiplication, matrix determinant calculation the like, an FDA radar low-altitude target detector is realized in an FPGA hardware platform, and the real-time detection of the FDAradar low-altitude target detection is effectively improved. In summary, according to the method, in a low-altitude target environment, the scanning characteristics of the FDA radar can be used to effectively complete the detection of a low-altitude target, and the method has high practicability in modern warfare.

The invention discloses an infrared weak and small target detection method. The method at least comprises the following steps: S1, an image preprocessing step; s2, an image blocking step: dividing theto-be-processed image into four overlapped sub-images, and performing parallel processing; s3, carrying out partition target segmentation on the sub-images, carrying out target segmentation on a large area by utilizing a maximum between-cluster variance method, carrying out target segmentation on a cell by utilizing a local signal-to-clutter ratio threshold segmentation method, and carrying out target fusion processing on two segmentation results; s4, carrying out noise filtering on the sub-images, wherein the noise filtering comprises scatter filtering and shape filtering; s5, calculating target information, wherein the target information at least comprises a target centroid position, a size and a signal-to-noise ratio; and S6, performing target fusion processing on the processing results of the four sub-images, deleting targets repeatedly detected in the overlapping region, and outputting target information. According to the method, an improved method is designed for infrared imagenoise suppression and small and weak target detection, the small and weak target detection probability can be effectively improved, and the false alarm rate is reduced.

The present invention discloses a dual-polarized SAR image system which is low in target detection false alarm rate and high in detection rate. According to the technical scheme, a receiving and transmitting conversion module receives horizontal polarization signals of an H transmitting antenna and vertical polarization signals of a V polarization receiving antenna at the same time, the polarization form of the transmitting signals is changed, and a data acquisition board carries out digital down-conversion on acquired frequency mixing signal data and converts the frequency mixing signal datato a baseband; the H-channel pulse pressure module and the V-channel pulse pressure module are connected with a reference function module in parallel, the reference function module carries out Dopplerfrequency modulation, Doppler center estimation, distance bending correction, walking correction, parameter estimation and orientation matching filtering on data, and after a dual-polarization SAR image is obtained, determination fusion processing is carried out on the target to obtain a target detection result, and matrix singular value SVD decomposition is carried out on the covariance matrix corresponding to each pixel so as to obtain a characteristic value of the covariance matrix and a polarization entropy value of each SAR image pixel.

The invention discloses a UHF waveband multi-channel radar radial speed detection method based on a tensor product. The problems that in the prior art, the low-speed moving target detection probability and radial speed estimation precision are low under the condition that an antenna bearing aperture is limited are mainly solved. According to the implementation process, the method comprises the steps that a tensor product operation is carried out on data vectors received by a radar to obtain data with a virtual aperture expanded; a tensor product operation is respectively carried out on search clutter guide vectors and search target guide vectors to obtain search clutter guide vectors and target guide vectors with the virtual aperture expanded; the search clutter guide vectors and target guide vectors with the virtual aperture expanded are tensioned into search signal subspace; the radial speed of a target is estimated through signal subspace fitting. The method has the advantages of being high in low-speed object detection probability and radial speed estimation precision, and is used for estimating the low target radial speed under the condition that the antenna bearing aperture is limited.

The invention discloses a distributed passive radar target detection realization method, and the method belongs to the technical field of passive radar target detection. An existing target detection method is characterized by carrying out correlation and over-threshold processing independently on each bistatic pair to finish target detection, and then, obtaining bistatic distance and Doppler information of a target through estimation and carrying out target location, which results in the problem of complex ambiguous location needing to be solved in the follow-up target exact positioning process. In order to solve the problem above, the invention introduces target location and velocity vector and constructs centralized target detection statistics, so that target positioning is realized while realizing target detection, and the problem of ambiguous target location no longer needs to be treated. Besides, the method carries out non-phase-coherent accumulation on a plurality of transmitter-receiver pairs before detection to obtain space diversity gains, thereby improving target detection probability, obtaining more-stable target detection performance and providing basis for continuous and stable tracking of the target.

The invention discloses a multi-target detecting and positioning method based on the perspective radar imaging of buildings. The method comprises the following steps: performing backward projection imaging; superimposing binarized images; strengthening the targets; obtaining the image matrix accumulation vectors; extracting the positions of the targets and normalizing a target region. According to the invention, a backward projection imaging method is used to speed up the imaging in a to-be-detected area; and through the superposing of binarized images and the strengthening of objects, the continuous inter-frame target association after the non-connected area detection imaging can be realized so as to increase the target amplitude for afterward detections. Through the obtaining of the image matrix cumulative vectors, the extracting of target matching and the normalizing of the target region, the image direction based multi-target enhanced detection is realized, which effectively enhances the targets with low echo amplitude due to the covering of strong targets. Therefore, detection efficiency for weak targets is increased. With good practicability and good detection efficiency, the method of the invention can be of highly significance in the technical field of perspective radar imaging of buildings.

