Star identification robust to angular rates and false objects with rolling shutter compensation

In this paper, a laboratory model is designed to evaluate the performance of star tracker algorithms for attitude determination of a satellite. Star tracker is the most accurate attitude sensor that determines satellite direction by applying centroiding algorithm, star identification and attitude determination. To utilize such algorithms, first, high quality of star images are needed which should be provided through the star tracker camera. Then, such images are given to processors and it determines the attitude of camera and satellite in three axes based on mentioned algorithms. First, in preliminary design, we define important star tracker parameters, like accuracy, detector, processor and field of view. In this paper, we have considered the range accuracy in yaw/pitch axis less than 20 arcsec and for roll axis less than 100 arcsec. To improve the attitude determination accuracy, we have applied an adaptive structure in centroiding algorithm, as only brightness stars are selected and identification algorithm is done based on them. Another important parameter is speed of identification algorithm which is handled by an ARM processor and improving pyramid algorithm, we reached less than 25 ms. Duo to this time, updating rate would be desired. Also knowing the coordination of bore sight direction that is distance between focal lens and imager is another important parameter that affects the accuracy of attitude and by ground calibration of camera, this parameter could be estimated carefully. Finally, implementation results on real images that are captured by a star tracker demonstrate optimum performance of algorithms.

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 Trackers are often the most accurate instrument in an Attitude Determination and Control Systems, but often present a slow update rate, requiring additional sensor and sensor fusion algorithms to provide a smoother and faster output. However, the available rate gyros are either noisy, or expensive and heavy. The proposed work investigates the feasibility of high-speed star trackers with modern optics, sensors, and computing systems. Firstly, we investigate the sensitivity of an optoelectrical acquisition system stimulated by dim stars, secondly, we propose and evaluate an algorithm designed to operate at high speed and to be compatible with an Field-Programmable Gate Array implementation, before evaluating the performance of the implementation on FPGA. Finally, we debate the usability of such a system, both in terms of compatibility with a mission and CubeSat ecosystems, and in terms of performance. As a result, aside from removing the need for a rate gyro, Attitude Determination and Control Systems overall pointing performances can be increased. The proposed attitude determination system achieved a 0.001° accuracy, with a 99.1% sky coverage and an ability to reject false-positive while performing a single-frame lost-in-space star identification at a 50 Hz update rate with a total delay of 19 ms, including 13 ms.

Star identification can be accomplished by several different available algorithms that identify the stars observed by a star tracker. However, efficiency and reliability remain key issues and the availability of new active pixel cameras requires new approaches. Two novel algorithms for recursive mode star identification are presented here. The first approach is derived by the spherical polygon search (SP-search) algorithm, it was used to access all the cataloged stars observed by the sensor field-of-view (FOV) and recursively add/remove candidate cataloged stars according to the predicted image motion induced by camera attitude dynamics. Star identification is then accomplished by a star pattern matching technique which identifies the observed stars in the reference catalog. The second method uses star neighborhood information and a catalog neighborhood pointer matrix to access the star catalog. In the recursive star identification process, and under the assumption of "slow" attitude dynamics, only the stars in the neighborhood of previously identified stars are considered for star identification in the succeeding frames. Numerical tests are performed to validate the absolute and relative efficiency of the proposed methods.

The star tracker is widely used in attitude control systems of spacecraft for attitude measurement. The attitude update rate of a star tracker is important to guarantee the attitude control performance. In this paper, we propose a novel approach to improve the attitude update rate of a star tracker. The electronic Rolling Shutter (RS) imaging mode of the complementary metal-oxide semiconductor (CMOS) image sensor in the star tracker is applied to acquire star images in which the star spots are exposed with row-to-row time offsets, thereby reflecting the rotation of star tracker at different times. The attitude estimation method with a single star spot is developed to realize the multiple attitude updates by a star image, so as to reach a high update rate. The simulation and experiment are performed to verify the proposed approaches. The test results demonstrate that the proposed approach is effective and the attitude update rate of a star tracker is increased significantly.

After the successfully launched hypersonic SHarp Edge Flight EXperiment (SHEFEX) in 2005, DLR has scheduled a second re-entry experiment SHEFEX 2 for 2010. The novel flight control system based on steerable canard fins requires a precise knowledge of the inertial spacecraft attitude. For this purpose, a star tracker is to be conceived and integrated in an inertial navigation system, updating the attitude information before re-entry. The developed star tracker is considered to be a low cost and low accuracy sensor that is suitable for the proposed mission and the attitude accuracy requirements. This sensor is based on an off-the-shelf camera and a PC104 computer communicating with the navigation computer. The attitude determination software consists of a processing chain including the camera control, the image processing, the star identification and the attitude estimation. The emphasis of the work is on developing a simple but robust system. Therefore, different algorithm concepts for each element of the chain have been implemented, tested and compared. Furthermore, star image simulation software has been developed, allowing performance and speed tests of the single blocks and the processing chain as a unit. The paper presents the star tracker system, details some newly developed parts and discusses the test results.

