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Radiation effects in star trackers can cause malfunctions that may lead to the loss of communication with the satellite. This paper presents a scheme to protect star tracker images stored in memory against single event upsets (SEUs). Fault injection and resource utilization reports show that, with the protection technique, 99.98% of the SEUs can be corrected using 37% less memory space than single error correction Hamming codes. The remaining 0.02% has a negligible effect in the star identification algorithm. [ABSTRACT FROM AUTHOR]

This paper presents a novel star identification algorithm for a “lost-in-space” mode star tracker. The Spearman-correlation approach provides reliable recognition even when the captured images are swayed and biased from the onboard star pattern database. The hamming distance approach provides a shortlisted list of star IDs. Thus, the proposed combination of hamming distance and Spearman correlation provides a reliable and fast recognition. The achievable performance is evaluated by testing on simulated and real images. [ABSTRACT FROM AUTHOR]

Images are commonly used for spacecraft navigation. When close to the observed body it is often advantageous to perform such image-based navigation with observations of landmarks. This work demonstrates that it is possible to solve the initial orbit determination (IOD) problem using only observations of unknown landmarks if the spacecraft is assumed to be orbiting an ellipsoidal central body of known shape. Further, the solution developed here is noniterative and is based purely on geometric arguments. Example autonomous IOD results using only unknown landmarks are shown for a spacecraft in a circular Mars orbit and an elliptical Earth orbit. [ABSTRACT FROM AUTHOR]

The main objective of this paper is to apply a particle image velocimetry technique accompanied by Delaunay triangulation and spatial angles to consecutive images of star tracker in order to estimate the angular velocity of spacecraft. This method is independent of star identification or attitude matrix and can be performed parallel to conventional star tracker algorithms. It is computationally light and consumes a reasonable time to perform. An interrogation window containing two or more stars in the first image is selected and based on the peak of normalized cross correlation matrix, the same window in the second image is matched. In order to make sure that the matched windows are indeed the same, local recognition features, such as spatial angles for windows with two stars and Delaunay triangle planar angles for three or more stars, are compared. When matched, window center angular displacement is calculated in a fixed imaging time interval, and eventually, an angular rate is estimated. In order to evaluate the performance of the proposed method, Monte Carlo simulation of random night sky images is used. It is shown that for angular rates, about 1°/s accuracies better than 7e−5°/s are achieved. Accuracy decreases to 1e−3°/s for the rates of about 12°/s in 0.1-s time interval. [ABSTRACT FROM AUTHOR]

Modern star trackers are based on photodetector arrays such as CCD or CMOS arrays. The accuracy of commercially available devices is ~1-3 arcseconds. However, the development of the space industry calls for higher orientation accuracies, which are needed in laser space communications, monitoring of near-Earth space and space debris, high-precision global mapping, and remote sensing of the Earth. The problems associated with enhancing the accuracy of modern star trackers are discussed. [ABSTRACT FROM AUTHOR]

Since 2003 the European Space Agency's roadmap for star tracker CMOS APS (active pixel) image sensors has included developments to integrate significant logic functionality with the pixel array, aiming at an imaging system-on-chip. FaintStar (FS) will be the first commercially available product resulting from these activities. FaintStar is being developed by ams Sensors Belgium (formerly CMOSIS) in two phases. Phase 1 served to specify, design, manufacture, and characterise a prototype chip, informally named FaintStar1 (FS1), the subject of this paper. FaintStar is a one megapixel image sensor with 10 µm pixels and rolling shutter. All interactions with the user are over a single 80 Mb/s SpaceWire link. FaintStar offers various readout modes (full frame, windowed, windowed with dual rolling shutter, etc.). The chip has 'pixels-to-centroids' processing, including transfer curve linearisation, bad pixel replacement, background image estimation and suppression, spike filtering, bright object extraction, and photometric barycentre calculation. The algorithms used are generic, i.e., non-reliant on third-party IP, yet highly user-configurable. Data-compressed or raw image output is also supported. The device has been developed for star trackers mainly, although applications such as high-accuracy sun sensing, and navigation, rendezvous, or rover cameras are also served. The prototype chip exceeds its expectations. This article starts with an overview of the FS1 design and reports on the Phase 1 characterisation results, including electro-optical performance, proton displacement damage, total dose, and single event radiation effects. Started end of 2017, the project's Phase 2 entails minor design refinements, creating FaintStar2 (FS2), its manufacturing, and then a formal evaluation campaign. After this, the sensor will be offered as a commercial off-the-shelf product. [ABSTRACT FROM AUTHOR]