Disclosed is a method for detecting a point target in an infrared image sequence. The method comprises the steps of (1) estimating a noise variance of a current frame image, adopting a bilateral filtering method to preprocess the image, (2) adopting the Robinson-Guard filtering method based on a template mid value to conduct filtering on the preprocessed image, (3) conducting binarization processing on the image, marking target points in the image, recording positional information of the target, (4) initializing parameters of a pipeline filter, (5) utilizing target positional information of first three frames for predicating the target position of the current frame, searching for the target, updating related information in a target position information sheet, conducting judgment to output the target information, and (6) repeating the steps until processing of all the images in the infrared image sequence is completed. According to the method for detecting the point target in the infrared image sequence, background suppression is effectively carried out, the false alarm probability is reduced, and the detection probability of the target is improved through the detection of the multi-frame sequence images.

The invention provides a special-shaped radar combined decision target detecting method. A high threshold and a low threshold are utilized for performing CFAR detection on original video data of eachradar. After performing high-threshold detection and low-threshold detection on each data, a distance condensation point trace is extracted from the data. Normalization is performed on the point traceamplitude according to distance point trace local signal clutter / noise ratio and the noise substrate of each radar. Combined detection and decision is performed on the low-threshold detection condensation point traces of all radars according to a radar distance measurement error. Furthermore the high-threshold detection condensation point traces of multiple radars are combined, thereby finishingoriginal-video-grade multiple-radar combined target detection processing. According to the method of the invention, the high threshold and the low threshold are utilized, thereby improving target detection probability. For each radar, the distance point trace is extracted and then combined determining is performed, thereby preventing a problem of direct fusion processing incapability caused by different multiple-radar sampling rates, different resolutions, different noise substrates and the like.

The invention discloses a radar sensor network deployment method for multi-target detection and belongs to the field of radar sensor network target detection. The radar sensor network deployment method for multi-target detection includes a radar sensor network DDS station distribution method and a BT multihop fusion algorithm, wherein the DDS station distribution method is used for regarding a monitoring region as an appropriate rectangle and performing even coverage on the monitoring region according to the radar sensor resource situation, the BT multihop fusion algorithm is used for effectively fusing information of multiple radar sensors in a multihop transmission mode, and finally comprehensive judgment is performed. The radar sensor network deployment method includes the radar sensor network DDS station distribution method and the BT multihop fusion algorithm, and the DDS station distribution method is used for evenly deploying the radar sensors in the monitoring region, can effectively monitor the region and effectively improves the target detection probability. The BT multihop fusion algorithm integrates a fusion algorithm with a radar sensor network, and multiple radar detection results in the network are fused to enable target detection results to be good.

The invention discloses a target detection method based on a coherent radar non-coherent accumulation mode. The method comprises the following steps: S1, performing sampling to obtain a frame of two-dimensional echo data; S2, performing pulse compression on each piece of data in the S1; S3, performing range walk calibration on the data in the S2; S4, performing coherent accumulation on the data in the S3; S5, repeating the steps S1 to S4 to obtain multi-frame coherent accumulation data; S6, performing inter-frame alignment on the multi-frame coherent accumulation data obtained in the step S5; S7, performing non-coherent accumulation on the multi-frame coherent accumulation data after inter-frame alignment; and S8, performing target detection based on the non-coherent accumulation data in the S7. The method has the advantages that range walk calibration is realized based on an inter-pulse autocorrelation method, and the detection of a moving target subjected to long-time coherent accumulation is realized; according to the method, after peak target alignment is carried out on two-dimensional data planes among multiple adjacent frames, non-coherent accumulation is carried out, then target detection is carried out, the purpose of improving the signal-to-noise ratio is achieved, and meanwhile target speed estimation can be achieved.

The invention discloses a slice interference suppression method for sub-band frequency coding, and mainly solves the problem that a target cannot be correctly recognized when interference signal energy is greater than signal energy due to the fact that interference data which is intermittently sampled and forwarded cannot be eliminated only by utilizing correlation in the prior art, and the target cannot be correctly recognized when the interference signal energy is too large. And the interference residue of the transition zone submerges the adjacent target signal segment, so that the target cannot be correctly identified. The method comprises the following specific steps: 1, estimating slice interference parameters; 2, generating a transmitting signal of an intra-pulse sub-pulse frequency; 3, coding the sub-pulse frequency of the transmitted signal according to the interference parameter; 4, constructing an echo signal waveform containing interference and a target; and 5, segmented pulse pressure interference resistance is realized. According to the method, frequency bands of sampled and forwarded sub-pulses and non-sampled sub-pulses are respectively concentrated through frequency coding, so that the target detection probability, the target accumulation gain and the target detection reliability are improved.

