A system for pedestrian use includes an accelerometer having multiple electronic sensors; an electronic circuit operable to generate a signal stream representing magnitude of overall acceleration sensed by the accelerometer, and to electronically correlate a sliding window of the signal stream with itself to produce peaks at least some of which represent walking steps, and further operable to electronically execute a periodicity check to compare different step periods for similarity, and if sufficiently similar then to update a portion of the circuit substantially representing a walking-step count; and an electronic display responsive to the electronic circuit to display information at least in part based on the step count. Other systems, electronic circuits and processes are disclosed.

A method of calibrating an inertial measurement unit, the method comprising: (a) collecting data from the inertial measurement unit while stationary as a first step; (b) collecting data from the inertial measurement unit while repositioning the inertial measurement unit around three orthogonal axes of the inertial measurement unit as a second step; (c) calibrating a plurality of gyroscopes using the data collected during the first step and the second step; (d) calibrating a plurality of magnetometers using the data collected during the first step and the second step; (e) calibrating a plurality of accelerometers using the data collected during the first step and the second step; (f) where calibrating the plurality of magnetometers includes extracting parameters for distortion detection and using the extracted parameters to determine if magnetic distortion is present within a local field of the inertial measurement unit.

Inertial measurement method and apparatus for a mobile entity perform a filtering process for an angular velocity signal, an alignment process where an approximate initial attitude angle is calculated from acceleration and angular velocity signals and then precisely adjusted, an angular velocity/acceleration bias calculation process where angular velocity bias is calculated by subtracting Earth's angular velocity from the angular velocity signal and an acceleration bias is calculated by subtracting gravitational acceleration from the acceleration signal, an attitude angle calculation process where an angular velocity is calculated by subtracting Earth's angular velocity and the angular velocity bias from the angular velocity signal, and an attitude angle is calculated by integrating the angular velocity, a location movement amount calculation process where acceleration is calculated by subtracting the gravitational acceleration and the acceleration bias from the acceleration signal, and calculate a location movement amount by second-order integration for the acceleration.

A system (10) for pedestrian use includes an accelerometer (110) having multiple electronic sensors; an electronic circuit (100) operable to generate a signal stream representing magnitude of overall acceleration sensed by the accelerometer (110), and to electronically correlate a sliding window (520) of the signal stream with itself to produce peaks at least some of which represent walking steps, and further operable to electronically execute a periodicity check (540) to compare different step periods for similarity, and if sufficiently similar then to update (560) a portion of the circuit substantially representing a walking-step count; and an electronic display (190) responsive to the electronic circuit (100) to display information at least in part based on the step count. Other systems, electronic circuits and processes are disclosed.

A method for determining navigation parameters of a vehicle under varying center of gravity position, the method comprising, detecting a plurality of acceleration values via a plurality of accelerometers, calculating a plurality of differential values based on the acceleration values, calculating an initial inertia value of the vehicle based on the differential values, calculating an initial mass value of the vehicle based on the differential values, obtaining a plurality of disturbance parameters, calculating a refined inertia value based on the initial inertia value and a first one of the disturbance parameters, calculating a refined mass value based on the initial mass value and a second one of the disturbance parameters, and determining navigation parameters based on the refined inertia value and the refined mass value.

Method, navigation device and computer program product for assisting with the navigation of a vehicle equipped with a navigation device, comprising the following steps: acquiring a priori values of kinematic variables of the navigation device, determining (202) respective current values of the kinematic variables of the navigation device and a current uncertainty matrix representative of an uncertainty of the respective current values of the kinematic variables, based on respective previous values of the kinematic variables, a previous uncertainty matrix representative of an uncertainty of the respective previous values of the kinematic variables and a model of Earth's gravity experienced by the navigation device, the modeled gravity increasing with an altitude of the navigation device.

The present disclosure relates to a method and apparatus for determining the misalignment between a device and a pedestrian, wherein the pedestrian can carry, hold, or use the device in different orientations in a constrained or unconstrained manner, and wherein the device comprises a sensor assembly. The sensors in the device may be for example, accelerometers, gyroscopes, magnetometers, barometer among others. The sensors have a corresponding frame for the sensors' axes. The misalignment between the device and the pedestrian means the misalignment between the frame of the sensor assembly in the device and the frame of the pedestrian. The present method and apparatus can work whether in the presence or in the absence of absolute navigational information updates (such as, for example, Global Navigation Satellite System (GNSS) or WiFi positioning).

An orientation identification method for identifying an orientation of a device installed by being mounted on a moving body includes: obtaining a certain amount of acceleration in three mutually orthogonal directions detected by an acceleration sensor included in the device; and identifying the orientation of the device expressed in a coordinate system from acceleration data indicating the certain amount of acceleration obtained in the obtaining, according to movement characteristics indicated by statistics of acceleration during movement of the moving body expressed in the coordinate system, the coordinate system including a gravitational acceleration direction as an axis.

Systems and methods for determining pose parameters of an inertial measurement unit (IMU) sensor include collecting measurement data generated by IMU sensors, using a processor to temporally integrate the measurement data, including any errors, generating a temporally continuous error propagation model, and temporally integrating the model to generate one or more compensation gradients for said pose parameters.

A method for determining a yaw angle estimate or vehicle heading direction is presented. A potential range of yaw angles is generated based on a plurality of primary telematics data. One or more yaw angle estimates are generated from the potential range of yaw angles. A driving pattern is determined based on at least one of the yaw angle estimates. The primary telematics data is a plurality of telematics data originated from a client computing device. The effects of gravity have been removed from the plurality of telematics data in a first primary movement window.