58results about How to "Reduce tracking time" patented technology

A clock generator and a data recovery circuit. The clock generator includes a voltage control oscillator (VCO) for generating a sampling clock and multi-phase clocks, a multiplexer for receiving the multi-phase clocks and selecting one of the multi-phase clocks to generate a selected clock according to a selection signal, a phase-frequency detector for receiving the selected clock and a reference clock and generating a phase-frequency error signal, a charge pump and loop filter for receiving the phase-frequency error signal and generating a control voltage, a phase detector for receiving the sampling clock and an input signal and generating a phase error signal, and a digital low-pass filter for receiving the phase error signal and generating the selection signal. The digital low-pass filter clears an accumulated phase error when it generates the selection signal to force the multiplexer to change the phase.

A mobile radio communication system which does not need an omnidirectional channel for both a base station and a mobile station to track each other and uses only a narrow beam channel and can reduce a tracking time than before for an adjacent base station and a mobile station to search each other while a visiting area base station and the mobile station are communicating in the overlapped area. The base station and the mobile station comprise a unit for transmitting and receiving in forward or reverse channel, in different frequency, in different tracking channel using a narrow beam. Both the mobile station and the visiting area base station search the location each other, and after searched, they assign the frequency and the beam used in the tracking channel. At the same time, by comprising a searching slot in an information channel to search an adjacent base station while communicating with the visiting area base station, a tracking of other adjacent base station can be performed.

A motion simulator includes a stationary frame, a movable frame pivotally connected with the stationary frame, an operating chamber formed at a lower side of one end of the movable frame, a first actuator for pivoting the movable frame, and a second actuator arranged between the operating chamber and the movable frame, for rotating the operating chamber in forward and backward directions with respect to the movable frame.

The invention discloses a loitering detecting method in video monitoring, comprising the steps of: carrying out position-based matching pursuit on targets appearing in a video monitoring area, recording presence time or appearance times of the pursued targets, and taking the targets with the presence time or appearance times longer or more than a corresponding first set threshold as candidate loitering targets; carrying out histogram-based matching pursuit on the candidate loitering targets, recording presence time or appearance times of the pursued candidate loitering targets, and taking the target with the presence time or appearance times longer or more than a corresponding second set threshold as a loitering target. In addition, the invention also discloses a loitering detecting system in the video monitoring. The technical proposal disclosed by the invention can improve the accuracy of a detection result.

The invention discloses an adaptive ORB object tracking method. The adaptive ORB object tracking method adds FAST characteristic direction information in order to solve the problem that the FAST characteristic has no direction; a BRIEF characteristic descriptor based on pixel point binary digit comparison is adopted in a characteristic point description portion; the defects that the BRIEF descriptor is sensitive to the image noise and has no rotation invariance are improved; and compared with an SIFT algorithm, the ORB algorithm has the rotation invariance and noise resistance, and the operation speed of the ORB algorithm is higher than that of the SIFT algorithm by two orders of magnitude. The adaptive ORB object tracking method fully utilizes the characteristic of the ORB algorithm, performs further improvement on the PRB algorithm, brings forward the ORB algorithm on the basis of that the improvement, further improves the operation speed and the tracking accuracy, and better meets the demand for the real-time tracking.

This invention is a kind of clock generating circuit and related data restore circuit. The clock generating circuit concludes a voltage controlled oscillator which generates a sampling signal and multiphase clock; a multiplexer which receives multiphase clock and outputs a clock of the multiphase clock based on a selecting signal; a phase frequency detector which receives the output signal of multiplexer and a referenced clock. It also generates a phase frequency error signal; a charge pumping and loop filter, which receives the phase frequency error signal and generates a controlling voltage; a phase detector which receives the sampling signal and input signal. It also generates a phase error signal; a digital low-pass filter which receives the phase err[r signal and generates the selecting signal; the digital low-pass filter clears off the phase accumulative error when generating the selecting signal to instruct the multiplexer to switch phase.

The invention discloses a target tracking device combined with a multi-view camera and a multi-view target tracking method. The target tracking device comprises a video capturing unit and a video processing unit, wherein the video capturing unit is used for capturing video information of multiple original visual angles; the video processing unit is improved based on a TLD tracking algorithm so that the purpose of multi-view target tracking is achieved starting from a detection module and a learning module of the algorithm. For the detection module, if a total graph is scanned, much time is consumed. A movement of a target between two frames is a small movement, so that a detection region is shortened into a small region, namely, ROI, around the last-frame target box, and thus the tracking time is greatly shortened. The target tracking device further comprises a multi-view information fusion unit, wherein the multi-view information fusion unit fuses multi-view information, and thus the robustness of the tracking of the detection module is enhanced by using a learning mechanism, so that the tracking performance is improved. According to the target tracking device, by fusing multi-view target information, the target tracking performance is improved.

