The present invention provides a method of estimating an orientation of a wind turbine. The method comprises determining, using a polarising light compass of the wind turbine, a sun polarisation value, and determining a yaw angle of the wind turbine associated with the sun polarisation value. A sun direction vector is determined based on the sun polarisation value and the associated yaw angle; and an orientation of the wind turbine is estimated relative to a fixed direction using the sun direction vector.

The present invention provides a method of estimating an orientation of a wind turbine. The method comprises determining, using a polarising light compass of the wind turbine, a sun polarisation value, and determining a yaw angle of the wind turbine associated with the sun polarisation value. A sun direction vector is determined based on the sun polarisation value and the associated yaw angle; and an orientation of the wind turbine is estimated relative to a fixed direction using the sun direction vector.

A method configured to operate an electronic device is provided. The method includes first sensing information of a geomagnetic sensor and second sensing information of at least one motion sensor. Designated attributes of the first sensing information and the second sensing information are compared. When the geomagnetic sensor is determined as a specific state depending on the comparison result, performance of a designated internal device is controlled.

A method configured to operate an electronic device is provided. The method includes first sensing information of a geomagnetic sensor and second sensing information of at least one motion sensor. Designated attributes of the first sensing information and the second sensing information are compared. When the geomagnetic sensor is determined as a specific state depending on the comparison result, performance of a designated internal device is controlled.

A method of data calibration, and in particular sensor calibration, which involves gathering an initial first estimate and then binning the data samples, so that calibration can be performed without the need for a known reference stimulus. The present disclosure relates to calibration of vectors in a measurement system, and in particular to calibration of a correction function for systematic errors in successive data vectors. There is provided a method of determining a vector calibration function comprising: binning successive data vectors; and optimising the binned data vectors once data vectors allocated to a minimum number of unique bins have been observed. The method comprises establishing an initial calibration estimate and where the binning and optimising are performed based on said initial calibration estimate.

A heading calibration method, adapted for a compass sensor is provided. The heading calibration method includes the following steps. R data segments are sequentially generated by rotating the compass sensor by a predetermined angle, wherein the data segments includes a plurality of magnetic data respectively. A partial calibration process is executed to calibrate a reference point coordinate according to the magnetic data in r.sup.th data segment and a initial value of the reference point coordinate, wherein r is between 1 and the R. Parts of the magnetic data in the r.sup.th data segment is extracted as whole data, and a whole calibration process is executed according to the whole data to update an initial value of the reference point coordinate. The partial calibration process is executed according to the updated initial value of the reference point coordinate and the magnetic data in a (r+1).sup.th data segment.

A heading calibration method, adapted for a compass sensor is provided. The heading calibration method includes the following steps. R data segments are sequentially generated by rotating the compass sensor by a predetermined angle, wherein the data segments includes a plurality of magnetic data respectively. A partial calibration process is executed to calibrate a reference point coordinate according to the magnetic data in r.sup.th data segment and a initial value of the reference point coordinate, wherein r is between 1 and the R. Parts of the magnetic data in the r.sup.th data segment is extracted as whole data, and a whole calibration process is executed according to the whole data to update an initial value of the reference point coordinate. The partial calibration process is executed according to the updated initial value of the reference point coordinate and the magnetic data in a (r+1).sup.th data segment.

An automobile has a system for navigating using a vehicle speed sensor reading rotation data from a wheel and a gyroscopic sensor. For each of a plurality of error parameter values, a distance traveled for each of a plurality of directions of travel. The system also includes selecting the error parameter value that maximizes the distance traveled in one or more of the directions of travel, applying the selected error parameter value to data from the gyroscopic sensor, and navigating using dead reckoning based on data from the vehicle speed sensor and data from the gyroscopic sensor with the applied error parameter value.

An automobile has a system for navigating using a vehicle speed sensor reading rotation data from a wheel and a gyroscopic sensor. For each of a plurality of error parameter values, a distance traveled for each of a plurality of directions of travel. The system also includes selecting the error parameter value that maximizes the distance traveled in one or more of the directions of travel, applying the selected error parameter value to data from the gyroscopic sensor, and navigating using dead reckoning based on data from the vehicle speed sensor and data from the gyroscopic sensor with the applied error parameter value.

In one example a magnetometer unit comprises logic, to receive first magnetic response data from a first magnetic sensor and second magnetic response data from a second magnetic sensor displaced from the first magnetic sensor, generate a composite response surface representation from the first magnetic response data and the second magnetic response data, and store the composite response surface representation in a non-transitory memory. Other examples may be described.