A capacitive accelerometer includes a proof mass, first and second fixed capacitive electrodes, and a DC biasing element arranged to apply a DC voltage (V.sub.B) to the proof mass based on a threshold acceleration value. A first closed loop circuit is arranged to detect a signal resulting from displacement of the proof mass and control the pulse width modulation signal generator to apply the first and second drive signals V.sub.1, V.sub.2 with a variable mark:space ratio. A second closed loop circuit keeps the mark:space ratio constant and to change the magnitude, V.sub.B, of the DC voltage applied to the proof mass by the DC biasing element so as to provide a net electrostatic restoring force on the proof mass for balancing the inertial force of the applied acceleration and maintaining the proof mass at a null position, when the applied acceleration is greater than a threshold acceleration value.

A sensor data acquisition method using a plurality of electronic devices includes receiving sample sensor data from each of the electronic devices for each predetermined period; generating reference data based on the sample sensor data; calculating a measurement accuracy of each of the electronic devices for each predetermined period based on at least one of the sample sensor data or the reference data; determining priority information of each of the electronic devices for each predetermined period based on at least one of the measurement accuracy or state information of each of the electronic devices; determining a measurement-activated electronic device and a measurement-deactivated electronic device based on the priority information; receiving sensor data from the measurement-activated electronic device for a time unit of a predetermined period; and determining whether to change the measurement-activated electronic device to another electronic device based on the priority information updated in each predetermined period.

A sensor data acquisition method using a plurality of electronic devices includes receiving sample sensor data from each of the electronic devices for each predetermined period; generating reference data based on the sample sensor data; calculating a measurement accuracy of each of the electronic devices for each predetermined period based on at least one of the sample sensor data or the reference data; determining priority information of each of the electronic devices for each predetermined period based on at least one of the measurement accuracy or state information of each of the electronic devices; determining a measurement-activated electronic device and a measurement-deactivated electronic device based on the priority information; receiving sensor data from the measurement-activated electronic device for a time unit of a predetermined period; and determining whether to change the measurement-activated electronic device to another electronic device based on the priority information updated in each predetermined period.

A microelectromechanical system (MEMS) accelerometer sensor has a mobile mass and a sensing capacitor. To self-test the sensor, a test signal having a variably controlled excitation voltage and a fixed pulse width is applied to the sensing capacitor. The leading and trailing edges of the test signal are aligned to coincide with reset phases of a sensing circuit coupled to the sensing capacitor. The variably controlled excitation voltage of the test signal is configured to cause an electrostatic force which produces a desired physical displacement of the mobile mass. During a read phase of the sensing circuit, a variation in capacitance of sensing capacitor due to the actual physical displacement of the mobile mass is sensed for comparison to the desired physical displacement.

A microelectromechanical system (MEMS) accelerometer sensor has a mobile mass and a sensing capacitor. To self-test the sensor, a test signal having a variably controlled excitation voltage and a fixed pulse width is applied to the sensing capacitor. The leading and trailing edges of the test signal are aligned to coincide with reset phases of a sensing circuit coupled to the sensing capacitor. The variably controlled excitation voltage of the test signal is configured to cause an electrostatic force which produces a desired physical displacement of the mobile mass. During a read phase of the sensing circuit, a variation in capacitance of sensing capacitor due to the actual physical displacement of the mobile mass is sensed for comparison to the desired physical displacement.

Recalibrating a micromechanical sensor. The sensor is assigned a signal processing device for correcting the sensor signal on the basis of at least one previously determined initial trim value that is selected such that, given a defined sensor excitation, a production-related deviation of the sensor signal from a target sensor signal is compensated. The method for recalibrating the sensor includes: applying a defined electrical test excitation signal to the sensor structure, acquiring the corresponding sensor response signal, ascertaining a trim correction value for the at least one initial trim value on the basis of a previously determined relation between the sensor response signal and the trim correction value, and determining at least one current trim value for correcting the sensor signal, the determination of the at least one current trim value taking place on the basis of the at least one initial trim value and the ascertained trim correction value.

Motion can be induced at a vehicle, e.g., by actuating components of an active suspension system, and first sensor data and second sensor data representing an environment of the vehicle can be captured at a first position and a second position, respectively, resulting from the induced motion. A second sensor can determine motion information associated with the first position and the second position. Calibration information about the sensor, the first sensor data, and the motion information can be used to determine an expectation of sensor data at the second position. A calibration error can be the difference between the second sensor data and the expected sensor data.

Motion can be induced at a vehicle, e.g., by actuating components of an active suspension system, and first sensor data and second sensor data representing an environment of the vehicle can be captured at a first position and a second position, respectively, resulting from the induced motion. A second sensor can determine motion information associated with the first position and the second position. Calibration information about the sensor, the first sensor data, and the motion information can be used to determine an expectation of sensor data at the second position. A calibration error can be the difference between the second sensor data and the expected sensor data.

A calibration method includes: at least two poses of an imaging device are acquired, and at least two pieces of first sampling data of an inertial sensor are acquired; spline fitting process is performed on the at least two poses to obtain a first spline curve, and spline fitting process is performed on the at least two pieces of first sampling data to obtain a second spline curve; and time-space deviation between the imaging device and the inertial sensor is obtained according to the first spline curve and the second spline curve, where the time-space deviation includes at least one of a pose conversion relationship or a sampling time offset.

An approach is provided for calibrating vehicle motion data using a rotation matrix calculated based on mobile device sensor data, thereby determining vehicle events (e.g., forward acceleration, stoppages, etc.). The approach, for example, involves determining a road segment that meets one or more criteria for straightness, inclination, or a combination thereof. The approach also involves collecting sensor data from at least one sensor of a mobile device associated with a vehicle in motion on the road segment based on the determination. The sensor data indicates one or more acceleration vectors in a mobile device frame of reference. The approach further involves calibrating the one or more acceleration vectors from the mobile device frame of reference to a vehicle frame of reference based on the sensor data. The approach further involves providing the one or more calibrated acceleration vectors as an output.