Italian Space Agency has funded, as one of the possible Italian experiments on board the International Space Station, the development of a new star tracker, called StarNav III, which observes the sky by means of three orthogonal fields of view and focuses all the star images onto a single CCD/CMOS imager. The main characteristics of this sensor are a high gain in the attitude accuracy estimation and in the operating time. These benefits cost, however, in terms of hardware and software design which are, in turn, more complex. The completed StarNav III feasibility study has output a variety of new software approaches (as, for instance, for acquisition, centroiding, star identification, and mirror misalignment), most of which can directly be applied to almost all of the existing CCD/CMOS star trackers. This paper shows the principal aspects of the relevant feasibility study.

This research is aimed to improve star tracker performance in presence of dynamic conditions. It offers an assessment of various image thresholding and centroiding algorithms to improve star tracker centroiding accuracy at moderate slew rates (< 10 0=s). Star trackers generally have arc-second accuracy in stationary conditions, however their accuracy degrades as slew rate increases. In dynamic conditions, blur effects add to the challenges of star detection. This work presents an image processing algorithm for star images that preserves star tracker detection accuracy and is able to detect dim stars up to slew rates less than 10 0=s. A number of algorithms from literature were evaluated and their performance in motion and simulations were measured. The primary performance metrics are false positive ratio, and false negative ratio of star pixels. This Work introduced a new algorithm for star acquisition in moderate slew rates that combines positive features of existing algorithms.

Traditionally, camera-based tracking approaches have treated rolling shutter and radial distortion as imaging artifacts that have to be overcome and corrected for in order to apply standard camera models and scene reconstruction methods. In this paper, we introduce a novel multi-camera tracking approach that for the first time jointly leverages the information introduced by rolling shutter and radial distortion as a feature to achieve superior performance with respect to high-frequency camera pose estimation. In particular, our system is capable of attaining high tracking rates that were previously unachievable. Our approach explicitly leverages rolling shutter capture and radial distortion to process individual rows, rather than entire image frames, for accurate camera motion estimation. We estimate a per-row 6 DoF pose of a rolling shutter camera by tracking multiple points on a radially distorted row whose rays span a curved surface in 3D space. Although tracking systems for rolling shutter cameras exist, we are the first to leverage radial distortion to measure a per-row pose - enabling us to use less than half the number of cameras required by the previous state of the art. We validate our system on both synthetic and real imagery.

An optical flow-based technique is proposed to estimate spacecraft angular velocity based on sequences of star-field images. It does not require star identification and can be thus used to also deliver angular rate information when attitude determination is not possible, as during platform de tumbling or slewing. Region-based optical flow calculation is carried out on successive star images preprocessed to remove background. Sensor calibration parameters, Poisson equation, and a least-squares method are then used to estimate the angular velocity vector components in the sensor rotating frame. A theoretical error budget is developed to estimate the expected angular rate accuracy as a function of camera parameters and star distribution in the field of view. The effectiveness of the proposed technique is tested by using star field scenes generated by a hardware-in-the-loop testing facility and acquired by a commercial-off-the shelf camera sensor. Simulated cases comprise rotations at different rates. Experimental results are presented which are consistent with theoretical estimates. In particular, very accurate angular velocity estimates are generated at lower slew rates, while in all cases the achievable accuracy in the estimation of the angular velocity component along boresight is about one order of magnitude worse than the other two components.

Noncontact measurement for rotational motion has advantages over the traditional method which measures rotational motion by means of installing some devices on the object, such as a rotary encoder. Cameras can be employed as remote monitoring or inspecting sensors to measure the angular velocity of a propeller because of their commonplace availability, simplicity, and potentially low cost. A defect of the measurement with cameras is to process the massive data generated by cameras. In order to reduce the collected data from the camera, a camera using ERS (electronic rolling shutter) is applied to measure angular velocities which are higher than the speed of the camera. The effect of rolling shutter can induce geometric distortion in the image, when the propeller rotates during capturing an image. In order to reveal the relationship between the angular velocity and the image distortion, a rotation model has been established. The proposed method was applied to measure the angular velocities of the two-blade propeller and the multiblade propeller. The experimental results showed that this method could detect the angular velocities which were higher than the camera speed, and the accuracy was acceptable.

