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43results about How to "Realize multi-target tracking" patented technology
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Multi-target tracking system based on deep learning and implementation method
InactiveCN106875425AReduce redundancyHigh speedImage enhancementImage analysisFixed frameMulti target tracking
The invention relates to a multi-target tracking system based on deep learning and an implementation method. The method comprises the following steps: getting the target position of a first frame through target detection, and adding multiple to-be-tracked targets to a tracking queue; inputting a next frame of image and traversing the tracking queue to get the position of the target in the next frame; after getting the position of the target in the next frame, judging whether the target is off the screen based on thresholds; if the target is not off the screen, invoking target detection every other fixed frame, and calculating the IOU (intersection over union) of the target detection result and the tracking result; if IOU<0.1, judging that a new target is added to the screen, and adding the target to the tracking queue; if IOU>0.5, replacing the tracking box with the target detection box to correct the position; and continuing target tracking. By carefully designing the network structure and improving the training method, under the condition of high tracking precision, the tracking speed is increased significantly, network redundancy is reduced, and the size of the model is reduced.
Owner:北京飞搜科技有限公司
Multi-target tracking method based on millimeter-wave radar
InactiveCN110361727AAchieve perceptionImprove accuracyRadio wave reradiation/reflectionPattern recognitionCluster algorithm
The invention discloses a multi-target tracking method based on millimeter-wave radar. The method comprises acquiring point cloud data by millimeter-wave radar; clustering the point cloud data to distinguish the echo signals of different targets; and estimating the state information of multiple observed targets according to a clustering result so as to track the multiple targets. The method improves a DBSCAN clustering algorithm according to the characteristics of the millimeter-wave radar, improves the accuracy of esimating the number of the targets and the states of the targets, and predictsand tracks the trajectories of the multiple targets in a complex environment by using a Kalman filter and data association algorithm.
Owner:ZHEJIANG UNIV
Multiple trace point-based human body action recognition method
ActiveCN101964047ARealize multi-target trackingSimple methodImage analysisCharacter and pattern recognitionPhysical medicine and rehabilitationMulti target tracking
The invention relates to a multiple trace point-based human body action recognition method. The method comprises the following steps of: based on an action requirement needing to be judged, setting at least one trace point on a human body or a sports apparatus to be tested; acquiring the space positions of each track point at different moments and recording the acquired space positions as a group of data points corresponding to the trace points; calculating corresponding action data of each trace point based on the action requirement needing to be judged by using the space position data of the group of data points corresponding to each trace point; and recognizing the movement action of the human body to be tested according to the corresponding action data of each trace point. The method can also recognize a human body gesture. The method has the advantages of realizing tracking of a plurality of targets, tracking a plurality of positions of the human body to be tested, recording the movement locus of a tracked position, positioning and describing the posture of the human body and truly reflecting the movement situation of the human body.
Owner:SHENZHEN TAISHAN SPORTS TECH CO LTD
Multi-target tracking method integrating obvious characteristics and block division templates
ActiveCN104091348AImprove the ability to adapt to scene lighting changesPrecise positioningImage analysisMulti target trackingLevel data
The invention provides a multi-target tracking method integrating obvious characteristics and block division templates. A target motion area is detected by adoption of RGB component background difference and an iterative threshold, and the adaptive ability of a motion detection algorithm to scene illumination change is improved. Based on target area block division, a motion pixel color saliency weighted block centroid model, block centroid shifting fusion and a scale updating method, the calculation efficiency is high, the resistance to partial occlusion is high, and the similar color scene jamming ability is strong. The problem of multi-target measuring-tracking distribution is solved by adoption of two-level data association, and an occluded local area can be accurately positioned. Therefore, adaptive template updating is guided by an occlusion matrix, a reliable global centroid transfer vector is obtained by making use of effective colors and motion information of blocks, and finally, continuous, stable and fast multi-target tracking in complex scenes is realized. The multi-target tracking method integrating obvious characteristics and block division templates is applied to fields like intelligent video surveillance, in-air multi-target tracking and attacking, and multi-task tracking intelligent robots.
