This application discloses a vector sensor zero-point calibration method, device, and, apparatus, an electronic device, and a non-volatile computer-readable storage medium. The calibration method includes: acquiring reference data during two measurements of a reference vector performed by a vector sensor; acquiring a zero-point offset M.sub.0 of the vector sensor according to the reference data; acquiring original data R.sub.k of any vector measured by the vector sensor; and acquiring valid data V.sub.k according to the zero-point offset M.sub.0 and the original data R.sub.k. With the calibration method in this application, the valid data V.sub.k is obtained after a zero-point error of the original data R.sub.k is eliminated, which is more closely approximated to an actual value of a to-be-measured vector.

The present invention relates to a method for updating strapdown inertial navigation solutions based on a launch-centered earth-fixed (LCEF) frame (g frame). The present invention uses the g frame as a navigation reference frame of a medium-to-short-range surface-to-surface missile. This is beneficial to establish a relative relationship between the missile and the ground so as to keep the same missile parameters required by a missile control and guidance system. The calculation of a navigation algorithm in the g frame is moderate, which is suitable for an embedded system.

Described are techniques and systems for secure camera based IMU calibration for stationary systems, including vehicles. Existing vehicle camera systems are employed, with enhanced security to prevent malicious attempts by hackers to try and cause a vehicle to enter IMU calibration mode. IMU calibration occurs when a calibration system determines the vehicle is parked in a controlled environment; calibration targets are positioned at different viewing angles to vehicle cameras to act as sources of optical patterns of encoded data. Features of the patterns are for security as well as for alignment functionality. Images of the calibration targets enable inference of a vehicle coordinate system, from which calculations for IMU mounting error compensations are performed. A relative rotation between the IMU and the vehicle coordinate system are applied to IMU data to compensate for relative rotations between the vehicle and the IMU, thereby improving vehicle slope and bank metrics.

A precision calibration method of attitude measuring systems is provided. The precision calibration method of attitude measuring systems includes the following steps: calibrating a zero-deviation, a scale coefficient, and a non-orthogonal angle between axes of an accelerometer to the attitude measuring system via an ellipsoid fitting model (S1); compensating original data of the accelerometer using a calculated ellipsoid parameter (S2); calibrating an electronic compass via the ellipsoid fitting model according to compensated accelerometer data (S3); compensating original electronic compass data by the calculated ellipsoid parameter (S4); calculating an attitude according to the compensated data of the accelerometer and compensated data of the electronic compass (S5). The above steps of the method have a reliable calibration result and a high precision with a less time consumption of calibration.

System for finding at least one mobile trolley in a locale, the system including at least one communication beacon which has a range covering the locale and which is connected to a computer control unit, and at least one electronic module mounted on the trolley and including a transmission device arranged to transmit position data to the communication beacon, and an inertial motion detection hub that includes a device for detecting linear motion along axes of a detection reference system and a device for detecting angular motion about the axes of the detection reference system and that is arranged to provide position data on the basis of linear motion measurement data and angular motion measurement data, the module being mounted on an element of the trolley such that any movement of the trolley within the locale causes angular movement of the element, the system being arranged to detect when the trolley is stopped when the angular motion measurement data correspond to zero angular motion at one measurement instant and being arranged to set to zero speeds calculated on the basis of the linear motion measurement data corresponding to the same measurement instant.

A method comprising: digitally processing orientation measurements provided by each of first and second inertial measurement units, the first and second units being arranged on first and second body members of a person, respectively, according to a predetermined unit arrangement, and the first and second body members being connected by a joint; the measurements are digitally processed such that the computing device at least: computes a length vector of a segment of the first body member based on a first orientation measurement of the first unit; defines a joint axis plane of the joint based on a second orientation measurement of the second unit; and computes a heading rotation value for making the first orientation measurement to be contained within the joint axis plane defined; and the method further comprising digitally modifying the first orientation measurement or the second orientation measurement by applying a rotation at least based on the heading rotation value computed. Also, a motion tracking system and a computer program product.

An inertial navigation system includes a first inertial measurement unit with at least a first sensor and a second inertial measurement unit with at least a second sensor corresponding in type to the first sensor. The first inertial measurement unit is rotatably mounted relative to the second inertial measurement unit, The inertial navigation system further include a controller arranged to: acquire a first set of measurements simultaneously from both the first inertial measurement unit and the second inertial measurement unit; rotate the first inertial measurement unit relative to the second inertial measurement unit; acquire a second set of measurements simultaneously from both the first inertial measurement unit and the second inertial measurement unit; and calculate from the first set of measurements and the second set of measurements at least one error characteristic of the first sensor and/or the second sensor.

A thermal regulation system includes a sensor, one or more temperature adjusting devices, and a filler provided in a space between the sensor and at least one of the one or more temperature adjusting devices. The one or more temperature adjusting devices are (1) in thermal communication with the sensor, and (2) configured to adjust a temperature of the sensor from an initial temperature to a predetermined temperature at a rate of temperature change that meets or exceeds a threshold value.

There is provided a drive control device, a drive control method, and a program that allow for an improvement in detection accuracy of a multi-IMU. Angular velocities supplied from a plurality of inertial measurement units (IMUs) are acquired, drive frequencies of the plurality of IMUs are calculated on the basis of acquisition timings of the acquired angular velocities, and on the basis of the drive frequencies of the plurality of IMUs, in a case where an interval between peak frequencies of the drive frequencies is smaller than ½ of a half width of a drive frequency distribution, control is performed so as to change the drive frequencies by heating or cooling temperatures of the IMUs so that the interval can be widened. The present disclosure can be applied to a multi-IMU.

Systems and methods for determining a swing angle of a swing boom of a vehicle are provided. Sensor data is received from sensors disposed on a swing boom and a body of a vehicle. It is determined whether the swing boom is static or moving relative to the body based on the sensor data. In response to determining that the swing boom is static, the received sensor data is corrected based on an observed swing angle and an estimated swing angle is calculated based on the corrected sensor data. In response to determining that the swing boom is moving, the estimated swing angle is calculated based on the received sensor data. The estimated swing angle is output.