High Accuracy Star Sensor Research Articles

Calibration Method for Relativistic Navigation System Using Parallel Q-Learning Extended Kalman Filter.

For the relativistic navigation system where the position and velocity of the spacecraft are determined through the observation of the relativistic perturbations including stellar aberration and starlight gravitational deflection, a novel parallel Q-learning extended Kalman filter (PQEKF) is presented to implement the measurement bias calibration. The relativistic perturbations are extracted from the inter-star angle measurement achieved with a group of high-accuracy star sensors on the spacecraft. Inter-star angle measurement bias caused by the misalignment of the star sensors is one of the main error sources in the relativistic navigation system. In order to suppress the unfavorable effect of measurement bias on navigation performance, the PQEKF is developed to estimate the position and velocity, together with the calibration parameters, where the Q-learning approach is adopted to fine tune the process noise covariance matrix of the filter automatically. The high performance of the presented method is illustrated via numerical simulations in the scenario of medium Earth orbit (MEO) satellite navigation. The simulation results show that, for the considered MEO satellite and the presented PQEKF algorithm, in the case that the inter-star angle measurement accuracy is about 1 mas, after calibration, the positioning accuracy of the relativistic navigation system is less than 300 m.

High-accuracy attitude angle measurement system using laser collimation

We propose a high-precision attitude angle measurement system utilizing laser collimation to rectify environmental errors that significantly impact the precision of high-accuracy star sensors. Environmental factors, primarily temperature variations, can induce shifts in the optical axis of star sensors deployed in orbit, leading to errors in attitude angle measurements. Leveraging the conventional star sensor architecture, we have augmented the system with an additional laser path and a four-quadrant detector (4QD) positioned in the image plane. This setup converts angular deviations of the optical axis into positional shifts of the laser spot, facilitating the measurement of environmental errors. Both simulations and experimental findings demonstrate that the laser collimation system effectively mitigates environmental errors, thereby enhancing the attitude accuracy of the star sensors.

The Optical Reference Error Analysis and Control Method in Ground Validation System of Stellar-Inertial Integration

The authenticity of the Stellar-Inertial integration ground validation system will eventually determine the navigation performance in flight. The optical reference error characteristics remain a crucial but unsolved issue due to the arc-second level accuracy in the ground validation system. The characteristic of the star simulator celestial angle error and the north reference error are discussed and analyzed in detail. A new error control method of the star simulators intersection angle is proposed with the help of the high precision three-axis turntable. The north reference error can be isolated as a certain azimuth bias error in ground validation. The synthesis of all the error sources is performed to give the criterion value of the evaluation accuracy for the ground validation system. Experimental tests confirm that the error analysis and control method are effective. The evaluation accuracy is improved from 10.99 to 4.88 arc-seconds under the condition of remaining the unchanged ground validation system. Meanwhile, such an in ground test system is close to the flight conditions and it can satisfy the stringent requirement for high-accuracy star sensors.

基于星点像重采样的星敏感器高精度质心算法

基于星点像重采样的星敏感器高精度质心算法

An Implicit UKF for Satellite Stellar Refraction Navigation System

The stellar refraction navigation is a type of autonomous celestial navigation method for satellites that uses high-accuracy star sensors to obtain the stellar refraction. The apparent height and the stellar refraction angle are two kinds of measurements for the satellite stellar refraction navigation system. A better navigation performance can be achieved by the stellar refraction angle rather than the refraction apparent height. However, the measurement model of the stellar refraction angle is an implicit function, which needs an implicit filter method. A new implicit unscented Kalman filter (UKF) method is proposed and applied to the satellite stellar refraction navigation system in this paper. The main difference between the classical UKF and the implicit UKF lies in the measurement update. First, since the implicit measurement model can be rearranged into an equation whose one side is zero, the vector of zeros is regarded as the equivalent measurement, and the difference between the predicted measurement and its true value is utilized for updating the predicted state and its covariance matrix. Second, the measurement noise and its covariance matrix are transformed based on the unscented transformation principle. In addition, the implicit UKF is compared with the implicit extended Kalman filter (IEKF), the iterative IEKF, and the UKF. Simulations show that the proposed implicit UKF method can obtain about 19.0% and 17.5% improvements in three-dimensional root mean square position estimation compared to the IEKF and the iterative IEKF, respectively. Although the navigation performance of the UKF is close to the implicit UKFs, the computational time of the implicit UKF is much shorter than the UKFs. In addition, the sensitivities of the four different Kalman filters to the star sensor's faults and the atmosphere perturbation are compared, respectively.

