12 results about "Velocity vector" patented technology

The invention relates to the technical field of data processing, in particular to an ocean transmission barrier searching method and system and a storage medium, and the method comprises the steps: carrying out the derivation of an earth turning flow field in a target sea area to obtain a differential equation of displacement, and carrying out the time integration of the differential equation to obtain the Lagrange trajectories of all grid point fluid infinitesimal elements in the target sea area; according to a partial derivative relationship between the velocity vector and a flow function, constructing a Poisson equation in combination with a geostationary flow field, and solving to obtain flow function distribution of the target sea area in a target time period; in the target time period, performing time integration on the flow function value of each fluid infinitesimal element in the target area along the Lagrange trajectory of the fluid infinitesimal element, and averaging to obtain a Lagrange average flow function distribution field; determining an LASF isoline of which the maximum line flow function standard deviation is smaller than a standard deviation threshold in the target time period, and determining a transmission barrier based on a substance line coinciding with the LASF isoline; according to the invention, the accuracy and reliability of transmission barrier identification in a complex marine environment are improved.

The present invention relates to a method for implementing velocity feature fusion for a visual target and a millimeter-wave radar point cloud. The method comprises: within the same frame period, acquiring host vehicle state information, millimeter-wave radar point cloud data, and target information that is output by a visual detection network model; calculating an actual radial velocity of a point cloud to the ground on the basis of the host vehicle state information; associating the millimeter-wave radar point cloud data with a visual target; using height information and dynamic and static information of the visual target to perform secondary non-target point cloud screening on an initially selected point cloud cluster, so as to acquire a final associated point cloud cluster; performing preliminary verification on the currently acquired visual target, and determining whether a velocity vector of the target is accurate; and if the velocity vector is not accurate, on the basis of a training result obtained by the visual detection network model, determining the accuracy degrees of the current target velocity direction and magnitude, and using a target point cloud cluster to calculate a target velocity magnitude and an angular velocity magnitude, so as to implement fusion processing of velocity features.

A device and its use for measuring the instantaneous velocity vector of objects (1), (3) and (4) moving relative to each other are described, wherein the device is permanently installed on the object (1), referred to as the measuring platform, and, for example, road traffic moves along with the flow of traffic. By means of the presented device several measuring barriers (7) send beams orthogonal to the movement of the measuring platform (1), each beam being designed as a sequence of temporally separated electromagnetic pulses. If the beams of the measuring barrier (7) are reflected by the stationary objects in the environment (29), the electromagnetic pulses propagated back are registered in the detector part of the distance measuring sensors (6) of the device and the lateral distance (11) of the objects to the direction of movement x of the measuring platform (1) is calculated from the transit time of the pulses. The lateral measuring range, defined by the measuring barriers (7), is divided into sensitive distance ranges A (8) and disjoint, non-sensitive distance ranges A (9) by the selection of the areas to be monitored. If an object (3) passes through the sensitive distance area A (8) and a sequence of valid distance measurements is taken in A (8), the computer evaluates the presence of an object in A (8) as, for example, a motor vehicle, and the time of the beginning and end of the passage through A (8) is determined using the current system time of the computer. From the known distances {x i | i ∈ {1,n}} of the distance measuring sensors {S i | i={1,n}} (6) among themselves and parallel to the direction of movement of the measuring platform (1) and from the associated measuring times t j of passing and the associated distance y i (t j) the relative velocity vector of the passing object (3), e.g. a motor vehicle, is calculated. The speed of the measuring platform (1) in the direction of movement x is calculated from the ongoing distance data to the lateral environment (29). The absolute velocity of the object (3) in the x-direction is calculated as the sum of the speed of the measuring platform (1) itself and the x-component of the relative velocity vector of the object (3) to the measuring platform (1). Continuously measured rotation rates and accelerations of the measuring platform (1) using an inertial measurement unit enable support for the calculation and correction of the velocities as well as real-time quality control of the measurement data.

The estimation device (10) of the present application includes: a sensor section (11) that transmits and receives a sensor wave and detects positions and relative velocities of a plurality of reflection points on an object; a velocity vector calculation section (23) that calculates a velocity vector of an arbitrary reference point of the object; a reflection point distance calculation section (21) that calculates a distance from the reference point to a straight line having a reflection point direction as a slope; a rotational relative velocity calculation section (25) that calculates a rotational relative velocity of the reflection point by subtracting a relative velocity at the reflection point direction based on the velocity vector of the reference point from the relative velocity of the reflection point; and an angular velocity calculation section (27) that calculates an angular velocity of the object based on the reflection point distance and the rotational relative velocity calculated by the reflection point distance calculation section and the rotational relative velocity calculation section.

