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.
Star trackers measures the attitude of spacecraft by matching the centroid coordinates extracted from star image with the star database. However, dim stars, fake stars, noise and irregularly shaped star spots interfere with star extraction. In order to solve these problems, a new star centroid extraction algorithm based on adjacent branch decision marker is proposed in this paper. The first step is to use labels to encode the pixel of star points which are processed by double threshold segmentation; the second step is to judge the validity of the labels by using the adjacent branch decision marker and output them. Compared with the traditional connected area segmentation method, the algorithm can solve the influence of irregular shape star points on Star Information segmentation, and two kinds of threshold segmentation method can effectively eliminate the influence of background on star point extraction. The experimental results show that the algorithm has high precision and speed of star centroid extraction, and the resource cost is low. Compared with other methods, this method has stronger anti background interference ability and better robustness.
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.
Former studies have proved that the attitude error in a single-axis rotation INS/GPS integrated system tracks the high frequency component of the deflections of the vertical (DOV) with a fixed delay and tracking error. This paper analyses the influence of the nominal process noise covariance matrix Q on the tracking error as well as the response delay, and proposed a Q-adjusting technique to obtain the attitude error which can track the DOV better. Simulation results show that different settings of Q lead to different response delay and tracking error; there exists optimal Q which leads to a minimum tracking error and a comparatively short response delay; for systems with different accuracy, different Q-adjusting strategy should be adopted. In this way, the DOV estimation accuracy of using the attitude error as the observation can be improved. According to the simulation results, the DOV estimation accuracy after using the Q-adjusting technique is improved by approximate 23% and 33% respectively compared to that of the Earth Model EGM2008 and the direct attitude difference method.
Deflections of the vertical (DOV) are normally ignored in the gravity compensation procedure, which become one of the primary error sources in inertial navigation. In a single-axis rotation INS/GPS system, bias of the gyro and the accelerometer can be ignored, the attitude error is mainly affected by DOV. In this paper, the ideal system assumption is abandoned and the influence of DOV on the attitude is comprehensively discussed, which can be divided into two parts i.e. the direct influence and the indirect influence. The attitude error tracks the DOV along the trajectory belongs to the former. A relatively fixed delay between the attitude error and the DOV belongs to the latter. The delay is essentially induced by the weak observability of the system to the violent DOV. Factors which affect the delay are carefully analyzed. The simulation results show that the delay is mainly affected by accuracies of the inertial sensors and the GPS. It decreases with the GPS accuracy increasing, but increases with the inertial sensor accuracy increasing. The process noise covariance matrix Q plays an important role. With analysis of the characteristics of the delay, influence of the DOV on attitude is studied further, which is necessary for the attitude correction in future.
Star trackers are beyond dispute the most accuracy absolute attitude determination sensors which are widely applied
in spacecraft, satellites, rockets, etc. High precision autonomous star tracker has accuracy better than one arc second and
generally resulting in a low update rate less than 10Hz. Typically, an autonomous star tracker consist two physically
independent components, the optical head and the associated processing electronic system. High accuracy attitude is
obtained through their cooperation. Basic principles of star navigation and components of a star tracker will be
introduced. Star trackers used to be with big body size, heavy mass, high power consumption and complicated structure but
with low accuracy. The state-of-the-art development will decrease the power consumption and mass of autonomous star
trackers significantly while increase update rate and improve dynamic accuracy and system robustness. Advance of
different generations of star trackers will be reviewed here. The accuracy performance of the star tracker depends on the
sensitivity to the starlight of the image sensor, the star detection threshold, the field of view (FOV), the number of stars in
the FOV, the accuracy of the star centroid, the dynamic maneuvering, the calibration and etc. Star centroid is a key
procedure and contributes much more to the final performance of a star track. Accuracy degradation will occur when the
carrier of the star track is in the state of high dynamic maneuvering. Hardware design and algorithms remedies have to
been adopted to reduce the degradation effects. Detailed discussion of accuracy performance will be presented.
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