Implicit UKF and its observability analysis of satellite stellar refraction navigation system

Satellite autonomous navigation by stellar refraction is a type of autonomous celestial navigation method that uses high-accuracy star sensors instead of Earth sensors to provide information regarding Earth's horizon. There are two kinds of measurements of satellite stellar refraction navigation. They are the apparent height and the stellar refraction angle. A better navigation performance can be achieved by the stellar refraction angle rather than the refraction apparent height. However, the measurement model of the stellar refraction angle is an implicit function. The traditional UKF and observability analysis methods are not applicable to the system with an implicit measurement model. The implicit UKF (IUKF) and its observability analysis method are proposed in this paper. The equivalent observability matrix is constructed based on the IUKF algorithm. Furthermore, the best scheme for observation of the stellar refraction angle is studied using this new IUKF and its observability analysis. Both the observability analysis and simulation results show that a significant improvement in navigation performance can be achieved by the rotating observation of the stellar refraction angle.

High-accuracy star sensor calibration based on intrinsic and extrinsic parameter decoupling

The performance of star sensors largely depends on the accuracy of the model parameter estimation carried out through calibration. Measurement errors in the calibration data would cause estimated values to deviate from the actual values and couple with one another. Only the intrinsic parameters estimated through calibration are useful to star sensors. Thus, the coupling between estimated intrinsic and extrinsic parameters would affect star sensor accuracy. High-accuracy star sensors are significantly affected by such coupling between the aforementioned parameters. This study investigates the coupling between extrinsic and intrinsic parameters through calibration residual and starlight pointing error. A calibration method based on the decoupling of intrinsic and extrinsic parameters is then proposed. The proposed method uses the invariance of intrinsic parameters and estimates intrinsic parameters through simultaneous optimizations with distinct extrinsic parameters. In both the simulations and the experiment, the decoupling calibration effectively improves the accuracy of the intrinsic parameter estimation. Using the same calibration data, the intrinsic parameters’ estimation precision of a high-accuracy star sensor increased by a range from 50.83 to 86.47%.

Autonomous satellite navigation using starlight refraction angle measurements

An on-board autonomous navigation capability is required to reduce the operation costs and enhance the navigation performance of future satellites. Autonomous navigation by stellar refraction is a type of autonomous celestial navigation method that uses high-accuracy star sensors instead of Earth sensors to provide information regarding Earth’s horizon. In previous studies, the refraction apparent height has typically been used for such navigation. However, the apparent height cannot be measured directly by a star sensor and can only be calculated by the refraction angle and an atmospheric refraction model. Therefore, additional errors are introduced by the uncertainty and nonlinearity of atmospheric refraction models, which result in reduced navigation accuracy and reliability. A new navigation method based on the direct measurement of the refraction angle is proposed to solve this problem. Techniques for the determination of the refraction angle are introduced, and a measurement model for the refraction angle is established. The method is tested and validated by simulations. When the starlight refraction height ranges from 20 to 50km, a positioning accuracy of better than 100m can be achieved for a low-Earth-orbit (LEO) satellite using the refraction angle, while the positioning accuracy of the traditional method using the apparent height is worse than 500m under the same conditions. Furthermore, an analysis of the factors that affect navigation accuracy, including the measurement accuracy of the refraction angle, the number of visible refracted stars per orbit and the installation azimuth of star sensor, is presented. This method is highly recommended for small satellites in particular, as no additional hardware besides two star sensors is required.

A new autonomous celestial navigation method for the lunar rover

A secure and autonomous navigation system is needed for the lunar rover in future lunar missions in case of emergencies. Celestial navigation is a very attractive solution for long distance navigation on the Moon without the need of ground navigation aids. It only uses star altitudes, which are measured by a high accuracy star sensor and inertial measurement unit (IMU) to estimate the position of the rover. The navigational accuracy of this method depends largely on the accuracy of measurements, so the measurement errors have a great impact on the navigational performance. A new autonomous celestial navigation method for the lunar rover is presented in this paper, which uses the augmented state unscented particle filter (ASUPF) to deal with the systematic error and random error in the measurements. The validity and feasibility of this new method is tested and examined by the hardware-in-loop test. A position estimation error within 60 m is obtained. Compared to the conventional method, this method shows better navigation performance and higher adaptability to these measurement errors.