66results about How to "Improve tracking stability" patented technology

The invention discloses an echo fused target track association method based on track state estimation.The method comprises the steps of conducting polar coordinate sector partitioning, conducting track starting/updating, conducting track prepushing and associated sector calculation, and judging the state of the prepushed track in an associated sector according to a corrected target fusion threshold and setting the state of the track as non-fusion, pre-fusion or fusion.Different track association strategies are adopted for the three track states; track-trace point association is conducted on the non-fusion track with the conventional nearest neighbor method; track association is conducted on the pre-fusion track with the target feature information assisted nearest neighbor method; for the fusion track, within the fusion wave gate range, feature information is used as the main basis for track association after echo defusion, the fusion track and a track cluster are updated in real time, and the fusion track and the track cluster are deleted if the number of tracks in the track cluster is lower than 2.By the adoption of the method, the probability of mis-tracking or track losing after target fusion can be reduced, and tracking stability can be improved.

The invention discloses a self-adaptive cruise control method and device and an automatic driving vehicle. The self-adaptive cruise control method comprises the steps that current video information infront of a vehicle is collected; the transverse position of a front vehicle and a first relative speed relative to the vehicle are obtained according to the current video information; and a current position of the front vehicle is obtained according to the transverse position, the first relative speed, a longitudinal position obtained through a radar and a second relative speed relative to the vehicle, and the front vehicle is used as a following target vehicle of a self-adaptive cruise mode when the current vehicle speed of the current position and the front vehicle meets a preset followingcondition. According to the self-adaptive cruise control method, the transverse distance and transverse speed of the target vehicle are obtained according to the video information, so that the relative position of a front target and the vehicle advancing track is judged, rapid reaction is given to target vehicle cut-in/cut-out, the following stability of a self-adaptive cruise control system is improved, the reliability and safety of self-adaptive cruise are effectively ensured, and user experience is improved.

The invention provides an FLL and subcarrier ring united frequency discrimination tracking loop which comprises a carrier tracking loop, a subcarrier tracking loop and a spreading code tracking loop. The carrier tracking loop comprises a carrier numerically-controlled oscillator, a mutual correlation processing unit, integral zero clearing units, a carrier loop frequency discriminator and an FLL loop filter. The subcarrier tracking loop comprises a subcarrier numerically-controlled oscillator, a mutual correlation processing unit, integral zero clearing units, a subcarrier loop phase discriminator and an SLL loop filter. The spreading code tracking loop comprises a numerically-controlled oscillator, a mutual correlation processing unit, integral zero clearing units, a code loop phase discriminator and a DLL loop filter. According to the structural characteristics of BOC signals, the FLL and subcarrier ring united frequency discrimination tracking loop can achieve independent tracking of the carrier frequency, the subcarrier phase and the spreading code phase, the tracking stability performance of weak signals is improved, the dynamic range of the loop is increased, and the problem of tracking ambiguity of the BOC signals under the low signal to noise ratio can be effectively solved.

The invention provides a particle swarm optimization based multi-cell position and outline synchronous accurate tracking system which comprises three main modules including a PSO based tracking module, a PSO based discovery module and a PSO based outline module. For existing-cell tracking, the PSO based tracking module obtains an initial state of a cell in a current frame on the basis of an existing-cell prior state, then calculates a cell outline through the PSO based outline module and meanwhile achieves accurate tracking by utilizing the iterative mass center updating process. For newly-emerging cell tracking, the PSO based discovery module discovers the position of a new cell in a whole image through appropriate particle swarm initialization and searching mechanism and further obtains the cell outline.

The invention relates to an object multi-mode tracking method based on a phased array system radar, wherein the method is mainly used for object tracking of a radar system. According to the method of the invention, a characteristic that a tracking task wave beam parameter of the phased array system radar can be compiled is utilized; a plurality of typical object tracking modes is arranged; and a matched mode is adaptively selected for tracking according to object tracking quality, object echo strength, object motility, clutter condition around the object and interference condition in the tracking process. The object multi-mode tracking method can improve object tracking stability and save radar resource. The object multi-mode tracking method has wide application prospect in a radar object tracking field.

The invention discloses a radar target tracking method based on environment situation analysis. The method comprises processing processes of polar coordinate sector division, sector drive tracking, target environment situation analysis, target matching association, target cleaning and target navigation establishment. A polar coordinate system is divided into sectoral regions of equal distance andorientation. When radar video data cross a predetermined orientation, a tracking module is driven to process the radar target data of a corresponding sector. Firstly, the environment situation analysis of a radar target is carried out, radar target environment situations are classified into three categories, namely, a security state, an early warning state and a fusion state, and then different tracking processing strategies are selected according to different environment situations of the radar target. Secondly, a target that meets a deletion criterion is deleted, and finally, points that arenot associated with the target are subjected to navigation establishment processing. The invention provides a target tracking processing strategy which has a certain effect on reducing false trackingand improving system tracking stability.