Owner:南京雷斯克电子信息科技有限公司
UAV onboard multi-target detection tracking and indication system and method
ActiveCN107977987AHigh precisionImprove robustnessImage enhancementImage analysisControl systemFeedback control
The invention discloses an UAV onboard multi-target detection tracking and indication system and method, and belongs to the technical field of target detection tracking and indication. The invention discloses an UAV onboard multi-target detection tracking and indication system comprising a multi-target detection and tracking system and a multi-target laser indication system. The multi-target detection and tracking system comprises an infrared camera, a visible light image sensor and a high-speed parallel image processing and tracking feedback control circuit. The multi-target indication systemincludes an integrated laser, a fast reflector, a fast reflector control module, and a laser control module. In order to improve laser indication accuracy, the UAV onboard multi-target detection tracking and indication system also includes a laser pointing control system. The invention also discloses an UAV onboard multi-target detection tracking and indication method based on the UAV onboard multi-target detection tracking and indication system. The UAV onboard multi-target detection tracking and indication system and method realize multi-target all-weather detection tracking and high-precision stable laser indication under the condition of a UAV onboard platform.
Owner:BEIJING INSTITUTE OF TECHNOLOGYGY
Video multi-target tracking method based on multi-Bernoulli characteristic covariance
ActiveCN106408594AEfficient extractionRealize multi-target trackingImage enhancementImage analysisSelf adaptiveSize change
The invention discloses a video multi-target tracking method based on multi-Bernoulli characteristic covariance which belongs to the technical field of artificial intelligent and intelligent information processing and aims mainly to solve the problems that in complex environment, the targets in video multi-target tracking are very close to each other and that the size change and tracking to them are not accurate. This method, according to the multi-Bernoulli filtering framework, is introduced by an integration graph and employs a particle filter method to track video multi-targets whose number are in constant change in combination with the characteristic covariance technology. Based on that, a self-adaptive mechanism and a size self-adaptive mechanism for targets in close contact are proposed to realize the self-adaptive processing of targets in close contact and the tracking windows respectively. Finally, a particle filter method is utilized to realize the self-adaptive recognition and tracking of the video multi-targets through their movement trajectories. The method of the invention is highly robust and has a good anti-interference ability. The method meets the design requirement of a practical engineering system and has good engineering application value.
Owner:JIANGNAN UNIV
A vehicle retrograde motion intelligent detection method based on tracking trajectory analysis
ActiveCN109948582AImprove reliabilityRealize multi-target trackingCharacter and pattern recognitionCorrelation filterVehicle detection
The invention discloses a vehicle retrograde motion intelligent detection method based on tracking track analysis. The method comprises the following steps: detecting a target vehicle in a video imageby utilizing a primary classifier and a secondary classifier; extracting a target vehicle area, distributing a nuclear correlation filtering tracker for the target vehicle; wherein each target vehicle is matched with one nuclear correlation filtering tracker, the nuclear correlation filtering tracker is used for obtaining a tracking area of the target vehicle, then the movement track growth direction of the target vehicle is obtained according to the tracking area and compared with the initially marked retrograde movement direction, and if the movement track growth direction is the same as the initially marked retrograde movement direction, the target vehicle retrograde movement occurs; And if not, the target vehicle does not run reversely. By means of the mode, real-time detection of vehicle retrograde running is achieved, and the problems existing in manual detection are solved; And meanwhile, the reliability of vehicle detection and recognition is improved by using the cascade classifier, and simultaneous tracking of multiple vehicle targets is realized.
Owner:HUNAN UNIV
Multi-characteristic matching multi-target tracking method based on Hough forest
ActiveCN107145862AEnhanced description abilityEasy to handleCharacter and pattern recognitionNODALMulti target tracking
The invention discloses a multi-characteristic matching multi-target tracking method based on Hough forest. A conserved and reliable track fragment is obtained through double-threshold correlation. A positive and negative sample set is generated in an online manner according to a sample selecting principle. The Hough forest is constructed. Through Hough forest learning, training samples with color, shape, class and motion information are divided to different leaf nodes. Statistics information of the leaf node is used for forecasting an association probability of two track fragments. When a reliable long-track fragment is obtained, the reliable long-track fragment is converted to a re-matching problem between the tracks. Two manners of similarity measuring and characteristic point matching are used. The reliable long-track fragment is associated to a real track through the association probability, thereby finishing matching. The multi-characteristic matching multi-target tracking method has advantages of settling problems of error accumulation and low tracking precision, improving capability for processing target shielding and deformation, and realizing multi-target tracking in a complicated scene.