The invention relates to a vehicle-mounted solar charger for an electric vehicle. The electric vehicle comprises a solar battery and a vehicle-mounted power battery. The vehicle-mounted solar charger comprises a charging system, a control system, a power module, a solar battery temperature detection module, a voltage sampling module, and a current sampling module. The charging system comprises an input protection module, an input filter module, a boost conversion module, an output filter module, and an output protection module, all of which are sequentially connected in series. The control system is connected with the charging system. The control system comprises a microcontroller module, a TL494 control module, and a drive module. The power module comprises a first power module and a second power module. The solar battery temperature detection module is connected with the solar battery and the microcontroller module. The beneficial effect is that the vehicle-mounted solar charger for an electric vehicle with the advantages of high tracking response speed, large range of output voltage and stable performance is provided.

The invention discloses a GPS software receiver baseband signal real-time tracking method based on code memory, wherein the method is based on prestored and fine-adjusted local C / A code to perform binary system storage and performs table lookup and invocation to solve the problem that real-time code which wastes time are generated in GPS software receiver tracking signal time. In GPS software receiver tracking loop, the process that local C / A code is generated through minute adjustment is longest in the three longest processes, namely generation of fine-adjusted local C / A code, generation of local carrier wave and related integration and the time for generating fine-adjusted local C / A code is nearly half of the entire signal tracking and processing time. The invention uses the binary data of prestored and fine-adjusted local C / A code and directly loads data to perform table lookup and call data so that the fine-adjusted early code and late code can not be generated in every tracking cycle, the time wasted by real-time code can be saved, the time for the generation of codes in tracking cycle is saved and the tracking speed doubles.

The invention relates to a finite-time neural network control method of a motor-driven single-connection rod manipulator. The method comprises steps of (1) establishing a mathematical model of the motor-driven single-connection rod manipulator and an actuator nonlinear module with a dead zone and input saturation limitations; (2) determining a control target, wherein system output is capable of tracking reference output of the system within the infinite time, and the system output is kept in a limited range; (3) designing an infinite time neural network control law and achieving a control target; and (4) designing a barrier Lyapunov candidate function and analyzing stability of a closed loop system, and according to the stability analysis of the Lyapunov candidate function, determining control parameters of the designed control law. According to the invention, by considering limitation factors of input saturation limitations, the dead zone, output limitations and system indeterminancy,the control method can be well applied in an actual system. In addition, infinite-time track tracking can be achieved; tracking time is reduced; and robustness and control precision of the system areimproved.

The invention relates to a video target tracking method based on compressive sensing. The video target tracking method comprises the steps of firstly, generating a sparse projection matrix according to the compressive sensing theory and performing sparse projection dimensionality reduction on positive and negative samples obtained by sampling to create a Bayes classifier, and when next frame of frame comes, performing sampling around the obtained target position of a prior frame, obtaining the most possible target position by classifying by use of the classifier, updating the target position and updating the parameters of the classifier. The video target tracking method based on compressive sensing is capable of effectively overcoming the problem of unstable tracking caused by target characteristic change, and capable of effectively reducing the computation complexity and shortening the tracking time by compressing high-dimensional information into low-dimensional information according to the compressive sensing theory.

Disclosed is a technique for accurately tracking a tracking target object. A disparity map image in which the disparity of each pixel of an object is shown is generated from a three-dimensional object image. A detection range is determined such that an object disposed on the front side of a pedestrian, which is a tracking target object, in the depth direction is excluded from the generated disparity map image. The pedestrian, which is a tracking target object, is detected in the determined detection range. In this way, it is possible to prevent a bike driver disposed on the front side of the pedestrian in the depth direction from being tracked.

