A method of determining a reference direction for an angular measurement device, comprising: providing a rigid structure having an antenna for a global navigation satellite system (GNSS) fixed at a first point thereof; fixing the angular measurement device to a second point on the rigid structure, separated from the first point by at least 0.5 meters; while rotating the rigid structure so as to cause rotational movement of the antenna around the sensitive axis, acquiring velocity measurement data from the GNSS and angular velocity measurement data from the angular measurement device; and using the velocity measurement data and the angular velocity measurement data to determine a reference direction for the angular measurement device.

Methods and systems for relative inertial measurement may include a user device comprising an inertial measurement device and/or a camera. A second inertial measurement device may be configured to move with a reference frame. One or more processors may receive inertial measurements from the first and second inertial measurement devices and determine movement of the user device relative to the reference frame by comparing the received inertial measurements. Additionally reference objects in a view of a camera may be used to calibrate the determined motion of the user device within the reference frame.

A movable structure includes: a moving part pivoting about a predetermined axis; a sensor module provided at the moving part or at a site interlocked with the moving part; and a control device controlling the moving part and the sensor module. The control device controls the moving part in such a way that the sensor module takes a first attitude, and gives a calibration instruction to the sensor module. The sensor module includes: an inertial sensor; a calibration unit calculating an attitude of the sensor module based on an output signal from the inertial sensor in response to the calibration instruction and generating correction information based on a difference between the calculated attitude and the first attitude; and a correction unit correcting the output signal from the inertial sensor, based on the correction information.

Among other things, a user interface device has a sensor configured to detect, at a wrist of a human, nerve or other tissue electrical signals associated with an intended contraction of a muscle to cause a rapid motion of a finger. An output provides information representative of the nerve or other tissue electrical signals associated with the intended contraction of the muscle to an interpreter of the information.

A sensor data processing system for an autonomous vehicle receives inertial measurement unit (IMU) data from one or more IMUs of the autonomous vehicle. Based at least in part on the IMU data, the system identifies an IMU data offset from a deficient IMU of the one or more IMUs, and generates an offset compensation transform to compensate for the IMU data offset from the deficient IMU. The system dynamically executes the offset compensation transform on the IMU data from the deficient IMU to dynamically compensate for the IMU data offset.

The present invention relates to a road vehicle localisation method based on magnetic landmarks. Said method is comprised by an offline phase and by an online phase. The offline phase is responsible for creating a reference landmark database comprised by a plurality of magnetic landmarks, wherein each magnetic landmark is associated to a path location data. The online phase is projected to match a current anomaly detected with a reference anomaly of the reference landmark database, in order to estimate the location of a vehicle based on the path location data of the correspondent reference landmark.

It is also described a system comprised by a sensor unit, a storage unit and by a processing unit, which is specifically programmed to operate according the road vehicle localisation method developed.

A method for determining the position and orientation of a vehicle, this method including measuring, with a magnetometer, a raw-measurement vector; obtaining a reference vector encoding, in a terrestrial reference frame, the amplitude and the direction of the geomagnetic field, the components of the reference vector being obtained from a pre-recorded model of the geomagnetic field and not measured by the magnetometer; then only if the margin of error in an estimate of the orientation of the vehicle is below a predetermined threshold, updating the pre-recorded data from which scale and offset coefficients used for correcting the raw measurement from the magnetometer are obtained, this update being performed using the raw vector, the reference vector and the new estimate of the orientation of the vehicle.

A pedestrian adaptive zero-velocity update point selection method based on a neural network, including the following steps: S1, collecting inertial navigation data of different pedestrians in different motion modes; S2, preprocessing the inertial navigation data collected in the step S1, labeling the preprocessed data, and obtaining a training data set, a validation data set, and a test data set according to the preprocessed data and a label corresponding to the preprocessed data; S3, inputting the training data set to a convolutional neural network for training, obtaining a pedestrian adaptive zero-velocity update point selection model based on the convolutional neural network, and using the validation data set to validate the pedestrian adaptive zero-velocity update point selection model; and S4, inputting the test data set into the pedestrian adaptive zero-velocity update point selection model based on the convolutional neural network, and obtaining a selection result of pedestrian zero-velocity update points.

An inertia detection device includes one set of gyro sensors for detecting an angular velocity of a detection target object along a same direction, the gyro sensors arranged in a same physical quantity range, in which sensor movement is detectable as a same physical quantity. When an abnormality affecting an output signal of one of the gyro sensors is caused, based on an observation that a difference of magnitudes of the output signals from normal and abnormal gyro sensors is different from a difference of magnitudes of the output signals from two normal gyro sensors, such an abnormality of one of the gyro sensors is determinable by a comparison between the output signals, without using an estimated value thereof.

The disclosure discloses a latitude-free initial alignment method under a swaying base based on gradient descent optimization. Firstly, swaying base latitude-free alignment is regarded as a Wahba attitude determination problem to inhibit device noise interference, and an objective function is established based on a gravitational acceleration vector under an earth system; then an exact solution of the objective function is obtained through a gradient descent optimization method, and inertial system conversion quaternion estimation is achieved under the latitude-free condition; and finally, an attitude quaternion is determined by only using information of an accelerometer and a gyroscope of a strapdown attitude heading reference system, and therefore latitude-free initial alignment under the swaying base is achieved. The disclosure can solve the problem that initial alignment cannot be accomplished with unknown latitude under the swaying base, and thus the application range of the strapdown attitude heading reference system is ensured.