Owner:SHANDONG UNIV
Convex optimization method for three-dimensional (3D)-video-based time-space domain motion segmentation and estimation model
ActiveCN102592287AEfficient use ofRealize multi-target trackingImage analysisSteroscopic systemsSpace time domainTime space
Owner:ZHEJIANG UNIV
Multi-target detection and tracking method under conditions of low observability and high clutter
InactiveCN106468771AEasy to detectRealize multi-target trackingRadio wave reradiation/reflectionAcoustic wave reradiationSonarSlide window
The invention discloses a multi-target detection and tracking method under conditions of low observability and high clutter, and belongs to the technical field of radar and sonar. The idea of the method is that a plurality of measurements from different propagation paths to a receiver are considered as the possible target measurements during the processing of the target-measurement correlation, and are enabled to be correctly correlated with each known multi-path measurement function, thereby obtaining the accumulation of target information, and improving the target detection capability; and then the target tracking is carried out in a mode of a sliding window. The method employs the target information which is transmitted to a sensor through different paths, enables the measurement information to be correctly correlated with each known multi-path measurement function, thereby obtaining the accumulation of target information, and improving the detection capability of a target under the conditions of the low observability and high clutter. The method can effectively reduce the impact between the adjacent objects.
Owner:UNIV OF ELECTRONICS SCI & TECH OF CHINA
Multi-target tracking method based on variational Bayesian label multi-Bernoulli superposition model
ActiveCN110503071ARealize multi-target trackingImprove computing efficiencyDigital technique networkCharacter and pattern recognitionInformation processingPattern recognition
The invention belongs to the technical field of intelligent information processing, and relates to a multi-target tracking method based on a variational Bayesian label multi-Bernoulli superposition model. The noise covariance of the superposition model is estimated. On the basis of an original superposition model, the covariance of measurement noise is unknown, unknown parameters are estimated based on variational Bayes, the prediction and updating process of the superposition model marked with the multi-Bernoulli filter is achieved, state extraction is conducted, and therefore the tracking problem of the superposition model under unknown measurement noise is solved. The method has the characteristics of wide application range, strong robustness, high estimation precision and the like, caneffectively solve the problem of non-cooperation in an actual superposition model scene, realizes multi-target tracking and parameter estimation in a complex scene, can meet design requirements, andhas a good engineering application value.
Owner:UNIV OF ELECTRONICS SCI & TECH OF CHINA
Kernel correlation filtering multi-target tracking method fusing motion information
ActiveCN111292355AReduce pollutionHigh precisionImage enhancementImage analysisPattern recognitionVideo monitoring
The invention discloses a kernel correlation filtering multi-target tracking method fusing motion information, and belongs to the field of computer vision and intelligent information processing. On the basis of detection and tracking, the KCF is introduced to track multiple targets, excessive dependence on a detector is reduced, and accurate tracking of the multiple targets is achieved; in the tracking process, speed information and an SCCM mechanism are combined into a tracking framework, so that the problems of tracking of a shielded target and drifting of a tracking frame are solved; and finally, the false target is judged by adopting the IOU and the historical trajectory information, so that trajectory fragments are reduced. Experiments show that the method has good tracking effect androbustness, and can widely meet the actual design requirements of intelligent video monitoring, man-machine interaction, intelligent traffic control and other systems.
Owner:JIANGNAN UNIV
People tracking method based on intelligent video analysis
ActiveCN104637071ARealize multi-target trackingRealize continuous trackingImage enhancementImage analysisState parameterMulti target tracking
The invention discloses a people tracking method based on intelligent video analysis. The people tracking method comprises the following steps of analyzing the content of an image, and removing unusable background information; according to the sizes, moving speeds and moving rules of different moving targets, accurately identifying people, animals, vehicles or other objects, and extracting important information; comparing the moving rule of each moving target and a formulated safety rule, and verifying the moving safety of each moving target; under a complicated background, positioning and tracking each moving target in real time; predicting and filtering the state parameters of each target, such as mass center displacement, speed and acceleration; after each target is blocked by a small blocking object, continuing to track; after the target tracking is completed, automatically returning back to a current preset position. The people tracking method based on the intelligent video analysis has the advantages that the multi-target tracking is realized, the continuous tracking on each target with blocking time not exceeding three seconds is realized, and the accurate tracking before crossing and after separation of multiple targets is realized.