The invention generally relates to a system for generating and transmitting a telemetry formatted message containing raw Global Positioning System (GPS) information, processed Inertial Measurement Unit (IMU) information corresponding to the position and attitude of a high speed vehicle in motion. This telemetry formatted message is received on the ground and used to improve Kalman filter operation. In particular, the telemetry formatted message is used as an input to a ground based Kalman filter that is set to track and predict the trajectory of the high speed vehicle. The telemetry formatted message content improves the overall operation of the Kalman filter by preventing Kalman filter resets that occur when a bit error is encountered in the IMU data and improves the time correlation of high data rate IMU information and low data rate GPS information, both necessary for accurate tracking of the high speed vehicle.

The invention discloses an ant colony neighbor cell tracking system based on a cooperation and competition mode and application thereof. The system includes an initial ant colony distribution and rough classification module, a multi-ant-colony decision module and a fusion and deletion module. The initial ant colony distribution and rough classification module uses an approximate median method to extract a foreground image of cells so as to obtain initial ant colony distribution and then uses a K-mean-value clustering method to roughly divides the ant colony into N groups of sub-ant colonies. The multi-ant-colony decision module constructs a cell position estimation module, which is under the common action of N independent sub-pheromone fields and total pheromone fields, on the cooperation and competition mode. The fusion and deletion module performs multi-cell position estimation based on pheromone field construction through combination of similar sub-ant-colonies and removal of false targets caused by clutter and uses a nearest neighbor method which is easy to realize to perform cell correlation and obtain cell motion trails and kinetic parameters. The ant colony neighbor cell tracking system based on the cooperation and competition mode is capable of realizing neighbor multi-cell kinetic parameter estimation under a low-contrast-ratio cell image sequence, that is, under conditions that neighbor multi-cell kinetic characteristics are different, cells are deformed and time variance happens in cell number and the like, on the basis that no cell detection module or large quantity of cell training samples are needed, through cooperation and competition of an ant cluster system, problems of neighbor multi-cell multi-parameter estimation and tracking are solved.

The invention relates to a collaborative control and target tracking method based on mobile multi-agent formation. The research that a moving object is tracked in a formation mode by using multi-agentcontrol at present lacks. According to the collaborative control and target tracking method, a target motion state is estimated and calculated by using a Kalman algorithm, and thus an estimated trajectory of target motion is obtained; then a consistency algorithm is adopted, and a multi-agent system is controlled to form the formation; and finally, the target estimated trajectory is tracked through a sensor control method. According to the collaborative control and target tracking method based on the mobile multi-agent formation, a Kalman filter under a gaussian noise environment is selectedto estimate target motion, processes of sensor controlling and target tracking are experimented through a consistency theory, combination of a sensor controlling problem and a target tracking problemis deepened in a traditional algorithm, and tracking stability is greatly improved.

An objective optical system includes a diffractive optical element on the light source side of an objective lens for focusing incident light of three different wavelengths with two different numerical apertures onto three different optical recording media. The diffractive optical element is formed of two lens elements made of different materials that are cemented together at a diffractive surface. Three conditions are satisfied so as to achieve optimum imaging. The diffractive surface may be shaped so that the order of the diffracted light of the shortest wavelength λ2 having the largest diffracted intensity is different from the order of the diffracted light of the second wavelength λ2 having the largest diffracted intensity, and the order of the diffracted light of the first wavelength λ1 having the largest diffracted intensity is also different from the order of the diffracted light of the third wavelength λ3 having the largest diffracted intensity.

The invention discloses an adaptive vector tracking method for a GPS Receiver. The method includes the following steps that: vector tracking loop initialization is carried out, wherein the vector tracking loop initialization includes the initial position, velocity, clock difference, clock drift and satellite ephemeris of the receiver; carrier and code NCO prediction parameters are calculated according to the position, velocity, clock difference, clock drift and satellite ephemeris estimated by using a navigation filter; the navigation filter carries out adaptive processing, wherein the adaptive processing includes the calculation of a scale factor calculation and a fuzzy controller, wherein the scale factor is used for judging an error channel, and the fuzzy controller outputs the measurement variance adjustment parameter of the corresponding channel with the ratio of a an innovation sequence variance to a measurement noise variance adopted as the input of the fuzzy controller; and the output of a carrier frequency discriminator and a code loop discriminator is adopted as the measurement information of the navigation filter, the measurement information is used for estimating the position, velocity, clock difference, clock drift and satellite ephemeris of the receiver, and the estimated information is used for correcting the position and velocity of the receiver, and the carrier and code NCO prediction parameters are calculated based on the satellite ephemeris, and therefore, stable tracking of input signals can be kept. The adaptive vector tracking method has the advantages of high navigation precision and stable tracking performance.