Due to the inadequacies of the speed of star detection and centroid calculation (SDCC), the applications of high-resolution and high-frame-rate image sensors are greatly limited in star trackers, restricting the performance of the star trackers. To resolve this problem, a novel distributed parallel super-block-based SDCC method is proposed in this paper. In contrast to the previous SDCC methods, the proposed method divides the star images into several sub-images and processes these sub-images in parallel. Then, by using a super-block-based method and a distributed shared memory-based method to process the stars in sub-images (sub-stars) and in adjacent sub-images (boundary stars), respectively, the position information of all the stars are detected during the parallel scan of the sub-images. The proposed method exhibits a speed that is up to $4 \,\, \times $ M times faster than the previous SDCC methods in processing the star images that are divided into M sub-images. Experimental results demonstrate that the proposed method is correct and effective. It is applicable to the use of most high-performance image sensors and resolves the performance limitation of star trackers to achieve better attitude accuracy and attitude update rate. [ABSTRACT FROM AUTHOR]

The integration of a star tracker and gyroscope units (GUs) can take full advantage of the benefits of each, and provide continuous and accurate attitude information with a high update rate. The systematic error calibration of the integrated system is a crucial step to guarantee its attitude accuracy. In this paper, a comprehensive calibration method for the star tracker and GUs integrated system is proposed from a global perspective. Firstly, the observation model of the predicted star centroid error (PSCE) with respect to the systematic errors including the star tracker intrinsic parameter errors, GUs errors and fixed angle errors is accurately established. Then, the systematic errors are modeled by a series of differential equations, based on which the state-space model is established. Finally, the systematic errors are decoupled and estimated by a Kalman filter according to the established state-space model and observation model. The coupling between the errors of the principal point and subcomponents of the fixed angles (i.e., ψx and ψy) is analysed. Both simulations and experiments indicate that the proposed method is effective at estimating the systematic errors of the star tracker and GUs integrated system with high accuracy and robustness with respect to different star centroid accuracies and gyroscope noise levels. [ABSTRACT FROM AUTHOR]

A method for validating the calibration parameters of the six accelerometers on board the Gravity field and steady-state Ocean Circulation Explorer (GOCE) from star tracker observations that was originally tested by an end-to-end simulation, has been updated and applied to real data from GOCE. It is shown that the method provides estimates of scale factors for all three axes of the six GOCE accelerometers that are consistent at a level significantly better than 0.01 compared to the a priori calibrated value of 1. In addition, relative accelerometer biases and drift terms were estimated consistent with values obtained by precise orbit determination, where the first GOCE accelerometer served as reference. The calibration results clearly reveal the different behavior of the sensitive and less-sensitive accelerometer axes. [ABSTRACT FROM AUTHOR]

Fast tracking algorithm discussed in this paper is applied to star trackers for improving the performance of star identification. Space Robotics Laboratory (SRL) in Tohoku University has developed star trackers for micro-satellites so far. Since it has only a lost-in-space algorithm for star identification, the attitude update rate is limited up to 1 Hz. It was implemented to the Philippines' 50 kg-class micro-satellite "DIWATA-1" released from the International Space Station on April 2016. Although on-orbit evaluation showed good results enough to output attitude autonomously, the performance of continuous attitude determination was worse than expected. Since quite a high access frequency of star catalog is required, timeout of the process for attitude calculation occurs frequently even if update rate is 1 Hz. Insufficient ground evaluation before launch is also one of the causes of operation failure. Tracking algorithm helps to calculate latest attitude faster than conventional methods by feeding back the previous attitude information. This algorithm includes two additional processes. First, future star positions on the image frame can be predicted according to the previous attitude and pre-identified star information. The sensor can find corresponding latest centroids compared to predicted star positions. Second, un-identified stars on the camera field of view (FOV) can be detected by referring to the star neighborhood catalog, which includes the list of some adjacent star IDs against each reference star. PC simulation shows that continuous attitude determination works effectively by keeping low catalog access frequency. The proposed algorithm is implemented to the real hardware. Then, ground evaluation is conducted using star simulator environment and satellite dynamics simulator. The result demonstrates that the processing speed in real situation becomes about 70 times faster compared to the previous method and it is successful to obtain much more stable 1 Hz attitude output. [ABSTRACT FROM AUTHOR]

In this paper, a novel guide star catalog generation algorithm is presented, which is a crucial part of an advanced star tracker design since the performance and reliability of star identification and attitude determination depend on the guide star selection. First, we propose an analytical method to estimate the stellar instrument magnitude and characterize the associated errors. Those stars whose instrument magnitudes are higher than the star tracker sensitivity constitute the original catalog. Then, the probability model of each star in the original catalog for attitude determination is established as the function of the field of view (FOV), the brightness accuracy, and the mean number of stars in FOV based on the brightness and uniformity principles, and the stars with larger probability are selected as guide stars. The accuracy of photometry method is validated by estimating the Hipparcos catalog instrument magnitude and comparing them with actual data. The efficiency of guide star selection algorithm is demonstrated by generating guide star catalog for a star tracker with a 16 ^\circ \times 16 ^\circ FOV. [ABSTRACT FROM PUBLISHER]