Owner:四川君逸数联科技有限公司
Multi-target tracking method and device based on video
InactiveCN102750550AEffectively handle multimodal problemsSmall amount of calculationCharacter and pattern recognitionMulti target trackingAdaBoost
The invention provides a multi-target tracking method and device based on video. The method comprises the following steps of: extracting a target module, initiating target parameters, detecting Adaboost, carrying out dynamic prediction on a particle set according to a motion model, updating a weight value of each mixing component, updating a motion state of each target, and updating the module. A multi-mode problem in multi-target tracking can be effectively solved, the effectiveness of calculation is maintained, the multi-target tracking can be realized, and simultaneously, the requirement of instantaneity can be ensured.
Owner:初红霞
Mask wearing condition monitoring system and method based on probabilistic neural network
ActiveCN111832400AReal-time monitoring of wearing masksImprove efficiencyBiometric pattern recognitionNeural architecturesPattern recognitionVideo monitoring
The invention relates to a mask wearing condition monitoring system and method based on a probabilistic neural network, and the system comprises: an input management module which is responsible for the reading and preprocessing of an input video; the target detection and segmentation module that is responsible for detecting and identifying each target in the video and segmenting the pedestrian mask part for detection; the multi-target tracking association module that performs many-to-many association on the detection result in each video in the video; the mask monitoring module that is used for carrying out low confidence coefficient and track discretization after completing preliminary track association; the output module that is arranged at a unified data center node, supports multi-pathcross-camera data output, performs multi-target tracking on each scene, and uniformly converges and outputs a calculation result; the system setting module that is used for configuring training of anetwork model used in the plurality of modules. Technical support is provided for the fields of video monitoring, behavior analysis and the like.
Owner:BEIHANG UNIV
Dynamic quantity sound source tracking method based on microphone array
ActiveCN105590021AReduce operation timeGuaranteed real-timePosition fixationSpecial data processing applicationsReal time trackingMulti targeting
The invention relates to a dynamic quantity sound source tracking method based on a microprocessor array. The method comprises the following steps: using a beam-forming algorithm to process a microphone array receiving signal and calculate a spatial spectrum; calculating the matching probability of spatial spectrum peaks and tracking sound sources so as to realize data association between the spatial spectrum peaks and the tracking sound sources; updating the particle weight of each tracking sound source and updating sound source positions according to the matching result; detecting the probability that the spectrum peaks are judged to be new sound sources, activating particle filters of the new sound sources and evaluating the possibility that the particle filters exist; monitoring the active states of the tracking sound sources and deleting non-active sound sources. By using the method, multi-target real-time tracking with a dynamic sound source quantity can be realized, and the method is widely applied in complex scenes such as human-machine interaction, teleconferences and virtual reality.
Owner:SHANGHAI JIAO TONG UNIV
Intelligent reconnaissance monitoring optoelectronic system
ActiveCN106878611AExpand the scope of surveillanceGuaranteed filling effectImage enhancementTelevision system detailsUser needsInter frame
Provided is an intelligent reconnaissance optoelectronic system which can download the pictures of the needed area according users' needs without increasing the communication bandwidth. The system has the advantages of intelligentization, networking, and digitlization, and a camera subsystem, a camera processing subsystem, a transmission subsystem, and a display processing subsystem. A user can transfer the information of the needed area or target through the display processing subsystem to the camera processing subsystem through the transmission subsystem, the camera processing subsystem cuts or tracks the user interested area or target by software, the camera processing subsystem automatically locks the tracking target by means of inter-frame differential detection. The system can download the needed information according to the user's needs, so that the difficulty that the reconnaissance monitoring cannot acquire the key information in real time due to the limitation of transmission bandwidth.
Owner:BEIJING RES INST OF SPATIAL MECHANICAL & ELECTRICAL TECH
Fish multi-target tracking method based on balanced joint network
PendingCN114202563AGood reasoning speedImprove balanceImage enhancementImage analysisData setMulti target tracking
The invention discloses a fish multi-target tracking method based on a balanced joint network, and belongs to the technical field of aquaculture. According to the method, on the basis of a Chinese agricultural artificial intelligence innovation and entrepreneurship contest data set, optimization, arrangement and supplementation are carried out on the basis of an original data set, and a new OptMFT data set is generated; the robustness of the model in a complex environment is further enhanced by performing merging training on a data set; meanwhile, some negative sample image frames with poor image quality are removed, the training weight of data with obvious fish targets and clear swimming tracks is enhanced, the fish recognition precision of the model is further improved, and full-frame training is performed on a data set to enhance robustness verification of the model under the condition of high-speed swimming of fish schools; the method is wide in application range, can achieve a good effect in multiple breeding environments, and is high in practicability.
