A system includes: a device capable of surveying a measurement target or emitting laser light; an acceleration sensor capable of detecting an acceleration of the device; an output unit capable of outputting information; a storage unit configured to store: history information on the acceleration; and a correspondence table including a predetermined condition to be detected based on the acceleration and an operation detail in correspondence with each other; and a control unit configured to control output of the output unit based on the operation detail corresponding to the predetermined condition of the device associated in accordance with the history information, if the acceleration detected by the acceleration sensor is determined to correspond to the predetermined condition.

A system includes: a device capable of surveying a measurement target or emitting laser light; an acceleration sensor capable of detecting an acceleration of the device; an output unit capable of outputting information; a storage unit configured to store: history information on the acceleration; and a correspondence table including a predetermined condition to be detected based on the acceleration and an operation detail in correspondence with each other; and a control unit configured to control output of the output unit based on the operation detail corresponding to the predetermined condition of the device associated in accordance with the history information, if the acceleration detected by the acceleration sensor is determined to correspond to the predetermined condition.

This application discloses a calibration method for navigation of an unmanned aerial vehicle (UAV), a non-transitory computer-readable storage medium and a UAV implementing the same. The calibration method includes: collecting, during a flight of the UAV, 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; acquiring valid data V.sub.k according to the zero-point offset M.sub.0 and the original data R.sub.k; and control headings and postures of the UAV according to the valid data V.sub.k. With the calibration method in this application, the valid data V.sub.k is defined as a vector data acquired 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.

This application discloses a calibration method for navigation of an unmanned aerial vehicle (UAV), a non-transitory computer-readable storage medium and a UAV implementing the same. The calibration method includes: collecting, during a flight of the UAV, 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; acquiring valid data V.sub.k according to the zero-point offset M.sub.0 and the original data R.sub.k; and control headings and postures of the UAV according to the valid data V.sub.k. With the calibration method in this application, the valid data V.sub.k is defined as a vector data acquired 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.

The present invention relates to a multi-channel lidar sensor module capable of measuring at least two target objects using one image sensor. The multi-channel lidar sensor module according to an embodiment of the present invention includes at least one pair of light emitting units configured to emit laser beams and a light receiving unit formed between the at least one pair of emitting units and configured to receive at least one pair of reflected laser beams which are emitted from the at least one pair of light emitting units and reflected by target objects.

Multiple calibration results for calibrating a barometric pressure sensor based on data received from a device containing the sensor are determined and stored in a table. The table is updated based on rules regarding a relationship between each calibration result and a current calibration value. The calibration results are weighted and combined to determine a combined calibration result. The calibration value for calibrating the sensor is selected from the calibration results, the combined calibration results, or the current calibration value based on a selection criteria.

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.

An electronic device and method utilizes an external sensor group to facilitate miniaturization the device and repair/replacement of external sensors. An interface connected to an external sensor package including at least one sensor. A processor that when the external sensor package is connected through the interface, determines from which group the external sensor package is included in among pre-configured groups and controls the performance of a function corresponding to the determined group.

An electronic device and method utilizes an external sensor group to facilitate miniaturization the device and repair/replacement of external sensors. An interface connected to an external sensor package including at least one sensor. A processor that when the external sensor package is connected through the interface, determines from which group the external sensor package is included in among pre-configured groups and controls the performance of a function corresponding to the determined group.