A star tracker provides the most accurate attitude solution in terms of arc seconds compared to the other existing attitude sensors. When no prior attitude information is available, it operates in “Lost-In-Space (LIS)” mode. Star pattern recognition, also known as star identification algorithm, forms the most crucial part of a star tracker in the LIS mode. Recognition reliability and speed are the two most important parameters of a star pattern recognition technique. In this paper, a novel star identification algorithm with star ID shortlisting is proposed. Firstly, the star IDs are shortlisted based on worst-case patch mismatch, and later stars are identified in the image by an initial match confirmed with a running sequential angular match technique. The proposed idea is tested on 16,200 simulated star images having magnitude uncertainty, noise stars, positional deviation, and varying size of the field of view. The proposed idea is also benchmarked with the state-of-the-art star pattern recognition techniques. Finally, the real-time performance of the proposed technique is tested on the 3104 real star images captured by a star tracker SST-20S currently mounted on a satellite. The proposed technique can achieve an identification accuracy of 98% and takes only 8.2 ms for identification on real images. Simulation and real-time results depict that the proposed technique is highly robust and achieves a high speed of identification suitable for actual space applications. [ABSTRACT FROM AUTHOR]

We investigate the precision in the readings of the star tracker BOKZ-M60 obtained in the dynamic field testbed of the Space Research Institute of the Russian Academy of Sciences (SRI RAS). The testbed features a mobile platform, on which a star tracker is mounted, which scans the starry sky. The platform movement is controlled by a PC, however, the values of the rotation angles in the platform hinges are not known with the desired degree of accuracy. In testing star trackers, the error in the known platform orientation must be around 1″, which corresponds to an error in determining the linear coordinates of the platform reference points of less than 3 μm. It is difficult and expensive to organize outside measurements of the movement of a mobile object with such accuracy. For this reason, the following accuracy estimation scheme is used. We consider comparatively long series of the determined orientation parameters obtained by the tracker in the testbed. With the help of a suitable mathematical model, a detailed reconstruction of the actual rotational motion of the tracker is performed based on these measurements. In this reconstruction, the residuals in the tracker readings are calculated. Based on the analysis of the residuals, conclusions are drawn about the accuracy of the tracker. As it turns out, the accuracy of determining the optical axis of the tracker lens depends on the angular velocity of the platform and lies in the range from 2″ to 25″ [ABSTRACT FROM AUTHOR]

Star trackers are currently the most accurate spacecraft attitude sensors. As a result, they are widely used in remote sensing satellites. Since traditional charge-coupled device (CCD)-based star trackers have a limited sensitivity range and dynamic range, the matching process for a star tracker is typically not very sensitive to star brightness. For active pixel sensor (APS) star trackers, the intensity of an imaged star is valuable information that can be used in star identification process. In this paper an improved brightness referenced star identification algorithm is presented. This algorithm utilizes the k-vector search theory and adds imaged stars’ intensities to narrow the search scope and therefore increase the efficiency of the matching process. Based on different imaging conditions (slew, bright bodies, etc.) the developed matching algorithm operates in one of two identification modes: a three-star mode, and a four-star mode. If the reference bright stars (the stars brighter than three magnitude) show up, the algorithm runs the three-star mode and efficiency is further improved. The proposed method was compared with other two distinctive methods the pyramid and geometric voting methods. All three methods were tested with simulation data and actual in orbit data from the APS star tracker of ZY-3. Using a catalog composed of 1500 stars, the results show that without false stars the efficiency of this new method is 4~5 times that of the pyramid method and 35~37 times that of the geometric method.

Star identification is one of the most important stages in attitude determination with star trackers. This can be performed using matching algorithms between observed stars and a master star catalogue. The main challenge in this approach is to provide a fast and reliable identification algorithm that is sufficiently robust in different pointing views of the star tracker optical system in the space. In this article, an identification algorithm based on a geometric voting scheme is presented. In this algorithm a pair of stars in the catalogue votes for a pair of stars in the image if angular distance between the stars of both pairs is similar. As angular distance is a symmetric relationship, each of the two catalogue stars votes for each of the image stars. The identity of each star in the image is set to the identity of the catalogue star which cast the most votes. Applying the algorithm in different attitudes and with different optical system parameters shows its high performance in star identification in our simulations.

Under highly dynamic conditions, the star-spots on the image sensor of a star tracker move across many pixels during the exposure time, which will reduce star detection sensitivity and increase star location errors. However, this kind of effect can be compensated well by setting an appropriate exposure time. This paper focuses on how exposure time affects the star tracker under highly dynamic conditions and how to determine the most appropriate exposure time for this case. Firstly, the effect of exposure time on star detection sensitivity is analyzed by establishing the dynamic star-spot imaging model. Then the star location error is deduced based on the error analysis of the sub-pixel centroiding algorithm. Combining these analyses, the effect of exposure time on attitude accuracy is finally determined. Some simulations are carried out to validate these effects, and the results show that there are different optimal exposure times for different angular velocities of a star tracker with a given configuration. In addition, the results of night sky experiments using a real star tracker agree with the simulation results. The summarized regularities in this paper should prove helpful in the system design and dynamic performance evaluation of the highly dynamic star trackers.