A navigation information processing method includes: acquiring motion state information of a vehicle based on an inertial device, and acquiring vehicle information of the vehicle based on a controller area network; performing a strapdown solution on the motion state information to obtain navigation information; fusing the navigation information and the vehicle information by using a preset Kalman filter to obtain target navigation information; and navigating the vehicle based on the target navigation information. Data collection does not need to rely on environment, and problems of unstable navigation effects caused by insufficient acquired data are solved. A Kalman filter is used to fuse navigation information and vehicle information, improving accuracy of navigation information and precision of positioning. A two-dimensional vector is used as an input vector of the Kalman filter, which has a simple filtering manner and consumes few hardware resources, reducing navigation costs.

An attitude measurement method, which relates to the technical field of measurement while drilling in directional drilling, which can improve the observability of inertial instrument errors, suppress the repeatability errors of gyroscopes and improve the attitude measurement accuracy. The method adopts the method of fine alignment at multiple positions to carry out initial alignment; the method includes the steps of: S1, taking current attitude data and velocity data of the strapdown inertial navigation system as first initial values, and performing fine alignment at a first position; S2, changing the position of a strapdown inertial navigation system to an nth position, and performing attitude update and velocity update according to the last fine alignment result in the position changing process; and S3, taking the results of attitude update and velocity update as the nth initial values, performing the nth fine alignment at the nth position to complete the initial alignment of the strapdown inertial navigation system, thereby realizing attitude measurement. The solution of the present invention is suitable for measuring the horizontal attitude and azimuth of the whole inclined section of a horizontal well, especially the application of directional drilling gyro measurement while drilling in the attitude measurement of large inclined wells and horizontal wells.

A system and to a method of analyzing and monitoring interfering movements of an inertial unit of an aircraft during a stage of statically aligning the inertial unit. During the static alignment stage, measurements of the velocity of the aircraft relative to the ground are acquired, and states of a mirror process having a model that is close to the model of the process of aligning the inertial unit are estimated. The states of the mirror process are estimated from observations constituted by the measurements of velocity relative to the ground. Finally, the estimates of the states are compared with respective validation thresholds in order to validate or not validate said alignment of the inertial unit.

A method and system for combining data obtained by sensors, having particular application in the field of navigation systems, are disclosed. The techniques provide significant improvement over state-of-the-art Markovian methods that use statistical noise filters such as Kalman filters to filter data by comparing instantaneous data with the corresponding instantaneous estimates from a model. In contrast, the techniques disclosed herein use multiple time periods of various lengths to process multiple sensor data streams, in order to combine sensor measurements with motion models at a given time epoch with greater confidence and accuracy than is possible with traditional “single epoch” methods. The techniques provide particular benefit when the first and/or second sensors are low-cost sensors (for example as seen in smart phones) which are typically of low quality and have large inherent biases.

Anchor points associated with point of sale information may be ordered by deriving a trajectory for the portable device, associating known positions of the anchor points with a map encompassing the trajectory, characterizing turns of the trajectory, generating candidate paths by comparing the characterized turns to the map, selecting a solution path that corresponds to the anchor points and ordering the anchor points based at least in part on the solution path.

This provides methods and systems for the global navigation satellite system (GNSS) combined with the dead-reckoning (DR) technique, which is expected to provide a vehicle positioning solution, but it may contain an unacceptable amount of error due to multiple causes, e.g., atmospheric effects, clock timing, and multipath effect. Particularly, the multipath effect is a major issue in the urban canyons. This invention overcomes these and other issues in the DR solution by a geofencing framework based on road geometry information and multiple supplemental kinematic filters. It guarantees a road-level accuracy and enables certain V2X applications which does not require sub-meter accuracy, e.g., signal phase timing, intersection movement assist, curve speed warning, reduced speed zone warning, and red-light violation warning. Automated vehicle is another use case. This is used for autonomous cars and vehicle safety, shown with various examples/variations.

Examples of systems and methods for locating movable objects such as carts (e.g., shopping carts) are disclosed. Such systems and methods can use dead reckoning techniques to estimate the current position of the movable object. Various techniques for improving accuracy of position estimates are disclosed, including compensation for various error sources involving the use of magnetometer and accelerometer, and using vibration analysis to derive wheel rotation rates. Various techniques utilize characteristics of the operating environment in conjunction with or in lieu of dead reckoning techniques, including characteristic of environment such as ground texture, availability of signals from radio frequency (RF) transmitters including precision fix sources. Navigation techniques can include navigation history and backtracking, motion direction detection for dual swivel casters, use of gyroscopes, determining cart weight, multi-level navigation, multi-level magnetic measurements, use of lighting signatures, use of multiple navigation systems, or hard/soft iron compensation for different cart configurations.

A positioning method applied to a mobile device having a sensor system and a positioning system includes determining that the mobile device is in a preset state; determining a speed reference value of the mobile device based on data detected by the sensor system; determining a position reference value of the mobile device based on preset map data and an estimated positioning value that is output by the positioning system; and correcting, based on the speed reference value and the position reference value, an estimated speed value and the estimated positioning value that are output by the positioning system.

An updating unit updates an attitude represented by quaternion by defining an initial attitude represented by quaternion as an initial value, and successively substituting output values of the triaxial gyro sensor. A second converter converts the attitude represented by quaternion into an attitude in the Euler angle representation. An angular speed derivation unit derives an angular speed based on a time-dependent change in the attitude in the Euler angle representation. The output unit outputs an angular speed derived based on an output value of a monoaxial gyro sensor, when a difference between a pitch angle derived based on the output value of the triaxial acceleration sensor and the output value of the second converter and a pitch angle from the second converter is equal to or larger than a threshold value.

A vehicular simultaneous localization and mapping may fuse lidar data and pseudoranges extracted from ambient cellular LTE towers. An ICP algorithm may be used to extract odometry measurements from successive lidar scans. A robust and computationally efficient feature extraction method may be used to detect edge lines and feature points from the lidars point cloud. Then, a point registration technique using a maximum likelihood approach allows the estimation of the covariance of the odometry error, which is used in EKF propagation. The proposed approach consists of a mapping mode when GNSS signals are available and subsequently a SLAM mode when GNSS signals become unavailable. The cellular transmitters states, namely position and clock bias and clock drift, are continuously estimated in both modes. Simulation and experimental results validate the accuracy of these systems and methods, and provides lane-level localization without GNSS signals.