The concept of software-defined satellite (SDS) enables in-orbit software reconfiguration and payload virtualization, significantly enhancing the configurability and cross-mission reusability of imaging payloads. However, this flexibility also exposes traditional star identification methods-which depend on fixed intrinsic camera parameters-to severe robustness limitations when dealing with multiple cameras and varying operational conditions. Therefore, a universal and adaptive star identification algorithm is essential to ensure stable and precise attitude determination within the SDS architecture. To this end, this paper proposes a parameter-independent star identification algorithm based on topological invariance features. The method integrates a topological invariant feature coordinate system with a self-organizing map (SOM) neural network, enabling consistent recognition across diverse payload configurations and observation scenarios. Extensive experiments under conditions such as stellar position noise, false-star noise, missing-star noise, focal length variation, and dynamic fields of view demonstrate that the proposed algorithm consistently outperforms three benchmark methods and maintains stable accuracy. These results confirm that the proposed method not only aligns with the SDS philosophy of hardware-software decoupling but also provides a necessary algorithmic foundation for its flexible, reconfigurable, and multi-payload attitude determination framework.

A star sensor is an embedded system used in modern spacecraft for estimating the orientation of the spacecraft. Star trackers capture image of star in the sky, process them and gave highly accurate attitude in all 3 axis. Basically a star tracker is an electronic camera connected to a microcomputer. First generation star trackers are characterized by acquiring and processing few stars information to estimate attitude with limited software modules. The availability of space qualified microcomputers enables generation shift in the star trackers development for attitude determination onboard. Laboratory for Electro-Optics Systems (LEOS) is actively involved in design and development of indigenous star trackers for different ISRO. Current star trackers employs traditional method of acquiring and processing star image and don't meet the many spacecraft requirements in terms of number of stars tracking, accuracy and update rate. In order to meet the current generation spacecraft requirements, LEOS has designed and developed second generation star trackers which are characterized by low weight, volume and power. These sensors are based on ERC-32 processor, here after referred as Mark-II sensor. The essential features expected from onboard software are robustness in operations, run-time and ability to give solutions especially during satellite injection with high angular rate. This paper presents the details of state-of-art software designed and developed for these star trackers to provide high accuracy and higher bandwidth with existing hardware limitations even with harsh space environment with limited resources and constraints.

The requirements, technical approach, and key features of the attitude determination system (ADS) being developed for the Space Station Freedom are described. Use of current technology provides new capabilities for all attitude autonomous operation and rapid determination of attitude in a debris-filled environment. The ADS is implemented using star trackers with fixed mosaic array detectors and inertial sensors based on laser gyro technology. Star catalog characteristics, star identification techniques, the functional implementation of the ADS system, and the results of preliminary covariance performance analyses are presented. Covariance analysis indicates that the stringent accuracy requirements of the Space Station can be met with the baseline system. The automated ADS mechanization provides rapid attitude acquisition from any orientation where stars are visible; astronaut intervention is not required. The inertial sensors and the star trackers are on-orbit replaceable, are highly reliable, and promise long-life operation. >

The eLine10k is a fast-frame, 64-channel readout ASIC for SLAC Linac Coherent Light Source (LCLS) detectors. The circuit has been designed to integrate the charge from high-capacitance 2D sensors with rolling shutter and ID strip sensors. It is suitable for applications requiring large input signal range, on the order of 10 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">4</sup> photons/pixel/pulse at 8keV (22Me <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-</sup> ), and a resolution of half a photon FWHM (500e <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-</sup> r.m.s). 2D sensors with a rolling shutter like the X-ray Active Matrix Pixel Sensor (XAMPS), for which the ASIC has been optimized, present several pixels which are bussed on the same readout line. Large input capacitance to each channel is expected leading to stringent noise optimization requirements. The large required number of pixels per channel, and the fixed LCLS beam period impose limitations on the time available for the readout of each single pixel. Giving the periodic nature of the LCLS beam, the ASIC developed for this application is a time-variant system, providing low-noise charge integration, filtering and correlated double-sampling, and a processing speed up to 500k pixel/s on each channel. To cope with the large input dynamic range, a charge pump scheme has been implemented using a synchronous zero-balance measurement method. It provides on-chip 4-bit coarse digital conversion of the integrated charge. The residual charge is sampled using correlated double sampling into an analog memory, multiplexed and measured with the required resolution using an external ADC. In this paper, the ASIC architecture and performance of the final release are presented.