In the field of autonomous navigation, the accuracy of the inertial navigation system (INS) heavily relies on the initial position information. Typically, this information is obtained from the global navigation satellite system(GNSS) or celestial navigation system (CNS). In this study, we present a novel approach for acquiring precise initial position information using the INS/CNS integration system. This method enables the independent determination of the carrier’s high-precision initial position in a static state. The experiment results show that the latitude error is 48.35m and the longitude error is -55.80m of this approach, which provide compelling evidence for the effectiveness of the proposed celestial positioning method.
Star tracker is a high-precision attitude sensor that obtains carrier attitude information by processing star images, and star centroid extraction is an important step in the work of star tracker. This paper proposes a star centroid extraction algorithm based on Field Programmable Gate Array (FPGA), which consists of six parts: threshold segmentation, 3X3 matrix generation, pixel weight calculation, connected component labeling, star centroid weight summation, and divider IP core. In order to verify the accuracy of FPGA centroid extraction algorithm, three sets of experiments were conducted. Firstly, generate a noise-free simulated star image, and compare the extraction result which was done on the ModelSim platform with the setting real values to analyze the FPGA centroid extraction accuracy under ideal situation. Secondly, Gaussian noise was added to the simulated star image, and analyzed the FPGA extraction accuracy under noisy situation. Finally, a real star image is extracted on Matlab and ModelSim, respectively, and take the Matlab extraction result as a reference value to evaluate the FPGA extraction accuracy. Simulation and experimental results show that the proposed algorithm has high extraction accuracy ,which can meet the working requirements of star tracker.
Triangle star identification algorithm is the most widely used and most mature star pattern recognition algorithms. When the number of guide star is relatively huge and the capacity of guide star catalog is relatively large, with the result that the complexity of triangle star identification algorithm increases, the time of star pattern recognition becomes longer, and even the storage space occupied by the algorithm becomes larger. So it is difficult to realize the rapid and effective star identification in star map. In order to improve the efficiency of star identification algorithm and shorten the time of star recognition, it is proposed that a star identification algorithm used on the data structure of hash map and based on the triangle algorithm. The first thing is to make the guide star catalog. Then, all the angular distance values d ijm (0 < i < j ≤ N) of the brightest N observed stars in an observed star image and their corresponding star angular distance sets are calculated, and the triangle features, namely angular distance values, are stored in the hash map. In this algorithm, each triangle feature is mapped to an integer, and the hash map of all triangle features is set to reduce the computational complexity of triangle pattern matching, decrease the number of star angular distance matching, and greatly shorten the time of star image recognition. Simulation results show that the star image recognition algorithm based on hash map has better computational complexity and efficiency of performance than traditional triangle algorithm.
Hull deformation is the fundamental reason that restricts the establishment of a unified attitude reference for large ships. The causes and types of hull deformation are introduced. Hull deformation measurement includes the yawing angle, the pitching angle, and the rolling angle. The rolling angle is more difficult to measure than the pitching angle and the yawing angle. Optical measurement methods and stress measurement methods are introduced to measure the rolling angle. Optical measurement methods mainly include the grating method, camera measurement method, dual light sources, and dual CCD method, polarized light energy measurement method, double-frequency polarized method, large steel reference method, etc. Stress measurement methods mainly include the hydraulic stress method and the strain sensor measurement method. The inertial matching measurement method which can measure the pitching angle, yawing angle, and rolling angle simultaneously is introduced. The urgent problems faced by measuring hull deformation and their developments are discussed.
Due to the harsh working environment and lacking of external information, after a long period of work, the performance of the local reference inertial device will deteriorate, which will cause the navigation information to fail to meet the requirements of user equipment. In this paper, a local reference dynamic calibration method based on hull deformation compensation is proposed. Firstly, eliminate the coordinate system misalignment between the main inertial navigation system (MINS) and the local reference. Furthermore, a Kalman filter is designed to calibrate the bias errors of the local reference laser gyro and accelerometer based on the high-precision navigation information of the MINS. The simulation results show that after accurate hull deformation compensation, the local reference laser gyro bias error estimation accuracy is better than 0.002°/h , accelerometer bias error estimation accuracy is better than 1μg ,which provides an effective solution for local reference marine dynamic calibration
The star tracker should be accurately calibrated in order to achieve high precision. The calibration procedure can be well performed in the laboratory with the aids of a high-precision two-axis rotary table. Hence, the calibration accuracy is heavily relied on the performance of the rotary table. In this paper, use a collimator to emit starlight, then the influence of the rotary table error on the calibration result of the star tracker is analyzed in detail. The simulation and experimental results show that the accuracy of the rotary table has a great influence on the laboratory calibration results. When the rotary table error is 2 '' Gaussian error, the attitude angle calibration error is within 3 '' . The intrinsic parameters calibration accuracy are as follows, the principal point error is within 5 pixels, the focal length error is 0.001mm, less than 20% deviation of tangential distortion, radial distortion within 120% deviation. Except the declination error and the fixed angle along the optical axis error is within 5 '' , the remaining extrinsic parameters have relatively large errors, but they have limited influence on the calibration results, for the star tracker calibration only focuses on the accuracy of the intrinsic parameters. The reprojection error of the star centroid is in a few hundredths of a pixel, and the corresponding angle error is 3 ''~5 '' , which can satisfy the high-precision attitude measurement of the star tracker.
The combination of the strap-down inertial navigation system(SINS) and the celestial navigation system(CNS) is one of the popular measures to constitute the integrated navigation system. A star sensor(SS) is used as a precise attitude determination device in CNS. To solve the problem that the star image obtained by SS is motion-blurred under dynamic conditions, the attitude-correlated frames(ACF) approach is presented and the star sensor which works based on ACF approach is named ACFSS. Depending on the ACF approach, a novel device-level SINS/ACFSS deeply integrated navigation method is proposed in this paper. Feedback to the ACF process from the error of the gyro is one of the typical characters of the SINS/CNS deeply integrated navigation method. Herein, simulation results have verified its validity and efficiency in improving the accuracy of gyro and it can be proved that this method is feasible.
The Strap-Down Inertial Navigation System (SINS) is a widely used navigation system. The combination of SINS and the Celestial Navigation System (CNS) is one of the popular measures to constitute the integrated navigation system. A Star Sensor (SS) is used as a precise attitude determination device in CNS. To solve the problem that the star image obtained by SS under dynamic conditions is motion-blurred, the Attitude Correlated Frames (ACF) is presented and the star sensor which works based on ACF approach is named ACFSS. Depending on the ACF approach, a novel device-level SINS/ACFSS deeply integrated navigation method is proposed in this paper. Feedback to the ACF process from the error of the gyro is one of the typical characters of the SINS/CNS deeply integrated navigation method. Herein, simulation results have verified its validity and efficiency in improving the accuracy of gyro and it can be proved that this method is feasible in theory.
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