An electronic timepiece includes a detection axis calibration unit configured to execute first calibration processing of calibrating an axial direction and second calibration processing of calibrating a direction along a third detection axis, the second calibrating processing being executed after first calibration processing, a mode setting unit configured to set a first measurement mode when second calibration processing is not completed after completion of the first calibration processing, and set a second measurement mode when the second calibration processing is completed, a first azimuth calculation unit configured to calculate an azimuth, based on detected values of a three-axis magnetic sensor in two axial directions, when the first measurement mode is set, and a second azimuth calculation unit configured to calculate an azimuth, based on detected values of the three-axis magnetic sensor in three axial directions and a detected value of a inclination sensor, when the second measurement mode is set.

An electronic timepiece includes a detection axis calibration unit configured to execute first calibration processing of calibrating an axial direction and second calibration processing of calibrating a direction along a third detection axis, the second calibrating processing being executed after first calibration processing, a mode setting unit configured to set a first measurement mode when second calibration processing is not completed after completion of the first calibration processing, and set a second measurement mode when the second calibration processing is completed, a first azimuth calculation unit configured to calculate an azimuth, based on detected values of a three-axis magnetic sensor in two axial directions, when the first measurement mode is set, and a second azimuth calculation unit configured to calculate an azimuth, based on detected values of the three-axis magnetic sensor in three axial directions and a detected value of a inclination sensor, when the second measurement mode is set.

Disclosed are a device, computer program and method, for determining a range to a target, the device comprising a global positioning system (GPS) receiver, a pressure sensor, a temperature sensor, a controller; wherein the method comprises determining the device's geographic location based on coordinates from the GPS receiver and the device's elevation based on pressure and temperature data from the sensors; obtaining a location and elevation of a landmark based on GPS coordinates from a database; determining a distance between the device and the landmark using GPS coordinates; applying a slope compensation based on the difference in elevation between the device's elevation and the landmark; and converting the distance to a signal perceptible to a user.

An example operation includes one or more of determining a sensor on a transport is not functioning properly, determining a severity of the malfunction, responsive to the severity exceeding a threshold, lowering an autonomous level of the transport, and responsive to the severity continuing to exceed the threshold, limiting an operation of the transport based on an intended output of the malfunctioning sensor.

An example operation includes one or more of determining a sensor on a transport is not functioning properly, determining a severity of the malfunction, responsive to the severity exceeding a threshold, lowering an autonomous level of the transport, and responsive to the severity continuing to exceed the threshold, limiting an operation of the transport based on an intended output of the malfunctioning sensor.

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.

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.

The present invention relates to a method and an apparatus for detecting a failure of a sensor device during operation of the sensor device. A test signal is generated in a first frequency band that is above a signal frequency band of the sensor device and fed into a sensor element of the sensor device. A set of samples is obtained, and a magnitude value is derived from said at least two consecutive samples at the first frequency band. The magnitude value is compared to a magnitude threshold value that defines a minimum for the magnitude value and if the magnitude value is below the magnitude threshold value, it is determined that an error has occurred in the sensor device.

A method for calibrating a magnetometer. The magnetometer travels through (Si) a set of path positions, and acquires (S2) a plurality of measurements of the magnetic field. Trajectory information (S3) is provided representative of the location and the orientation of a point integral with the magnetometer. The measurements of the magnetic field are matched up (S4) with the trajectory information. A determination (S5) is made of calibration parameters of the magnetometer by the minimisation of a cost function involving, for a plurality of determination times, at least the calibration parameters, a measurement of the magnetic field, and a relationship linking the change in a magnetic field with the change in the location and in the orientation of the magnetometer derived from the trajectory information.

A method for calibrating a magnetometer. The magnetometer travels through (Si) a set of path positions, and acquires (S2) a plurality of measurements of the magnetic field. Trajectory information (S3) is provided representative of the location and the orientation of a point integral with the magnetometer. The measurements of the magnetic field are matched up (S4) with the trajectory information. A determination (S5) is made of calibration parameters of the magnetometer by the minimisation of a cost function involving, for a plurality of determination times, at least the calibration parameters, a measurement of the magnetic field, and a relationship linking the change in a magnetic field with the change in the location and in the orientation of the magnetometer derived from the trajectory information.