An inertial measurement system (200) for a longitudinal projectile, comprising a first, roll gyro to be oriented substantially parallel to the longitudinal 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. The system further comprises a controller (225, 250), 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; —for at least two time points, to compare the computed pitch and yaw angles with expected values for the pitch and yaw angles; —for each of said at least two time points, to calculate a roll angle error based on the difference between the computed pitch and yaw angles and the expected pitch and yaw angles; —to calculate a roll angle error difference between said at least two time points; —to calculate the total roll angle subtended between said at least two time points; —to calculate a roll angle scale factor error based on said computed roll angle error difference and said total subtended roll angle and apply the calculated roll angle scale factor error to the output of the roll gyro.

The subject matter disclosed herein relates to a system and method for receiving a plurality of signals generated by a plurality of sensors adapted to detect physical movement of a mobile device with respect to a plurality of coordinate axes. A time at which at least one of the received signals is digitized is delayed to provide an output of digitized versions of the received plurality of signals synchronized with respect to a common point in time.

A position calculation device includes an acceleration sensor and a gyro sensor to detect a movement of the user which is mounted on the body of the user, an arithmetic processing unit which executes setting a traveling direction axis by using a detection result of the sensor, using a change in a traveling direction of the user and correcting the traveling direction axis, and calculating a position based on the detection result of the sensor by using predetermined constraint condition based on the traveling direction axis.

A hybrid approach for using reference frames is presented in which a series of anchor frames is used, effectively resetting a global frame upon a trigger event. With each new anchor frame, parameter values for lane boundary estimates (known as lane boundary states) can be recalculated with respect to the new anchor frame. Triggering events may a based on a length of time, distance traveled, and/or an uncertainty value.

An IMU sensor fault detection method and apparatus for a multiple IMUs and GNSS integrated navigation system is disclosed. The method is based on a decentralized Kalman filter. In a navigation system in which multiple IMU sensors and GNSS sensors are integrated, a fault of an IMU sensor is detected through correlation analysis between fault detection test statistics of each sub-filter consisting of each IMU sensor.

An IMU sensor fault can be detected and meet the navigation continuity probability requirement required by the system to support the operation of high-safety autonomous vehicles. By considering the correlation between the sub-filters, the continuity requirement assigned to each sub-filter is relaxed, and the relaxed continuity requirement has a direct effect on the improvement of the navigation system availability, contributing to the increase of the system availability.

A method and apparatus for displaying a virtual route estimates a position of a vehicle based on sensing data received asynchronously from sensors, and outputs a three-dimensional (3D) virtual route generated by registering a driving environment model corresponding to a driving environment of the vehicle and the position of the vehicle in map information.

A measurement processing method, wherein: during an operational phase, a second computer executes a first algorithm for estimating a new value of a datum; during a phase when the second computer is unavailable, a first computer determines and records characteristics of a signal measured by a sensor, the number of characteristics determined during the phase being strictly less than the number of intermediate measurements that the first computer establishes during the operational phase; the unavailability phase is stopped at a time t2 and the method proceeds to an active recovery phase, during which the second computer executes a second algorithm for estimating a value of the datum at a time within the interval [t1; t2] based on the characteristics determined and recorded during the unavailability phase; then the active recovery phase is stopped and the method returns to the operational phase.

A method for simultaneous localization and mapping is provided, which can reliably handle strong rotation and fast motion. The method provided a simultaneous localization and mapping algorithm framework based on a key frame, which can support rapid local map extension. Under this framework, a new feature tracking method based on multiple homography matrices is provided, and this method is efficient and robust under strong rotation and fast motion. A camera orientation optimization framework based on a sliding window is further provided to increase motion constraint between successive frames with simulated or actual IMU data. Finally, a method for obtaining a real scale of a specific plane and scene is provided in such a manner that a virtual object is placed on a specific plane in real size.

Movement information is calculated with high accuracy, without being influenced by the number of GNSS signals receivable by each of a plurality of antennas. A movement information calculating device includes a plurality of antennas, a clock generator, a plurality of GNSS receivers, and an arithmetic logical unit. The plurality of antennas, each receives a GNSS signal. The clock generator generates a clock signal. The plurality of GNSS receivers are connected to the respective antennas, and share the clock signal from the clock generator and calculate GNSS observed values by using the shared clock signal and the GNSS signals, respectively. The arithmetic logical unit calculates movement information including a speed of a movable body based on the GNSS observed values from the plurality of GNSS receivers.

A method and a device resets an inertial unit of a transport on the basis of information delivered by a viewfinder of the transport. According to one embodiment: a horizontal velocity vector of the transport and coordinates of the transport are obtained from the inertial unit, a horizontal line of sight of the viewfinder is obtained on at least one landmark, coordinates of at least one landmark are obtained, an angle between the horizontal velocity vector and the horizontal line of sight is computed, the drift of the computed angle is computed, an error is computed on the basis of the obtained coordinates, the computed angle and its computed drift, and the computed error is transferred to a Kalman filter for filtering the error and resetting the inertial unit.