The invention discloses an infrared target detection method and device based on multi-feature fusion, equipment and a medium. The method comprises the following steps: acquiring a detection target image; performing global threshold segmentation on the detection target image to obtain a binary image; performing connected domain marking on the binary image to obtain candidate targets; performing feature extraction on each candidate target, and performing filtering processing on each feature channel to obtain a feature component value of each candidate target; performing multi-feature fusion on the candidate targets to obtain a normalized feature vector; and judging whether the normalized feature vector reaches a detection threshold, if the normalized feature vector reaches the detection threshold, reserving the candidate targets, and otherwise, deleting the candidate targets. Aiming at the problems of low infrared image contrast, less target feature information and the like, multi-feature fusion processing is performed by mining multiple feature information of targets and clutters, and parallel processing is performed by using multiple feature channels, so that the target detection probability is improved, and the false alarm rate is reduced.

The invention discloses a radar detection blind area calculation method and device. The radar detection blind area calculation method comprises the following steps: acquiring digital down-conversion radar data; supplementing N zeros to the tail of the radar data to obtain zero filling data, wherein N is the number of filter coefficients; performing pulse compression on the zero filling data by using a finite-length unit impulse response filter in a field-programmable gate array; and carrying out target solution on the data after pulse compression. According to the radar detection blind area calculation method and device, the radar performance is high, and the short-distance detection probability is high.

The invention discloses a 4D millimeter wave radar point cloud-based vehicle detection method. The method comprises the steps of filtering outliers and noise points in a point cloud data set by using a fusion filtering algorithm; performing point cloud clustering by using an improved DBSCAN algorithm, recognizing point cloud data with similar characteristics, and completing point cloud preprocessing; and detecting the preprocessed 4D millimeter wave radar point cloud data set by using a three-branch Point RCNN network to obtain a detection result. According to the invention, high target detection probability is realized, and the problem that 4D millimeter wave radar target detection technologies are deficient is preliminarily solved.

The invention discloses a radar target constant false alarm detection method based on sparse signal processing. The method comprises the following steps of: obtaining the parameters of a pulse Dopplerradar system; constructing a sparse strip-shaped dictionary matrix A; calculating a detection statistic magnitude |AHy|; calculating a judgment threshold lambda; and obtaining a radar target constantfalse alarm detection result. According to the method, a sparse signal processing model is adopted, the sparse strip-shaped dictionary matrix A is constructed, and the detection statistic magnitude is calculated through A, so that when a target exists near a certain range unit, the detection statistic magnitude of the range unit is increased to some extent; and the sparse signal processing modelis adopted, the judgment threshold is calculated through known noise power, and the problem that in the prior art, the judgment threshold is raised by a target in a reference window is solved. Throughthe combined action of the two, the target detection probability is improved while the constant false alarm characteristic of radar target detection is ensured. The method is especially suitable fordense radar target scenes.

The invention discloses an arc array radar moving target focusing detection method based on radial velocity search. The method sequentially comprises the following steps of carrying out range direction processing on echo signals of an arc array radar, and designing a plurality of groups of different matched filters for traversal filtering to realize focusing detection of the moving target. A radial speed search mode is adopted, different matching filters are designed for different reference radial speeds, and traversal matching is carried out on echo signals of the arc array antenna, so that a real moving target at a corresponding speed can be better matched, the energy of the moving target is improved in echo signal processing, and the target detection probability is improved.

The invention discloses a multi-sensor multi-target tracking method based on posterior track estimation, and the method comprises the steps: obtaining the posterior track probability hypothesis density of each sensor and a corresponding posterior track estimation set through a track probability hypothesis density filtering method, and constructing an association cost matrix between different sensors; dividing posterior tracks in the posterior track estimation sets of different sensors into associated tracks and non-associated tracks; fusing the probability hypothesis densities of the associated tracks among different sensors to obtain a fused associated track probability hypothesis density; error tracks in the non-associated tracks among different sensors are removed, the probability hypothesis density of the non-associated tracks after the error tracks are removed is fused with the probability hypothesis density of the fused associated tracks, and the probability hypothesis density of the fused tracks among the different sensors is obtained; and according to the fusion track probability hypothesis density among different sensors, extracting to obtain a multi-sensor estimated track state. According to the invention, the communication load is obviously reduced, and the problem of missing detection in GCI fusion is solved.

