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This paper investigates the attitude estimation errors caused by the deflections of vertical (DOV) in the case of a rotational inertial navigation system (INS) integrated with a global satellite navigation system (GNSS). It has been proved theoretically and experimentally that the DOV can introduce a tilt error to the INS/GNSS integration, whereas...
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... Some other systems such as GNSS receivers or odometer provide low-frequency measurements that can be fooled by jamming or short-term measurement errors, but these sensors provide good performance over the long term. The basic idea of Extended Kalman Filter (EKF) is to take the best of each sensor, and it includes a high-frequency prediction step using inertial sensors to precisely measure motion and navigation data [14][15][16]. The loose coupling between GPS/GNSS and the EKF allows GPS data to improve inertial sensor performance, and on the other hand, inertial data improve overall navigation performance. ...
As a kind of large-scale unmanned aerial vehicle, a high-altitude balloon can carry a large load up to tens of kilometers in the near space for a long time, which brings a new way for the stratosphere atmospheric detection. In order to provide a suitable working environment for the near-space detection load, it is necessary to design a sensor system based on a high-altitude balloon, which is used to provide environmental temperature, height position, and attitude information, current working, and video surveillance. The high-altitude balloon-based sensor system designed in this paper had participated in the near-space flight experiment, whose total flight time was 30 hours and 53 minutes, and the horizontal flight time was 28 hours and 58 minutes crossing the day and night. The high-altitude balloon-based sensor system had withstood the severe environment of the near-space during the day and night, providing accurate temperature measurement, real-time altitude position and attitude data acquisition, reliable current monitoring, and comprehensive video surveillance. In the next three years, the high-altitude balloon-based sensor system developed in this paper will continue to participate in the experiment and provide support for more detection loads.
... However, the navigation errors of INS are mainly caused by the gyroscope drifts and accelerometer biases. In order to improve the accuracy of INS without using the high-cost and high-precision IMU, the Rotational Inertial Navigation System (RINS) has been proposed [6][7][8]. In a RINS, the IMU is mounted on a rotary table and forced to rotate along the given axes back and forth to modulate the errors of IMU from constant to periodically varying components, so as to reduce the navigation errors [9]. ...
Single-axis rotational inertial navigation systems (single-axis RINSs) are widely used in high-accuracy navigation because of their ability to restrain the horizontal axis errors of the inertial measurement unit (IMU). The IMU errors, especially the biases, should be constant during each rotation cycle that is to be modulated and restrained. However, the temperature field, consisting of the environment temperature and the power heating of single-axis RINS, affects the IMU performance and changes the biases over time. To improve the precision of single-axis RINS, the change of IMU biases caused by the temperature should be calibrated accurately. The traditional thermal calibration model consists of the temperature and temperature change rate, which does not reflect the complex temperature field of single-axis RINS. This paper proposed a multiple regression method with a temperature gradient in the model, and in order to describe the complex temperature field thoroughly, a BP neural network method is proposed with consideration of the coupled items of the temperature variables. Experiments show that the proposed methods outperform the traditional calibration method. The navigation accuracy of single-axis RINS can be improved by up to 47.41% in lab conditions and 65.11% in the moving vehicle experiment, respectively.
The Strapdown inertial navigation system (SINS) requires the precise attitude, whereas the deflection of the vertical (DOV) is normally ignored in alignment. To solve the issue of orientation and position errors caused by DOV, a novel DOV calculation method, estimated by misalignment angles based on single-axis rotating modulation, is proposed. The theoretical limit error equation of attitude angle, affected by the coupling of inertial measurement units (IMU) errors and DOV, has been specifically derived based on the inertial frame alignment theory. It is pointed out that the DOV components directly affect the values of misalignment angles, coupling with horizontal accelerometer errors. Moreover, the specific process of combining coarse alignment of inertial frame and fine alignment of Kalman filter method is presented. Finally, the experiment analysis validates the performance of the proposed method and correctness of the theoretical analysis, where the estimation accuracies of DOV components are 0.349′′ and 0.479′′ respectively.
At near-vertical position, the system error is a major factor lowing the attitude accuracy in the attitude determination system, and correction technology is often used to compensate all kinds of system errors. First, the absolute errors of the computed attitude angle including the measurement error and the correction error are analyzed, and the correction error caused by the correction matrix is emphatically derived and discussed. Then a novel balance correction method with a non-unit correction matrix is proposed and verified theoretically. Finally, an inertial measurement unit (IMU) is tested for near-vertical position and corrected with the conventional unit matrix and the proposed balance correction. Experimental results suggest that the balance correction under near-vertical position can enhance the accuracies of the attitude angles over four times than those with the conventional correction.