The invention relates to a bistatic MIMO (Multiple Input Multiple Output) radar tracking method based on chaotic multi-population symbiotic evolution. The bistatic MIMO radar tracking method comprises the steps of acquiring signal sampling data, and acquiring fractional low-order covariance; initializing a search interval; initializing the position and the speed of individuals by using a Sine chaotic reverse learning strategy, determining an optimal individual position of each population and the optimal individual position of the whole ecosystem according to a fitness value; updating the speed of individuals of each population in the ecosystem by using a Sine chaotic multi-population symbiotic evolution mechanism; judging whether all individuals in the ecosystem can search a better position or not after sigma times of iterations; judging whether a maximum number of iterations reaches or not; and updating a search interval of 2P angles. The bistatic MIMO radar tracking method not only can solve a problem of dynamic direction tracking of bistatic MIMO radar in a Gaussian noise environment, but also can solve a problem of dynamic direction tracking of the bistatic MIMO radar in an impact noise environment.

The invention discloses a vision-based density traffic vehicle counting and traffic flow calculation method and system. The vision-based density traffic vehicle counting and traffic flow calculation method comprises the steps of zooming an acquired continuous frame image to obtain a pyramid characteristic map, inputting the pyramid characteristic map to a trained pyramid-YOLO network to detect vehicle targets with different scales so as to obtain a boundary frame with the vehicle targets; presetting a line-crossing probability function, judging probability of each target vehicle passing through a counting line in an image with the vehicle targets, and sieving a traced vehicle according to a probability value; performing tracking track processing on the traced vehicle according to a limitation-based multi-target tracing algorithm, and counting the vehicles passing through the counting line according to an obtained track set; and calculating to obtain vehicle flow traffic volume, speed and density according to the obtained vehicle counting result. By the vision-based density traffic vehicle counting and traffic flow calculation method, the problem of a dense traffic scene is solved,a system on the basis of vehicle detection, tracing, counting and parameter estimation is proposed, vehicle detection is accurately and rapidly performed, the dense vehicle is accurately traced, and flow estimation is achieved.

The invention discloses a tracing method of a solar battery maximum power point. A part of curve which is nearby the maximum power point of a solar battery output characteristic power / voltage curve 1 is approximated to a parabola 2, a parabolic equation is solved by using three groups of power / voltage data 3, 4 and 5 on the part of the curve, and an extreme point 6 of the parabolic equation is the maximum power point 7 output by the solar battery.

The invention discloses a face tracking method and system based on deep learning, and the method comprises the steps: S1, obtaining a starting frame of a video stream as a current frame, and setting n= 0; s2, judging whether the current frame n of the video stream meets the condition that n% N is equal to 0 or not, if so, executing the step S3, and if not, executing the step S4, wherein N is a preset interval frame number; s3, performing face detection on the current frame, if a face is detected, outputting a face candidate box, and executing the step S4, otherwise, obtaining the next frame of the video stream as the current frame, setting n to be equal to 0, and executing the step S2; s4, performing face verification on the face candidate box, verifying whether the face candidate box contains a face or not, if so, outputting a face frame image, and executing the step S5, otherwise, obtaining a next frame of the video stream as a current frame, setting n to be equal to 0, and executing the step S2; s5, performing key point positioning on the face frame image, and calculating an external rectangular frame of a face key point; and S6, expanding the external rectangular frame to obtain an expanded rectangular frame, extracting a next frame of the video stream as a current frame, setting n = n + 1, setting the expanded rectangular frame as a face candidate frame, and executing thestep S2. The method is compatible with single-face and multi-face tracking, is not influenced by a scene environment, and is high in face tracking robustness and high in real-time performance.

The invention provides an efficient maximum power real-time tracking method for a photovoltaic power generation system, and particularly relates to a maximum power point real-time tracking control method based on a new ant colony algorithm and a variable step size type conductance increment method. The method comprises the following steps: 1) tracking near a maximum power point by using a novel ant colony algorithm based on an updating solution; selecting an optimal solution through the movement of ants, and recording a corresponding optimal voltage value and power; 2) determining whether themaximum distance between ant colonies is less than 0.02 Uoc as a threshold of algorithm iteration and determining whether to call a variable step size conductance increment method; and 3) carrying outperiodic test according to the relational expression shown in the description, judging whether the external environment is suddenly changed or not, if not, initializing algorithm parameters and carrying out search again, and otherwise, outputting the voltage Umax and the corresponding maximum power Pmax.