Owner:CHINA AGRI UNIV
Target tracking method in multi-camera scene based on SIFT (Scale Invariant Feature Transform)
PendingCN113160283ARealize multi-target trackingHigh precisionImage enhancementImage analysisScale-invariant feature transformData set
The invention discloses a target tracking method in a multi-camera scene based on SIFT, and the method comprises the steps: obtaining a target detection total data set which is formed by photographing pictures containing different types of detection targets; using the target detection total data set to train a target detector YOLO-V5s model; obtaining a target tracking re-identification data set, wherein the target tracking re-identification data set is formed by taking photos containing different types of tracking targets and extracting the part containing the tracking target in each photo; training a target appearance feature extraction network in a DeepSort algorithm by using the target tracking re-identification data set; and acquiring a video shot by splicing multiple cameras by using an SIFT algorithm, and tracking a tracking target in the video by using the trained YOLO-V5s model in combination with the trained DeepSort algorithm. According to the invention, a larger target detection range can be obtained, and the target tracking precision is improved.
Owner:HOHAI UNIV
Novel binocular vision multi-target tracking method and system
InactiveCN111612818ARealize multi-target trackingImprove automationImage enhancementInstruments for road network navigationComputer graphics (images)Multi target tracking
The invention belongs to the technical field of automatic driving multi-target tracking, and particularly relates to a novel binocular vision multi-target tracking method and system, and the method comprises the steps: obtaining an image through binocular vision; acquiring a moving target according to the image; constructing a vehicle motion space and a vehicle motion model; and tracking the moving target according to the vehicle motion space and the vehicle motion model through improved joint probability data association. According to the invention, multi-target tracking of the intelligent vehicle is realized, the automation and intelligence level of a driving system is greatly improved, the tracking precision and speed are improved, obvious deviation is not generated during vehicle tracking, and pedestrian tracking is not missed.
Owner:JIANGSU XINTONGDA ELECTRONICS SCI & TECHCO
Target tracking method in multi-camera scene
InactiveCN112927267AImprove re-identification accuracyRealize multi-target trackingImage enhancementImage analysisPattern recognitionData set
The invention discloses a target tracking method in a multi-camera scene, which realizes splicing of pictures of different cameras by combining YOLO-V4 with an improved DeepSort algorithm and an image splicing algorithm, and finally realizes multi-target tracking in a spliced video. In the aspect of data sets, a self-made intelligent trolley data set and a self-made vehicle re-identification data set containing an intelligent trolley are adopted. According to the vehicle re-identification method, multi-target tracking in a multi-camera scene is realized by constructing a rich data set, improving a model and splicing and fusing pictures, and the vehicle re-identification accuracy is well improved.
Owner:HOHAI UNIV
Multiple trace point-based human body action recognition method
ActiveCN101964047BRealize multi-target trackingSimple methodImage analysisCharacter and pattern recognitionHuman bodyPhysical medicine and rehabilitation
Owner:SHENZHEN TAISHAN SPORTS TECH CO LTD
Multi-target data association method based on photoelectric sensor
ActiveCN111693051ARealize multi-target trackingNavigational calculation instrumentsNear neighborMultiple target
The invention discloses a multi-target data association method based on a photoelectric sensor. The multi-target data association method comprises the following steps: judging angle measurement information according to the angle measurement information acquired by different sensors and judging whether the angle measurement information comes from the same target or not; obtaining three-dimensionalspace coordinate information of the target after judging that the three-dimensional space coordinate information comes from the same target; and updating the track of the target based on a nearest neighbor plot-track association algorithm of the weighted sum distance. According to the invention, multi-target tracking can be realized under the condition that only the measurement information of theazimuth angle and the pitch angle of the target can be obtained. The multi-target data association method based on the photoelectric sensor can be widely applied to the field of multi-target trackingand multi-sensor information processing.
