Abstract: A method for calculating an INS initial heading angle error includes comparing an RTK trajectory with an INS trajectory under a tilt RTK application scenario, which may achieve heading angle initialization with an accuracy of 1 deg within 2 seconds. An INS trajectory estimation method eliminates accelerometers, and a large initial gyro bias is compensated by averaging the stationary gyro measurement at the beginning of the measurement to ensure the accuracy of the estimated INS trajectory. A rather short initialization duration also greatly improves the measurement efficiency. Compared with common heading initialization methods for the tilt RTK, the inventive method eliminates magnetometers and thus prevents interference from magnetic fields, obtaining stronger adaptability in complex environments.

Abstract: A static state determining method and apparatus are disclosed to resolve a problem in the prior art that accuracy of determining a static state is low. An inertial navigation system obtains a first running data that is measured by an IMU in a first specified duration, determines N first standard deviations of the first running data; matches the N first standard deviations with a prestored database; determines, in the prestored database, a piece of first information corresponding to each of the N second standard deviations; multiplies a first probability in each of the N pieces of first information by a corresponding weight, and adds N values obtained through the multiplication and if the second probability is greater than or equal to a static probability threshold, the inertial navigation system determines that a device in which the inertial navigation system is located is in a static state in the first specified duration.

Abstract: The invention relates to a quick calibration method for an inertial measurement unit (IMU). According to the method, a user holds and rotates the IMU to move in all directions without any external equipment, so that twelve error coefficients including gyro biases, gyro scale factors, accelerometer biases and accelerometer scale factors can be accurately calibrated in a short time. The quick calibration method for the IMU is characterized by being free of hardware cost, high in efficiency and simple and easy to implement, and can ensure certain calibration precision. Thus, the quick calibration method is especially suitable for in-situ quick calibration for the medium- and low-grade IMUs, thereby effectively solving the problem of environmental sensitivity of the error coefficients of the mechanical IMU, and promoting popularization and application of MEMS (micro-electro mechanical systems) inertial devices.

Abstract: Disclosed are systems and methods for evaluating the navigation performance of MEMS inertial sensors. The method uses MEMS inertial sensors static data signals to estimate the static sensor errors and combines them with a reference kinematic signal obtained through field testing of a high-grade inertial sensor. Such emulated field data may then be processed with the corresponding GPS data collected in the same or different field test to evaluate the navigation performance of the MEMS inertial sensors.

Abstract: Compensating for the misalignment of a navigation device with respect to a vehicle is described. In one example, the compensation is made by applying a high pass filter to a measured acceleration of the vehicle to produce a motion acceleration signal, weighting the motion acceleration signal with a measured steering rate of the vehicle, and deriving misalignment parameters for the navigation device with respect to the vehicle using the weighted motion acceleration signal.

Abstract: Disclosed are systems and methods for evaluating the navigation performance of MEMS inertial sensors. The method uses MEMS inertial sensors static data signals to estimate the static sensor errors and combines them with a reference kinematic signal obtained through field testing of a high-grade inertial sensor. Such emulated field data may then be processed with the corresponding GPS data collected in the same or different field test to evaluate the navigation performance of the MEMS inertial sensors.

Abstract: Compensating for the misalignment of a navigation device with respect to a vehicle is described. In one example, the compensation is made by applying a high pass filter to a measured acceleration of the vehicle to produce a motion acceleration signal, weighting the motion acceleration signal with a measured steering rate of the vehicle, and deriving misalignment parameters for the navigation device with respect to the vehicle using the weighted motion acceleration signal.