The present disclosure provides a method for vehicle speed estimation using multiple geomagnetic sensors, and mainly solves the problem of low accuracy of vehicle speed estimation in existing single-geomagnetic, dual-geomagnetic and multi-geomagnetic scenarios. There are M vehicle detection modules (1), and the vehicle detection modules are deployed along a roadside at equal intervals and configured to detect processes that a vehicle approaches and leaves a detection point, record the time when the vehicle approaches the detection point and send time data to a data processing module (2). In order to avoid the situation that the vehicle detection modules do not detect the vehicle and may not perform, vehicle speed estimation, the data processing module (2) performs matching of data association on the time data uploaded by all the vehicle detection modules by using standard deviations of vehicle position estimation and speed estimation, and performs multiple Kalman filter iterations on the matched time data and the positions of the vehicle detection modules, so as to obtain a precise vehicle speed. The present disclosure improves the accuracy of vehicle speed estimation, and may be used for intelligent transportation management.

An eddy current (EC) detection system comprises an EC probe including a plurality of sensors to provide corresponding EC response signals; and processing circuitry to evaluate speed of the EC probe based on a measurement of similarity of the EC response signals; determine whether the speed of the EC probe is too fast or two slow based on quality of the measurement; and generate a command to adjust speed of the EC probe during further EC inspection.

An embodiment apparatus for correcting an indicated speed tolerance includes a global positioning system (GPS) receiver, a processor, a memory coupled to the processor and storing instructions that, when executed by the processor, cause the processor to calculate an indicated speed by using a tolerance value for each vehicle speed section of a plurality of vehicle speed sections based on a wheel speed, and to correct an error between the indicated speed and a vehicle speed by using an actual speed of a vehicle based on GPS information received from the GPS receiver, and a display device configured to display the indicated speed.

An embodiment apparatus for correcting an indicated speed tolerance includes a global positioning system (GPS) receiver, a processor, a memory coupled to the processor and storing instructions that, when executed by the processor, cause the processor to calculate an indicated speed by using a tolerance value for each vehicle speed section of a plurality of vehicle speed sections based on a wheel speed, and to correct an error between the indicated speed and a vehicle speed by using an actual speed of a vehicle based on GPS information received from the GPS receiver, and a display device configured to display the indicated speed.

A method for identifying a longitudinal jerking of a motor vehicle is provided, wherein a wheel speed of a driven wheel and a wheel speed of a non-driven wheel are recorded and wherein the longitudinal jerking of the motor vehicle is detected on the basis of a change in the measured wheel speeds. The detection of the longitudinal jerking is improved by comparing the change in the wheel speed of the driven wheel with the change in the wheel speed of the non-driven wheel in order to detect a longitudinal jerking as a result of a vibration stimulation in the drive train.

A method for identifying a longitudinal jerking of a motor vehicle is provided, wherein a wheel speed of a driven wheel and a wheel speed of a non-driven wheel are recorded and wherein the longitudinal jerking of the motor vehicle is detected on the basis of a change in the measured wheel speeds. The detection of the longitudinal jerking is improved by comparing the change in the wheel speed of the driven wheel with the change in the wheel speed of the non-driven wheel in order to detect a longitudinal jerking as a result of a vibration stimulation in the drive train.

Systems and methods for determining a velocity of a fluid or an object are described. Systems and methods include receiving image data of the fluid or the object, the image data comprising a plurality of frames. Each frame comprises an array of pixel values. Systems and methods include creating a frame difference by subtracting an array of pixel values for a first frame of the image data from an array of pixel values for a second frame of the image data. Systems and methods include measuring a difference between a location of the object in the first frame of the image data and the second frame of the image data. Systems and methods include creating a correlation matrix based on the measured difference. Systems and methods include using the frame difference and the correlation matrix to automatically determine the velocity of the fluid or the object.

Embodiments of the present disclosure provide a method and apparatus for determining a velocity of an obstacle, a device, and a medium. An implementation includes: acquiring a first point cloud data of the obstacle at a first time and a second point cloud data of the obstacle at a second time; registering the first point cloud data and the second point cloud data by moving the first point cloud data or the second point cloud data; and determining a moving velocity of the obstacle based on a distance between two data points in a registered data point pair.

A method for calculating a scale factor for a gyroscope can include detecting, by a gyroscope, a physical motion of a robot, detecting, by an optical flow (OF) sensor (and/or camera), one or more image signals including information; and deriving estimates of sensor calibration parameters based on the detected physical motion and the information.

Systems and methods for determining a velocity of a fluid or an object are described. Systems and methods include receiving image data of the fluid or the object, the image data comprising a plurality of frames. Each frame comprises an array of pixel values. Systems and methods include creating a frame difference by subtracting an array of pixel values for a first frame of the image data from an array of pixel values for a second frame of the image data. Systems and methods include measuring a difference between a location of the object in the first frame of the image data and the second frame of the image data. Systems and methods include creating a correlation matrix based on the measured difference. Systems and methods include using the frame difference and the correlation matrix to automatically determine the velocity of the fluid or the object.