An inertia-based navigation apparatus and an inertia-based navigation method based on relative preintegration are provided. The inertia-based navigation apparatus includes: a first sensor detecting and outputting motion information about a moving body which is moving, based on a first coordinate system; a second sensor detecting and outputting inertia data about a translational acceleration and a rotational angular velocity related to the movement of the moving body, based on a second coordinate system; and a controller determining, at every first time, pose information about a position, a velocity and an attitude of the moving body in a reference coordinate system, based on the motion information and the inertia data.

Demodulation circuitry includes an input terminal configured to be coupled to an analog-to-digital converter (ADC) and configured to receive a plurality of ADC outputs. The plurality of ADC outputs are generated based on resolver outputs. The demodulation circuitry also includes a rectifier configured to rectify the plurality of ADC outputs. Rectifying the plurality of ADC outputs preserves a phase of the plurality of ADC outputs. The demodulation circuitry includes amplitude determination circuitry configured to determine, based on the rectified plurality of ADC outputs, demodulated amplitude values corresponding to the resolver outputs. The demodulation circuitry further includes angle computation circuitry configured to generate position outputs based on the demodulated amplitude values.

In a locator device, a dead reckoning part calculates a position of a subject vehicle by dead reckoning. A pseudorange smoothing part smooths a pseudorange between a GNSS satellite and a position of the subject vehicle using a carrier wave phase of the GNSS satellite. A GNSS receiver positioning error evaluation part evaluates reliability of the position of the subject vehicle calculated by the multi-GNSS receiver. A GNSS positioning part (KF method) calculates a position of the subject vehicle from a smoothed value of the pseudorange, a positioning augmentation signal, and an orbit of the GNSS satellite. A complex positioning part (KF method) calculates an error in the dead reckoning from the position of the subject vehicle calculated by the GNSS positioning part (KF method), and corrects the position of the subject vehicle calculated by the dead reckoning part based on the error in the dead reckoning.

A system includes a memory and a processor. The memory is configured to store map data indicating positions of landmarks. The processor is configured to receive image data from an image sensor. The processor is also configured to determine, based on the image data, a first estimate of a position, relative to the image sensor, of a landmark identified in the map data. The processor is configured to determine orientation of the image sensor based on inertial measurement unit measurements. The processor is also configured to determine, based on position information, the orientation, and the map data, a second estimate of the position of the landmark. The processor is configured to determine position offset data based on a comparison of the first estimate and the second estimate. The processor is also configured to generate, based on the position offset data and the position information, an output indicating an adjusted position.

A method for improving the accuracy of an inertial navigation system (INS) by performing a synchronization procedure to align the INS to a compass-derived initial heading comprises the steps of determining a heading of minimal error for the compass and defining that heading as the initial heading; orienting the INS to align with the so-defined initial heading; synchronizing the internal navigation system to that heading; and proceeding with navigation by use of the INS. The INS may be vehicle mounted or be contained in a portable navigation unit for swimmers or other users. The heading of minimal error may be determined by placing the compass within a multi-axis Helmholz coil system and monitoring compass readings and deviation errors as a function of actual compass positions.

A functional iterative integration-based method for an inertial navigation solution includes: fitting a Chebyshev polynomial function of an angular velocity and a Chebyshev polynomial function of a specific force according to gyroscope-measured values and accelerometer-measured values on a time interval; iteratively calculating Chebyshev polynomial coefficients of an attitude quaternion by using the obtained Chebyshev polynomial coefficients of the angular velocity and an integral equation of the attitude quaternion, and performing polynomial truncation on a result obtained from each iterative calculation according to a preset order; iteratively calculating Chebyshev polynomial coefficients of a velocity/position by using the obtained Chebyshev polynomial coefficients of the specific force, the Chebyshev polynomial coefficients of the attitude quaternion and an integral equation of the velocity/position, and performing polynomial truncation on a result obtained from each iterative calculation according to a preset order; and obtaining attitude/velocity/position information on the corresponding time interval.

The present invention discloses a cubature Kalman filtering method suitable for high-dimensional GNSS/INS deep coupling, including: S1, constructing a high-dimensional GNSS/INS deep coupling filter model; S2, generating an initialization cubature point for the constructed filter model by using standard cubature rules; S3, performing CKF filtering by using novel cubature point update rules. The present invention is suitable for high-dimensional GNSS/INS deep coupling filtering with high precision and high stability.

A method for detecting malfunctions in inertial measurement units which are used in a vehicle to measure angular velocities and specific forces may have at least three inertial measurement units. Each inertial measurement unit may have a plurality of sensors, such as accelerometer and gyroscopic sensors. A first inertial measurement unit is used as a master inertial measurement unit. A second inertial measurement unit and a third inertial measurement unit, the capabilities of which can be lower than those of the first inertial measurement unit, are used as slave inertial measurement units. Measurements of the master inertial measurement unit are used as reference values to compensate measurements of the slave inertial measurement unit regarding estimation of error model parameters with respect to the master inertial measurement unit to detect a malfunction in one of the three sensor signals.

The invention concerns a method for estimating navigation date of a land vehicle, comprising steps of: recciving inertial data (100) acquired by an inertial sensor, receiving geometry and orientation parameters of a travelled road, integrating (106) the data on the basis of the parameters in order to produce navigation data comprising a movement of the vehicle relative to the road measured in a direction (Zr, Yr), the vehicle only being able to move in the direction within a bounded interval without leaving the road, estimating (108) an error affecting the navigation data by sol ing equations assuming that a difference between the calculated movement and a reference movement constitutes an error in the movement of the vehicle parallel to the direction, the reference movement having a value less than or equal to the length of the interval, correcting (110) the produced navigation data from the estimated error.

Methods of calibrating strapdown heading sensors and strapdown heading sensors are provided. The methods include compensating raw sensor data generated by sensors of an uncalibrated strapdown heading sensor to compensate for errors in an instrument frame of the strapdown heading sensor. The strapdown heading sensor is put in a target apparatus and output data is compensated to compensate for errors in an apparatus frame relative to the instrument frame. The strapdown heading sensors include a housing and a compass module having a first sensor configured to detect a magnetic field of the Earth and a second sensor configured to detect a gravitational force of the Earth. The first sensor and the second sensor are each passively isolated from bending and/or flexing of the housing such that an alignment between the first sensor and the second sensor is not disturbed due to the bending and/or flexing.