An estimating device (10) comprises: a sensor unit (11) that transmits and receives sensor waves to detect the positions and relative velocities of a plurality of reflection points on an object; a velocity vector calculating unit (23) that calculates a velocity vector at an arbitrarily defined reference point in the object; a reflection point distance calculating unit (21) that calculates the distance from the reference point to a straight line inclined in the direction of the azimuth of each reflection point; a relative rotational velocity calculating unit (25) that calculates the relative rotational velocity of each reflection point by subtracting the relative velocity in the reflection point azimuth direction due to the velocity vector of the reference point from the relative velocity of the reflection point; and an angular velocity calculating unit (27) that calculates the angular velocity of the object on the basis of the reflection point distances and the relative rotational velocities calculated by the reflection point distance calculating unit and the relative rotational velocity calculating unit.

One or more embodiments of the present disclosure relate to obtaining a first state estimate corresponding to an object, the first state estimate including a first velocity vector estimate corresponding to the object. The disclosure may further relate to receiving first sensor data corresponding to a first portion of the object. The embodiments may further include determining a first expected measurement corresponding to the first portion, the first expected measurement including a first expected range rate determined based at least on the first angle measurement and the first velocity vector estimate of the first state estimate. And, determining a second state estimate corresponding to the object, the second state estimate including a second velocity vector estimate corresponding to the object and determined based at least on the first range rate measurement and the first expected range rate.

The invention discloses a rapid analysis method for a collision risk of a space object, and relates to the technical field of collision analysis and application. The method comprises the following steps: S1, establishing an intersection coordinate system for describing a relative motion relation according to motion state parameters of two objects; s2, constructing a vector relation equation of time variation under the condition of linear motion by utilizing a relative position and velocity vector relation of the two objects during motion; and S3, calculating the collision risk of the two objects based on the minimum approaching distance and the approaching moment between the two objects. According to the invention, the efficiency and precision of collision analysis calculation can be improved.

The invention relates to the technical field of platelet concentration, in particular to a platelet concentration method and system based on gravity settling, and the method comprises the following steps: acquiring settling path unit parameters and acquiring speed difference values, screening staggered difference value points and judging acceleration trend, extracting decreasing curvature difference to determine boundaries, and determining a platelet concentration result. Adjusting the dip angle acquisition speed change rate to screen a fallback path, and calculating a vector to establish an extraction path to obtain secondary concentrated data. According to the invention, through extracting the settlement velocity difference and the acceleration change trend, identifying the layered boundary area, improving the positioning accuracy of the concentration boundary, inducing the dynamic response based on the inclination angle disturbance, screening the path unit with the prominent speed rising rate, and enhancing the perception capability and the layered definition of the boundary area. By means of velocity vector direction and center position calculation, a stable linear extraction path is constructed, efficient recovery and focusing extraction of trace platelets are achieved, platelet concentration precision, stability and reutilization efficiency are improved, and complex sample conditions are adapted.

A method of measuring a velocity vector of a target object is provided. The method includes: obtaining pieces of radar data obtained by detecting the target object; based on the pieces of radar data, extracting velocity vectors for respective points that correspond to the detected target object; and calculating the velocity vector of the target object based on the velocity vectors.

The present disclosure relates to a system (100) comprising a device (102) having a set of sensors (104) for sensing the first set of attributes. The device comprises a set of network elements for sensing a second set of attributes. A processor (116) is configured to extract the first set of attributes relating to the velocity vector, velocity magnitude, direction, distance, and position on the road of the objects. The processor is configured to extract the second set of attributes relating to location data and proximity data of the objects. The processor (116) is configured to fuse the first set of attributes and the second set of attributes to form an occupancy grid map of objects in real time to create a local dynamic map (LDM) of the observed area.

A method of measuring a velocity vector of a target object is provided. The method includes: obtaining pieces of radar data obtained by detecting the target object; based on the pieces of radar data, extracting velocity vectors for respective points that correspond to the detected target object; and calculating the velocity vector of the target object based on the velocity vectors.

A method (1000) for determining a position deviation of a first node the method comprising obtaining (1110) input data, at a first and second position. Said input data comprises, an estimated position of the first node (p1) and a first velocity vector (v1) of the first node, obtaining (1120) the exact position (p2*) of the second node; obtaining (1125) the emitted frequency (fe) of an acoustic signal a source; (1130) receiving the acoustic signal (S) and measuring the observed frequency; calculating (1140) a second velocity vector (v12) which defines the velocity of the first node in relation to the second node; and calculating (1150), the angle (α) between the first velocity vector and the second velocity vector; determining (1160) based on the angle, the first velocity vector, and the estimated position of the first node, a line of direction (L) indicating the direction from the estimated position of the first node towards an estimated position of the second node, and determining (1300) based on a first and second line of direction an intersection point defining the estimated position of the second node (p2); determining (1400) a deviation vector (Vd) corresponding to the difference between the estimated position of the second node and the exact position of the second node, and determining (1500) the position deviation of the first node which corresponds to the deviation vector. The disclosure further relates to a positioning system for determining a position deviation for a first node and an underwater vehicle.