The invention discloses a multi-target detection and positioning method based on building perspective radar imaging. The method includes back projection imaging, superimposed binarized images, target enhancement, acquisition of image matrix accumulation vectors, target position extraction, and target area normalization. . The invention uses the backward projection imaging method to speed up the imaging of the area to be detected, and realizes the target correlation between consecutive frames after the imaging of the non-connected domain detection by superimposing the binarized image and the target enhancement processing, and enhances the target amplitude, which is beneficial to the subsequent detection. The multi-target enhancement detection based on image directionality is realized by acquiring image matrix accumulation vector, target matching extraction, and target area normalization processing, which effectively enhances targets with low echo amplitudes covered by strong targets, thereby improving weaker targets. The detection rate of the target has the advantages of good real-time performance and high target detection probability, and has extremely high application value in the field of building perspective radar technology.

The invention discloses a frequency diversity array radar low-altitude target detection method, which belongs to the field of phased array radar low-altitude target detection. First of all, the scanning characteristics of the FDA radar make its beam pointing related to the radial distance and the frequency difference. By introducing a frequency difference between different transmitting array elements, the signal-to-noise ratio caused by the multipath effect in the low-altitude target environment can be effectively suppressed. loss. Then, the generalized likelihood ratio test (GLRT) method is used to derive the FDA radar low-altitude target detector, which can effectively improve the target detection probability under the condition of a certain false alarm rate. Finally, through the design of sub-modules such as matrix multiplication and matrix determinant calculation, the FDA radar low-altitude target detector is realized on the FPGA hardware platform, which effectively improves the real-time performance of FDA radar low-altitude target detection. To sum up, this method can effectively complete the detection of low-altitude targets by using the scanning characteristics of FDA radar in the low-altitude target environment, and has high practicability in modern warfare.

The invention discloses a method for detecting weak spot targets in an infrared image, which adopts structural elements of 5×5 dimensions in 8 directions to extract all possible targets of different scales; obtains the target region of interest through adaptive threshold processing, and effectively improves the target Signal-to-noise ratio; use the judgment criterion of background edge points and point targets in the local neighborhood to remove the residual background edge points; remove noise points and obtain the target motion trajectory according to the matching relationship between frames; the algorithm complexity is not high and meets real-time The results show that the target detection probability of the present invention is high, and the false alarm rate is low at the same time, which has important application value.

The invention discloses a robust design method for slow time series in an independent interference environment, which belongs to the field of radar signal processing. For undulating point targets with unknown speeds, the invention normalizes the Doppler f T modeled as f 0 Nearby uniformly distributed random variables, and their second-order statistical properties are described. Finally based on f T The covariance matrix M of constructs a robust design optimization problem to maximize f T The SNR in the distribution interval can improve the target detection probability in this interval, and it has better Doppler robustness compared with the optimal design in which the target Doppler is accurately known. Compared with the robust design method in the unknown Doppler interval [0,1], the optimization range of the present invention is more targeted, so it can achieve a better optimization effect. In addition, the algorithm used in the present invention has the advantages of semi-positive definite relaxation algorithms. Lower computational complexity improves algorithm efficiency.

The invention discloses an infrared target detection method, device, equipment and medium based on multi-feature fusion. The method includes acquiring a detection target image; performing global threshold segmentation on the detection target image to obtain a binarized image; Connected domain marking is performed to obtain candidate targets; feature extraction is performed on each candidate target, and each feature channel is filtered to obtain the feature component value of each candidate target; multi-feature fusion is performed on candidate targets to obtain a normalized feature vector ; Judging whether the normalized feature vector reaches the detection threshold, if it reaches the detection threshold, the candidate object is retained, otherwise, the candidate object is deleted. Aiming at the problems of low contrast of infrared images and less target feature information, the present invention performs multi-feature fusion processing by mining various feature information of targets and clutter, and utilizes multiple feature channels for parallel processing, thereby improving target detection probability and reducing false alarm rate .

Disclosed is a method for detecting a point target in an infrared image sequence. The method comprises the steps of (1) estimating a noise variance of a current frame image, adopting a bilateral filtering method to preprocess the image, (2) adopting the Robinson-Guard filtering method based on a template mid value to conduct filtering on the preprocessed image, (3) conducting binarization processing on the image, marking target points in the image, recording positional information of the target, (4) initializing parameters of a pipeline filter, (5) utilizing target positional information of first three frames for predicating the target position of the current frame, searching for the target, updating related information in a target position information sheet, conducting judgment to output the target information, and (6) repeating the steps until processing of all the images in the infrared image sequence is completed. According to the method for detecting the point target in the infrared image sequence, background suppression is effectively carried out, the false alarm probability is reduced, and the detection probability of the target is improved through the detection of the multi-frame sequence images.