A sensor bias estimation device for estimating a bias of a yaw angular velocity sensor of a vehicle, includes: a bias estimation unit that acquires a yaw angular velocity integrated value by integrating a yaw angular velocity acquired from a yaw angular velocity sensor, acquires a GNSS azimuth from a GNSS unit which calculates, as the GNSS azimuth, an azimuth of the vehicle based on a GNSS signal, and acquires an estimated bias value based on an azimuth difference which is a difference between the yaw angular velocity integrated value and the GNSS azimuth; a first determination unit that determines whether a first condition that an accuracy of the GNSS azimuth acquired from the GNSS unit is within a prescribed range is met; and a bias decision unit that decides the estimated bias value as the bias of the yaw angular velocity sensor when the first condition is met.

Various implementations include systems for rendering 3D audio signals for a vehicle operator. In particular implementations, a method of spatializing audio for an audio device worn on a head of an operator includes: receiving audio data and location data, the location data indicating where the audio data should be rendered relative to the vehicle; tracking a head position of the operator of the vehicle; calculating a compensated location of where the audio data should be rendered based on the location data and the head position of the operator of the vehicle; and spatially rendering, using the audio device, the audio data at the compensated location.

Sensor data fusion systems that provide noise reduction and fault protection. The sensor data fusion system fuses data acquired by respective accelerometers having different attributes. For example, one accelerometer has low noise and high bias, while another accelerometer has high noise and low bias when measuring specific force. The high-noise, low-bias accelerometer may be a gravimeter. Gravimeters and traditional accelerometers measure the same physical variable, i.e., specific force. By combining an expensive gravimeter and low-cost accelerometers, a synthetic sensor having both low noise and low bias may be achieved. Such synthetic sensors may be utilized in a gravity anomaly-referenced navigation system to achieve improved navigation performance.

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.

A method of controlling a mobile platform includes measuring a distance between the mobile platform and an object when the mobile platform is located at each of a plurality of positions to obtain a plurality of measured distances each being obtained at one of the plurality of positions. Location information of the plurality of positions of the mobile platform is obtained by an inertial measurement unit (IMU) on the mobile platform. The at least two distance sensors being configured to capture data from different directions. The method further includes determining a position of the object based on the plurality of measured distances and the location information and controlling the mobile platform to avoid the object based on the results of the determined position of the object.

The invention provides a method for initial alignment of radar assisted airborne strapdown inertial navigation system. By calculating the slant distance and angular position between the radar and the airborne inertial navigation equipment, a nonlinear measurement equation for the initial alignment of the radar assisted inertial navigation system is obtained. The unscented Kalman filter algorithm is used to estimate and compensate the error amount of strapdown inertial navigation system to complete the initial alignment task. The significance of the present invention is to provide an in-flight initial alignment solution when the global positioning system is limited, which has fast convergence speed and high estimation accuracy and has high engineering application value.

The performance of a microelectromechanical systems (MEMS) device may be subject to unwanted thermal gradients or nonuniform temperatures. The thermal gradients may be approximated based on voltage measurements taken through bond wires coupled to bond points located on the MEMS device. Thermal gradient measurement may be improved depending on the arrangement of bond wires and/or the material of the bond wires. Sense circuitry that is coupled to the MEMS device may determine corrective actions, such as updating the operation of the MEMS device, that compensate for the adverse effects from the thermal gradients.

A method for calibrating zero rate offset (ZRO) of a first inertial sensor located on a device, the method includes determining a stability level of the device based on information associated with at least one non-inertial sensor located on the device; and performing a calibration of the ZRO of the first inertial sensor when the stability level is above a threshold.

In a method and with a device for position determination by inertial navigation, a current position is determined from a known starting position and starting orientation by sensing accelerations and rotation rates. To do this, sensors are used to sense accelerations and rotation rates, and the accelerations and rotation rates acting on the sensors along or about three sensor axes are calculated. An evaluation device is used to determine a position from the data of the individual sensors, and the vector components of the positions determined are then added in a weighted manner. The weightings are determined by calibration.

A method, an apparatus, a device, and a medium for calibrating a temperature drift are provided. The method includes: acquiring a first measurement value and a second measurement value, the first measurement value being a measurement value of a to-be-measured quantity at a current moment determined based on an inertial measurement unit, and the second measurement value being a measurement value of the to-be-measured quantity at the current moment determined based on a global positioning system; and determining a temperature drift calibration value of the inertial measurement unit at the current moment based on the first measurement value and the second measurement value.