The invention provides a maximum power tracking control method and system for a photovoltaic array. The tracking control method comprises the following steps: firstly, determining a relationship between an output voltage and an output current of the photovoltaic array by utilizing a photovoltaic effect according to acquired actual light intensity and actual temperature; secondly, based on the relationship between the output voltage and the output current, tracking the maximum power point of the photovoltaic array by adopting an adaptive weight particle swarm algorithm; and finally, adjusting the transformation ratio of a DC-DC converter disposed between the photovoltaic array and the load according to the output voltage of the maximum power point, and enabling the photovoltaic array to work at the maximum power point. According to the method, the particle swarm algorithm with the self-adaptive weight is used for tracking the maximum power point of the photovoltaic array, the power loss caused by falling into local optimum in the tracking process is avoided, the tracking of the first peak power through the particle swarm algorithm in the initialization stage is not needed, and the tracking time of the maximum power point is shortened.

The invention relates to a fixed-time predetermined performance recurrent neural network mechanical arm control method. The method comprises the steps that (1) a mathematical model of a mechanical armdriven by a direct-current motor is established, and an actuator model with an unknown nonlinear dead zone is established; (2) system reference output is determined, and a performance function, whicha tracking error needs to meet, is designed; (3) a fixed-time predetermined performance recurrent neural network controller, a neural network weight update law and a fixed-time differentiator are designed so that system output can track a reference output trajectory in fixed time, and meanwhile the system tracking error is limited within a performance boundary range designated in advance; and (4)stability analysis is performed on a control system, and controller parameters are determined according to the stability analysis result. Through the method, fixed-time predetermined performance trajectory tracking can be realized, so that tracking time is shortened, control precision is improved, and transient performance and steady performance of the system in the control process are guaranteed.

The invention discloses a ray tracing method and system based on NURBS, and mainly solves the problems of low speed and low precision of an existing ray tracing method. The scheme is as follows: the method comprises the following steps of 1, representing a curved surface as a plurality of curved surface elements according to the curved surface node distance information; 2, excluding part of curvedsurface elements without an intersection by utilizing axis arrangement bounding boxes of the curved surface elements; 3, further excluding the curved surface elements without the intersection by utilizing a triangular surface element control network; 4, taking the intersections of the ray and the residual curved surface elements by utilizing an extreme value search iteration method; and 5, tracking the ray by utilizing a geometrical relationship and a Fresnel law to form recursion in order to trace a ray trajectory. According to the method and the system, more curved surface elements withoutthe intersection are excluded by the axis arrangement bounding boxes and the triangular surface element control network, so that the ray tracing time is shortened; the ray-curved surface intersectionis solved through the extreme value search iteration, so that the precision of the intersection is improved; and the method and the system can be used for rapidly and accurately computing the radar scattering cross section area of a surface curved target.

The invention relates to a photovoltaic multi-peak power point tracking method based on a territory particle swarm. The method comprises the following steps: 1) adjusting a duty ratio of a PWM as 0 toobtain output voltage of a Boost circuit; 2) setting the number of the particle swarm; 3) computing an adaptive value of each particle, re-judging and selecting a global optimal particle and the global optimal particle territory according to the obtained adaptive values; 4) determining a maximum value estimation range in the particle territory; 5) judging whether the condition that the maximum value estimation range contains the adaptive value of the global optimal particle is tenable; 6) judging whether the condition that the maximum distance dmax between the particles is less than 0.02Uocaris tenable; 7) computing each particle adaptive value, re-judging and selecting the global optimal particle; 8) judging whether the condition that the maximum distance dmax between the particles is less than 0.01Uocar is tenable; and 9) maintaining the output voltage as the voltage of the obtained global optimal particle location, and judging whether the environment changes suddenly.

The embodiment of the invention provides a position tracking method and a device applied to a portable station. Through a pre-tracking model, an antenna position is judged and a satellite theoretical position is solved; a coarse tracking module carries out tracking in a dot matrix mode for searching for sampling points whose satellite beacon level values are larger than a tracking threshold; and a fine tracking module carries out tracking in a cross dot matrix mode for searching for the maximal satellite beacon level point. By adopting the method and the device provided by the embodiment of the invention, an open loop control method is adopted, in comparison with a closed loop control method, elements such as a position feedback element and an encoder can be saved, the space of the portable device can be saved, and the weight of the portable device is reduced. As the elements in the portable station are reduced, reliability of the portable station is enhanced, maintenance is easy, and stability is high.

The invention provides a related object tracking method and device, electronic equipment and a non-transitory storage medium, and relates to the technical field of research and development management.The method comprises the steps of obtaining individual information of a related object; acquiring real-time monitoring video information of all monitoring devices in the specified geographic area atpreset time intervals; inputting the individual information as a first input and the real-time monitoring video information as a second input into a related object positioning model, and determining the real-time position of the related object at the current time node through the related object positioning model; acquiring a real-time position of a tracker; and calculating a tracking path from thetracking party to the involved object according to the real-time position of the tracking party and the real-time position of the involved object at the current time node. Through the technical scheme of the invention, the real-time position of the involved object can be cyclically updated, the tracking route can be conveniently and effectively adjusted, and the tracking efficiency and success rate are improved.

