Abstract:
A method and device for calibrating a magnetometer device. In an embodiment, the present invention provides a method to automatically calibrate a magnetometer device in the background with only limited movement in each of the three axis (approximately 20 degrees in each direction). A device implementing the present method will never get stuck in a lock-up state. Embodiments of the present invention provide a conservative and accurate magnetometer status indicator that is essential for indoor navigation using inertial sensors. The implemented algorithm is relatively low computationally intensive and is intelligent enough to know when it has the right kind and right amount of magnetic data before it initiates a calibration.
Abstract:
A method is provided for time synchronization in a MEMS (MicroElectroMecahnical system) based system having a MEMS processor and a plurality of MEMS devices. In a specific embodiment, the method includes, in the MEMS processor, transmitting a synchronization signal to the plurality of MEMS devices and saving a local time upon transmitting the synchronization signal. The MEMS processor also receives sampled data and time information from the plurality of MEMS devices, when the data and information become available. The method also includes, in one or more of the MEMS devices, receiving the synchronization signal from the MEMS processor and storing a local time upon receiving the synchronization signal. The MEMS device also performs a sensing operation and stores sampled sense data and sense time information.
Abstract:
A method and device for calibrating a magnetometer device. In an embodiment, the present invention provides a method to automatically calibrate a magnetometer device in the background with only limited movement in each of the three axis (approximately 20 degrees in each direction). A device implementing the present method will never get stuck in a lock-up state. Embodiments of the present invention provide a conservative and accurate magnetometer status indicator that is essential for indoor navigation using inertial sensors. The implemented algorithm is relatively low computationally intensive and is intelligent enough to know when it has the right kind and right amount of magnetic data before it initiates a calibration.