The disclosure discloses a latitude-free initial alignment method under a swaying base based on gradient descent optimization. Firstly, swaying base latitude-free alignment is regarded as a Wahba attitude determination problem to inhibit device noise interference, and an objective function is established based on a gravitational acceleration vector under an earth system; then an exact solution of the objective function is obtained through a gradient descent optimization method, and inertial system conversion quaternion estimation is achieved under the latitude-free condition; and finally, an attitude quaternion is determined by only using information of an accelerometer and a gyroscope of a strapdown attitude heading reference system, and therefore latitude-free initial alignment under the swaying base is achieved. The disclosure can solve the problem that initial alignment cannot be accomplished with unknown latitude under the swaying base, and thus the application range of the strapdown attitude heading reference system is ensured.

A method for stabilizing a magnetic field of an inertial measurement unit (IMU), is provided that includes initializing accelerometer and gyroscope (AG) heading data for the IMU and initializing accelerometer, gyroscope and magnetometer (AGM) heading data for the IMU. Determining whether a tracking state exists and completing processing of the AG heading data and the AGM heading data if the tracking state does not exist. Calculating a magnetic field error if the tracking state exists.

A method of controlling a mobile platform includes measuring a distance between the mobile platform and an object when the mobile platform is located at each of a plurality of positions to obtain a plurality of measured distances each being obtained at one of the plurality of positions. Location information of the plurality of positions of the mobile platform is obtained by an inertial measurement unit (IMU) on the mobile platform. The at least two distance sensors being configured to capture data from different directions. The method further includes determining a position of the object based on the plurality of measured distances and the location information and controlling the mobile platform to avoid the object based on the results of the determined position of the object.

An apparatus for measuring gravity acceleration of a drilling tool comprises sensors and a measurement circuit. The sensor comprises a three-axis gravity accelerometer, a reference measurement sensor and a temperature sensor. The three-axis gravity accelerometer measures acceleration component signals in three mutually orthogonal directions, and the reference measurement sensor generates a signal that varies with rotation and is not affected by vibration or shock to serve as a reference signal. The temperature sensor measures the temperature in the apparatus to compensate the temperature effect of the gravity accelerometers. The measurement circuit acquires output signals of the sensors and performs cross-correlation processing on the accelerometer components using the reference signal to extract gravity acceleration signals so as to eliminate centrifugal acceleration, vibration, shock and other interferences generated by rotation. The non-interference gravity acceleration signals is used for calculating an inclination angle and a toolface angle of a drilling tool in the rotating state.

An ensemble of motion sensors is tested under known conditions to automatically ascertain instrument biases, which are modeled as autoregressive-moving-average (ARMA) processes in order to construct a Kalman filter. The calibration includes motion profiles, temperature profiles and vibration profiles that are operationally significant, i.e., designed by means of covariance analysis or other means to maximize, or at least improve, the observability of the calibration model's structure and coefficients relevant to the prospective application of each sensor.

There is provided an information processing apparatus that is able to more accurately detect an azimuth during traveling of a mobile object. The information processing apparatus includes a north-seeking process controller that performs a north-seeking process on a basis of, among pieces of information related to a mobile object, at least two pieces of information, in which orientations of the mobile object at respective timings when the at least two pieces of information are measured by an inertial measurement unit are different from each other, and at least one of the at least two pieces of information measured by the inertial measurement unit is measured while the mobile object is traveling.

A sensor data processing system of an autonomous vehicle can receive inertial measurement unit (IMU) data from one or more IMUs of the autonomous vehicle. Based at least in part on the IMU data, the system can identify an IMU data offset from a deficient IMU of the one or more IMUs, and generate an offset compensation transform to compensate for the IMU data offset from the deficient IMU. The system may then dynamically execute the offset compensation transform on the IMU data from the deficient IMU to dynamically compensate for the IMU data offset.

Methods are provided for determining a positioning of a portable device including first and second sensor(s) each having a confidence. These methods include: receiving first and second signals from the first and second sensor(s), respectively; generating positional data representing positional conditions of the portable device and including first and second positional data respectively from the first and second signals, by modelling the received signals based on predefined models defining a correspondence between predefined signals and predefined positional data; comparing the first and second positional data to determine a difference between them; adjusting the confidence of the sensors by determining a new confidence depending on a previous confidence and the determined difference between positional data; weighting the generated positional data depending on corresponding confidences; and determining the positioning of the portable device based on the weighted generated positional data. Computer programs and systems suitable for performing such methods are also provided.

In an inertial sensor that includes an angular rate detection circuit having a structure synchronized with a resonant frequency of an angular rate detection element, an object thereof is to realize an angle output having high accuracy with less integration error in an integration circuit for detecting an angle. The inertial sensor includes an angular rate detection element chip C1 that has a mechanical structure for angular rate detection; and a signal processing LSI chip C2 that is angular rate detection circuit for detecting an angular rate from the angular rate detection element chip C1. The signal processing LSI chip C2 calculates an angle by sampling a signal obtained from the angular rate detection element chip C1 at a discrete time synchronized with a drive frequency of the angular rate detection element chip C1.

An integrated navigation method for a mobile vehicle is provided, which includes: acquiring a motion measurement of the mobile vehicle by using an inertial navigation element in the mobile vehicle and calculating a gesture parameter of the mobile vehicle based on the motion parameter; estimating, based on the gesture parameter, a motion state of the mobile vehicle in a real time manner by using a satellite navigation element in the mobile vehicle to obtain an error estimation value of the motion state, and correcting a motion parameter of the mobile vehicle based on the error estimation value of the motion state; and controlling an operation route of the mobile vehicle based on corrected navigation information.