An attack path detection method, attack path detection system and non-transitory computer-readable medium are provided in this disclosure. The attack path detection method includes the following operations: establishing a connecting relationship among a plurality of hosts according to a host log set to generate a host association graph; labeling at least one host with an abnormal condition on the host association graph; calculating a risk value corresponding to each of the plurality of hosts; in a host without the abnormal condition, determining whether the risk value corresponding to the host without the abnormal condition is greater than a first threshold, and utilizing a host with the risk value greater than the first threshold as a high-risk host; and searching at least one host attach path from the high-risk host and the at least one host with the abnormal condition according to the connecting relationship of the host association graph.

A motion simulator includes a stationary frame, a movable frame pivotally connected with the stationary frame, an operating chamber formed at a lower side of one end of the movable frame, a first actuator for pivoting the movable frame, and a second actuator arranged between the operating chamber and the movable frame, for rotating the operating chamber in forward and backward directions with respect to the movable frame.

The invention discloses a control method and system for a direct-drive permanent magnet hydroelectric generation system on the basis of fuzzy control, a terminal and a readable storage medium. The control method aims at solving the problems that in the conventional maximum power tracking control process of a water turbine, the tracking speed is low, the steady-state precision is low, and the efficiency of the water turbine is reduced due to the fact that a large amount of energy is easily lost in the tracking process. A water turbine comprehensive characteristic curve is used for extracting power P, rotating speed n and flow Q data, BP (back propagation) neural network training is carried out on the power P, rotating speed n and flow Q data, and a neural network off-line model is obtained. According to the method, the neural network off-line model is used for evaluating the initial rotating speed, then the fuzzy control MPPT (maximum power point tracking) is used for tracking the maximum power, the combination of a neural network and a fuzzy controller is realized, in addition, the influence of the flow Q change is also considered, a new maximum power point is rapidly tracked, the power loss and the energy waste are reduced, and the efficiency of the water turbine is improved.

The invention discloses a maximum power point tracking device for an energy harvesting system. The maximum power point tracking device comprises an energy collection device, an inductor, a PMOS transistor MP, an NMOS transistor MN, a load capacitor C, a pulse generation circuit, a switch control unit, a time delay unit, a logic gate, a driving stage, a comparator, a Voc sampling module and an MPPoutput module. According to the device, the switch control and current conversion technology is adopted, and the effective maximum power sampling and tracking time is reduced. The fast boost converterbased on the current holding technology is adopted, large input capacitance can be avoided, and the energy loss in the sampling process can be reduced while the area is reduced. Compared with a traditional maximum power point tracking device, the maximum power point tracking device is simple in structure, the tracking time can be remarkably shortened, and the power conversion efficiency is improved.

The embodiment of the invention discloses a sight tracking method and device, equipment and a storage medium. The method comprises the following steps: acquiring an infrared thermal imaging eye pattern and user state information when a user watches; determining corresponding feature information based on the temperature value of each pixel point in the infrared thermal imaging eye pattern; acquiring pre-stored sight calibration data corresponding to user position information included in user state information; and determining gaze information based on the feature information and pre-stored gazecalibration data. By adopting the technical scheme, the technical problem of long sight line tracking time consumption caused by the fact that a user needs to gaze a plurality of calibration points in advance for sight line calibration during sight line tracking is solved, the sight line tracking time is shortened, the sight line tracking efficiency is improved, and meanwhile, the use experienceof the user is enhanced.

A mobile radio communication system which does not need an omnidirectional channel for both a base station and a mobile station to track each other and uses only a narrow beam channel and can reduce a tracking time than before for an adjacent base station and a mobile station to search each other while a visiting area base station and the mobile station are communicating in the overlapped area. The base station and the mobile station comprise a unit for transmitting and receiving in forward or reverse channel, in different frequency, in different tracking channel using a narrow beam. Both the mobile station and the visiting area base station search the location each other, and after searched, they assign the frequency and the beam used in the tracking channel. At the same time, by comprising a searching slot in an information channel to search an adjacent base station while communicating with the visiting area base station, a tracking of other adjacent base station can be performed.