The invention relates to an inertial unit for being attached to a rotatable part of a vehicle, the rotatable part being coupled to a power equipment of the vehicle, the inertial unit including: at least one acceleration sensor and/or at least one magnetometer arranged to detect a tilting angle of the rotatable part, and/or at least one counter device arranged to detect rotations of the rotatable part, and at least one gyroscope arranged to detect directions at a rim level of the rotatable part for providing angular information for positioning.

A head-tracking system includes a georeferenced head tracker (GHT) configured to provide georeferenced head position data, and a platform-referenced head-tracker (PRHT) configured to provide platform-referenced head position data. A controller is coupled with the GHT and the PRHT, and configured to be coupled with an avionic system configured to provide georeferenced aircraft position data. The controller includes a processor configured to access the georeferenced head position data, compare a current drift error of the GHT with a predetermined error threshold. When the current drift error is below the threshold, the processor transmits a signal indicative of the georeferenced head position data being a current georeferenced head position data. When the current drift exceeds the threshold, the processor access the georeferenced aircraft position-data, generates update data based on the platform-referenced head position data and the georeferenced aircraft position data, and updates the GHT at a known instant in time.

A sensor module includes an X-axis angular velocity sensor device that outputs digital X-axis angular velocity data, a Y-axis angular velocity sensor device that outputs digital Y-axis angular velocity data, a Z-axis angular velocity sensor device that outputs digital Z-axis angular velocity data, an acceleration sensor device that outputs digital X-axis, Y-axis, and Z-axis acceleration data, a microcontroller, a first digital interface bus that electrically connects the X-axis angular velocity sensor device, the Y-axis angular velocity sensor device, and the Z-axis angular velocity sensor device to a first digital interface, and a second digital interface bus that electrically connects the acceleration sensor device to a second digital interface.

An inertial sensor device includes a first interface, a second sensor, a second interface, a host interface, and a processing circuit. The first interface is an interface for a first sensor configured to detect a first physical quantity in a first detection axis, a second physical quantity in a second detection axis, and a third physical quantity in a third detection axis. The second sensor is configured to detect the physical quantity in the third detection axis as a high-accuracy third physical quantity with a higher accuracy than the first sensor. The processing circuit is configured to output the first physical quantity and the second physical quantity to a host via the host interface, and output the high-accuracy third physical quantity instead of the third physical quantity to the host via the host interface.

Technologies for determining a user's location by a mobile computing device include detecting, based on sensed inertial characteristics of the mobile computing device, that a user of the mobile computing device has taken a physical step in a direction. The mobile computing device determines a directional heading of the mobile computing device in the direction and a variation of an orientation of the mobile computing device relative to a previous orientation of the mobile computing device at a previous physical step of the user based on the sensed inertial characteristics. The mobile computing device further applies a Kalman filter to determine a heading of the user based on the determined directional heading of the mobile computing device and the variation of the orientation and determines an estimated location of the user based on the user's determined heading, an estimated step length of the user, and a previous location of the user at the previous physical step.

A system and method for correcting bias and angle misalignment errors in the angle rate and acceleration outputs from a 6-DOF IMU mounted to a vehicle. The method includes providing velocity and estimation attitude data in an inertial frame from, for example, a GNSS/INS, and determining an ideal acceleration estimation and an ideal rate estimation in a vehicle frame using the velocity and attitude data. The method then determines the IMU bias error and misalignment error using the ideal acceleration and rate estimations and the angle rate and acceleration outputs in an IMU body frame from the IMU.

A method and system are provided for improved pedestrian dead reckoning. In an embodiment, the crab angle of a device, i.e., the angle by which the device direction of travel differs from the device orientation, is determined via the processing of measurements from a vector accelerometer. The measured acceleration vector is rotated so that one component is vertical, and the crab angle is then found by determining a horizontal direction having the greatest energy. Correlations between the two horizontal acceleration components and the vertical acceleration component may be computed to determine the user's gait, further improving dead reckoning, e.g., for improving indoor position resolution.

An inertial measurement system for a spinning projectile comprising: a first, roll gyro to be oriented substantially parallel to the spin axis of the projectile; a second gyro and a third gyro with axes arranged with respect to the roll gyro such that they define a three dimensional coordinate system; a controller, arranged to: compute a current projectile attitude from the outputs of the first, second and third gyros, the computed attitude comprising a roll angle, a pitch angle and a yaw angle; calculate a roll angle error based on the difference between the computed pitch and yaw angles and expected pitch and yaw angles; provide the roll angle error as an input to a Kalman filter that outputs a roll angle correction and a roll rate scale factor correction; and apply the calculated roll angle correction and roll rate scale factor correction to the output of the roll gyro; wherein the Kalman filter models roll angle error as a function of roll rate and one or more wind variables. The system provides improved calibration of the roll axis rate gyro scale factor, e.g. of an IMU fitted to a rolling projectile. A separate process (an Euler angle filter) is used to calculate an estimate of the roll angle error without the use of the Kalman filter and is then provided as an input to the Kalman filter which can then operate in a stable manner. The filter can be configured to estimate and correct for crosswind effects which would otherwise significantly degrade performance.

A declination of an object, an orientation of the object and/or a position of the object can be determined using a gyroscope. In this regard, the gyroscope can be mounted to the object. The gyroscope can be pivoted. An undetermined pivoting of the object about an axis with the gyroscope can be measured. A component of a rotation of Earth acting on the gyroscope can be determined using the undetermined pivoting and the pivoting angular velocity (w.sub.carousel). At least one parameter set can be determined. The pivoting angular velocity (w.sub.carousel) of the gyroscope about the swivel axis with a second sensor can be determined.

A method and a system for recognizing a two-dimensional (2D) movement track based on a smart watch is provided. The method comprises: acquiring accelerometer signal data and gyroscope signal data of the smart watch; estimating a tilt angle of the smart watch by using the accelerometer signal data and correcting the gyroscope signal data by using the tilt angle; and calculating angle value information of the smart watch by using the corrected gyroscope signal data and estimating a coordinate point. According to the present application, the movement track of the smart watch can be accurately estimated by using the accelerometer and the gyroscope built in the smart watch.