Disclosed is a self-adaptive horizontal attitude measurement method based on motion state monitoring. Based on a newly established state space model, a horizontal attitude angle is taken as a state variable, an angular velocity increment Δω.sup.b for compensating a random constant zero offset is taken as a control input of a system equation, and a specific force f.sup.b for compensating the random constant zero offset is taken as a measurement quantity. Meanwhile, judgment conditions for a maneuvering state of a carrier are improved, and maneuvering information of the carrier is judged by comprehensively utilizing acceleration information and angular velocity information output by a micro electro mechanical system inertial measurement unit (MEMS-IMU), whereby a measurement noise matrix of a filter can be automatically adjusted, thereby effectively reducing the influence of carrier maneuvering on the calculation of a horizontal attitude. The method has no special requirement on the maneuvering state of the carrier, and can ensure that the system has high attitude measurement precision in different motion states without an external information assistance.

A posture estimation device includes an acquisition part acquires information of angular velocities and accelerations from a plurality of sensors that detects angular velocities and accelerations and that are attached to a plurality of locations on an estimation object, a conversion part that converts information acquired by the acquisition part into information of a standard coordinate system from a sensor coordinate system, an integrating part that calculates an orientation of a reference area of the estimation object as a part of a posture of the estimation object by integrating the converted angular velocities, and a correction part, assuming a representative plane passing through a reference area included in the estimation object, corrects the converted angular velocities of the reference area so that a normal line of the representative plane and an orientation of the reference area calculated by the integrating part approaches to directions that are perpendicular to each other.

There is proposed a method of estimating a navigation state with several variables of a mobile carrier according to the extended Kalman filter method, comprising the steps of:—acquisition of measurements of at least one of the variables,—extended Kalman filtering (400) producing a current estimated state and a covariance matrix delimiting in the space of the navigation state a region of errors, with the help of a previous estimated state, of an observation matrix, of a transition matrix and of the measurements acquired, the method being characterized in that it comprises a step (310, 330) of adjustment of the transition matrix and of the observation matrix before their use in the extended Kalman filtering in such a way that the adjusted matrices satisfy an observability condition which depends on at least one of the variables of the state of the carrier, the observability condition being adjusted so as to prevent the Kalman filter from reducing the dimension of the region along at least one non-observable axis of the state space, in which the observability condition to be satisfied by the adjusted transition and observation matrices is the nullity of the kernel of an observability matrix associated therewith and in which the adjustment comprises the steps of:—calculation (301) of at least one primary basis of non-observable vectors with the help of the previous estimated state—for each matrix to be adjusted, calculation (306, 308) of at least one matrix deviation associated with the matrix with the help of the primary basis of vectors, shifting (330) of each matrix to be adjusted according to the matrix deviation associated therewith so as to satisfy the observability condition.

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.

An apparatus and method for measuring a velocity of a moving object in a navigation system are provided, which can increase an accuracy of velocity measurement and position estimation of the moving object are provided. The apparatus includes a sensor part including an acceleration sensor for measuring acceleration of the moving object and outputting a corresponding acceleration measurement value, and includes an altimeter for measuring an altitude of the moving object and outputting a corresponding altitude measurement value; and a calculation part for calculating the velocity of the moving object by using the acceleration measurement value output from the acceleration sensor and the altitude measurement value output from the altimeter.

A method for filtering the signals arising from a sensor assembly (EC) comprising at least one measurement sensor for measuring a vector physical field which is substantially constant over time and in space in a reference frame, said sensor assembly (EC) being tied in motion to a moving frame, moving in the reference frame, the method comprising the steps consisting in: applying a first transformation (T1) to the measurements of a measurement sensor of the sensor assembly (EC) which are provided in the moving frame, to a pseudo reference frame, with the aid of a first change-of-frame operator (R(t)) by rotation between the moving frame and the pseudo reference frame; and applying a filtering (FILT) to the measurements thus transformed in the pseudo reference frame; and applying a second transformation (T2), the inverse of said first transformation, to the measurements filtered by said filtering (FILT), from the reference frame to the moving frame, with the aid of a second change-of-frame operator (R.sup.−1(t)) by rotation between the pseudo reference frame and the moving frame, the inverse of said first operator (R(t)).

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.

An inertial measurement system (200) for a longitudinal projectile, comprising a first, roll gyro to be oriented substantially parallel to the longitudinal axis of the projectile; a second gyro and a third gyro with axes arranged with respect to the roll gyro such that they define a three dimensional coordinate system. The system further comprises a controller (225, 250), arranged: —to compute a current projectile attitude from the outputs of the first, second and third gyros, the computed attitude comprising a roll angle, a pitch angle and a yaw angle; —for at least two time points, to compare the computed pitch and yaw angles with expected values for the pitch and yaw angles; —for each of said at least two time points, to calculate a roll angle error based on the difference between the computed pitch and yaw angles and the expected pitch and yaw angles; —to calculate a roll angle error difference between said at least two time points; —to calculate the total roll angle subtended between said at least two time points; —to calculate a roll angle scale factor error based on said computed roll angle error difference and said total subtended roll angle and apply the calculated roll angle scale factor error to the output of the roll gyro.

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.

Techniques provided herein are directed toward addressing these and other issues by providing robust means for initializing an accelerometer that can take place even while a vehicle is in motion. Specifically, linear acceleration and velocity data can be estimated from wheel speeds, and angular velocity can be estimated with a gyroscope. The vehicle's acceleration can then be computed from these estimates, and subtracted from a total acceleration measured by the accelerometer to determine gravitational acceleration, which can then be accounted for in subsequent measurements taken by the accelerometer. A vehicle velocity may also be determined based on the vehicle's estimated angular velocity and linear velocity. Embodiments may also employ techniques for translating measurements taken in one coordinate frame to another coordinate frame for estimate determination and/or outlier compensation.