Owner:SUN YAT SEN UNIV
Knowledge graph-driven power distribution network field operation video intelligent safety management and control method
ActiveCN112419091ARealize multi-target trackingImprove the safety management and control level of on-site operationsData processing applicationsCharacter and pattern recognitionPower gridIntelligent management
The invention discloses a power distribution network field operation video intelligent safety control method driven by a knowledge graph, and the method comprises the steps: firstly constructing a power operation safety control knowledge graph, and aims to decompose objects, flows, matters needing attention and other semantic information in an operation task, thereby enabling the operation to be more visual and visualized; establishing a basis for subsequent personnel information security matching, skill point action matching and dynamic evaluation; dividing a power grid operation site area and a video intelligent management and control category; finally, using a deep learning algorithm, monitoring videos of all areas of an operation site are combined, safety control is conducted on operators in the whole process in real time, original passive on-site operation manual supervision is changed into active intelligent automatic monitoring, support is provided for early warning of on-site operation safety risks, and therefore the risks of the on-site operators are reduced, and the safety of the operators is improved. Therefore, the method is of great significance to the improvement of the safety management and control level of the power distribution network on-site operation.
Owner:WUHAN UNIV
Acoustic wave multi-target tracking method based on multiple loudspeakers and multiple microphones
ActiveCN112327252ARealize multi-target trackingHigh precisionPosition fixationAcoustic wave reradiationAcoustic waveLoudspeaker
The invention belongs to the technical field of multi-target identification and tracking, and particularly discloses anacoustic wave multi-target tracking method based on multiple loudspeakers and multiple microphones. The method comprises the following steps: designing a class of self-correlation strong cross-correlation weak acoustic wave signals and sending the self-correlation strong cross-correlation weak acoustic wave signals through the loudspeakers; identifying the direct signal and the reflected signals from the plurality of targets, obtaining the arrival time of the direct signal andthe arrival time of the reflected signals, and calculating the propagation path length of the reflected signals by using the flight time of the reflected signals; and drawing ellipses by taking the corresponding microphones and loudspeakers as focuses and combining the propagation path lengths of the reflected signals from the targets, and determining the positions of the multiple targets by utilizing intersection points of the multiple ellipses. The method is not influenced by factors such as environment and equipment conditions, has good transportability, and makes up for the defects of anexisting target tracking scheme of the electronic equipment.
Owner:OCEAN UNIV OF CHINA
An Intelligent Vehicle Detection Method Based on Tracking Trajectory Analysis
ActiveCN109948582BGet rid of the barriers of manual monitoringDispatch in timeCharacter and pattern recognitionCorrelation filterEngineering
The invention discloses a vehicle retrograde intelligent detection method based on tracking trajectory analysis, which uses a primary classifier and a secondary classifier to detect target vehicles in video images, extract target vehicle areas, and assign kernels to target vehicles Correlation filter tracker, each target vehicle is matched with a kernel correlation filter tracker, using the kernel correlation filter tracker to obtain the tracking area of the target vehicle, and then according to the tracking area to obtain the growth direction of the target vehicle's trajectory, and compare it with the initial marked retrograde Directions are compared, if they are the same, the target vehicle is going retrograde; if they are different, the target vehicle is not going retrograde. The present invention realizes the real-time detection of vehicle retrograde through this method, and solves the problems existing in manual detection; at the same time, the reliability of vehicle detection and recognition is improved by using cascaded classifiers, and simultaneous tracking of multiple vehicle targets is realized.
Owner:HUNAN UNIV
An Intelligent Reconnaissance and Surveillance Photoelectric System
ActiveCN106878611BExpand the scope of surveillanceGuaranteed filling effectTelevision system detailsImage enhancementEngineeringCommunication bandwidth
Owner:BEIJING RES INST OF SPATIAL MECHANICAL & ELECTRICAL TECH
A Multi-target Data Association Method Based on Photoelectric Sensor
ActiveCN111693051BRealize multi-target trackingNavigational calculation instrumentsInformation processingMulti target tracking
Owner:SUN YAT SEN UNIV
Multi-object Tracking Method Fused with Salient Features and Block Templates
ActiveCN104091348BImprove the ability to adapt to scene lighting changesPrecise positioningImage analysisVideo monitoringMulti target tracking
Owner:南京雷斯克电子信息科技有限公司
A multi-target detection and tracking method under the condition of low observable and high clutter
InactiveCN106468771BEasy to detectRealize multi-target trackingRadio wave reradiation/reflectionAcoustic wave reradiationSonarSlide window
Owner:UNIV OF ELECTRONICS SCI & TECH OF CHINA
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