The invention provides a multicellular multi-parameter joint estimation and accurate tracking system based on an ant colony system, and belongs to the field of cell tracking, wherein parameters include positions, speed, outlines and the like. Initial position distribution of an ant colony is generated due to the fact that a corresponding local area gray level variance of each gray image is defined. Two information pixel fields which work in parallel and are mutually independent are built on the basis, wherein the pixel fields comprise a position field and an outline field. A bounded ant colony decision making system is respectively built on a cell position estimation module and a cell outline estimation module. Finally, important parameters such as positions, speed and outlines of cells are precisely estimated. Therefore, accurate tracking of multiple cells is achieved. By means of mutual cooperation of the bounded heuristic type ant colony systems, a cell detection module is needless, a large number of cell training samples are needless, and the joint estimation and tracking problems of multicellular kinetic parameters and multicellular outlines in a low-contrast cell image sequence are solved.

Present invention concerns a tie being the carrying element for rails in a railway track. The tie comprises means (1) for fastening the rails to the tie which in use is lying in a ballast bed of crushed stone at the formation plane of the line. At the underside (2) the tie is provided with a number of elevations (4), whose height (H) is 40-100% of Dmax of the crushed stone. Each elevation (4) protrudes across the tie, and constitutes a cogging towards the crushed stone, in the longitudinal direction of the tie.

The invention discloses a multi-bernoulli random stochastic finite ant colony multi-cell tracking method. Firstly, a multi-bernoulli stochastic finite ant colony is proposed, the existence probabilityof the stochastic finite ant colony and the corresponding probability density function are given, on the basis, a related tracking problem is divided into prediction and update stages, in the prediction stage, prediction of the pheromone field and a sub ant colony state from a previous frame to a next frame is realized, the existence probability and discrete probability density distribution of the multi-Bennuoli stochastic finite ant colony in the prediction stage are given, in the update stage, the pheromone field is updated through multi-Bennuoli stochastic finite sub ant colony decision making, the multi-cell status is extracted, and thereby precise multi-cell tracking is achieved.

The invention provides a multi-cell automatic tracking method based on a multi-Bernoullie filter with a label, which comprises a step of cell set initialization by the multi-Bernoullie filter with the label, a step of prediction by the multi-Bernoullie filter with the label and a step of updating by the multi-Bernoullie filter with the label. Cell set initialization adopts the k shortest path, a new cell set is generated according to the newly-appearing cell detection probability, weights and cell probability densities of the former-frame cell set and the newly-detected cell set are used, a predicted cell set in the current frame, the cell predicted probability density in the cell set and the cell set weight are acquired, the posterior probability density of the cells in the cell set and the weight of the cell set are calculated and updated through similarities, and cell tracking can be completed with no need of relevance.

The invention belongs to the missile circuit technology, and relates to the improvement of the missile preamplifier. It includes a missile-borne computer and a low-noise operational amplifier U2, and is characterized in that there is a digital analog switch U1 whose output terminal Out is connected to the inverting input terminal of the low-noise operational amplifier U2, and its positive power supply terminal Vdd and negative power supply The terminal Vss is respectively connected with the positive and negative power supplies, its address data input terminal Adr is connected with the corresponding output port of the bomb computer, its signal input terminal is respectively connected with one end of the input resistor, and the other end of the input resistor is connected with the signal input of the conversion circuit. terminal Vin connection. The invention cancels the capacitance in the feedback loop, greatly shortens the response time of gain switching, and improves the tracking stability of the missile.

The invention provides a multi-cell automatic tracking system based on the fireworks algorithm, which generates potential cells in the image sequence by sparks generated by the fireworks explosion, and then searches and matches the real cells in the image according to the appropriate fitness function and the fireworks search mechanism, Finally, the nearest neighbor association is used to complete the cell tracking. The firework algorithm tracking system provided by the present invention can accurately track multiple cells. For multiple unknown and changing cells, cells with different dynamic characteristics, and neighboring cells, it can achieve accurate tracking effects, high tracking stability, and low false alarm rate. , The missed detection rate is low.

An information processing device includes a learning image input unit configured to input a learning image, in which a tracked object is captured on different shooting conditions, together with the shooting conditions, a feature response calculation unit configured to calculate a response of one or more integrated features, with respect to the learning image while changing a parameter in accordance with the shooting conditions, a feature learning unit configured to recognize spatial distribution of the one or more integrated features in the learning image based on a calculation result of the response and evaluate a relationship between the shooting conditions and the parameter and a spatial relationship among the integrated features so as to learn a feature of the tracked object, and a feature storage unit configured to store a learning result of the feature.