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.

In an embodiment, a method includes: obtaining a first signal from a first sensor of a rotorcraft, the first signal indicating measured angular velocity around a first axis of the rotorcraft; filtering the first signal with a lag compensator to estimate angular position around the first axis of the rotorcraft; and adjusting flight control devices of the rotorcraft according to the estimated angular position and the measured angular velocity around the first axis of the rotorcraft, thereby changing flight characteristics of the rotorcraft around the first axis of the rotorcraft.

An inertial measurement system for a spinning projectile includes: 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; 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; 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.

A method and apparatus are provided for determining the orientation of an object relative to a platform likely to be exposed to buffeting. The object may be a helmet worn by a pilot in which orientation of the helmet relative the aircraft while in flight may usefully be known, in particular when determining the position of space-stabilised symbols being displayed in an associated helmet-mounted digital display system. According to the method, not only may orientation of an object may be predicted at some time ahead of a time point of validity of source sensor data, but the prediction may be dynamically configured to according to a detected severity of buffeting to reduce the effects of the buffeting upon the quality of data output by the system. The method includes measuring the severity of any buffeting using the same source data as used to determine orientation of the object.

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.

Examples of systems and methods for locating movable objects such as carts (e.g., shopping carts) are disclosed. Such systems and methods can use dead reckoning techniques to estimate the current position of the movable object. Various techniques for improving accuracy of position estimates are disclosed, including compensation for various error sources involving the use of magnetometer and accelerometer, and using vibration analysis to derive wheel rotation rates. Various techniques utilize characteristics of the operating environment in conjunction with or in lieu of dead reckoning techniques, including characteristic of environment such as ground texture, availability of signals from radio frequency (RF) transmitters including precision fix sources. Navigation techniques can include navigation history and backtracking, motion direction detection for dual swivel casters, use of gyroscopes, determining cart weight, multi-level navigation, multi-level magnetic measurements, use of lighting signatures, use of multiple navigation systems, or hard/soft iron compensation for different cart configurations.

A sensor module includes a first sensor device, a second sensor device, and a microcontroller. The first sensor device includes a first synchronization terminal to which an external synchronization signal or a synchronization signal which is a signal based on the external synchronization signal is input, a first interface outputs first measurement data to the microcontroller on the basis of the synchronization signal which is input to the first synchronization terminal, the second sensor device includes a second synchronization terminal to which the synchronization signal is input, and a second interface outputs second measurement data to the microcontroller on the basis of the synchronization signal which is input to the second synchronization terminal.

One or more embodiments herein can provide a process to determine dead-reckoning localization of a vehicle. An exemplary system can comprise a memory that stores computer executable components, and a processor that executes the computer executable components stored in the memory, wherein the computer executable components can comprise an obtaining component that obtains plural sensor readings defining movement of a vehicle, wherein the plural sensor readings comprise an inertial sensor reading, a kinematics sensor reading, and an odometry sensor reading, and a generation component that generates, based on the plural sensor readings, a pose value defining a position of the vehicle relative to an environment in which the vehicle is disposed. A sensing sub-system of the exemplary system can comprise an inertial measurement unit sensor, a kinematics sensor, and an odometry sensor.

The present invention relates to systems and methods for providing location and guidance, and more particularly for providing location and guidance in environments where global position systems (GPS) are unavailable or unreliable (GPS denied and/or degraded environments). The present invention further relates to systems and methods for using inertial measurement units IMUs to provide location and guidance. More particularly, the present invention relates to the use of a series of low-accuracy or low-resolution IMUs, in combination, to provide high-accuracy or high-resolution location and guidance results. The present invention further relates to an electronics-control system for handing off control of the measurement and guidance of a body in flight between groups or subgroups of IMUs to alternate between high dynamic range/lower resolution and lower dynamic range/higher resolution measurement and guidance as the environment dictates.

A method for calculating an INS initial heading angle error includes comparing an RTK trajectory with an INS trajectory under a tilt RTK application scenario, which may achieve heading angle initialization with an accuracy of 1 deg within 2 seconds. An INS trajectory estimation method eliminates accelerometers, and a large initial gyro bias is compensated by averaging the stationary gyro measurement at the beginning of the measurement to ensure the accuracy of the estimated INS trajectory. A rather short initialization duration also greatly improves the measurement efficiency. Compared with common heading initialization methods for the tilt RTK, the inventive method eliminates magnetometers and thus prevents interference from magnetic fields, obtaining stronger adaptability in complex environments.