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Infrared Earth sensors are widely used in attitude-determination and control systems of satellites. The main deficiency of static infrared Earth sensors is the requirement of a small field of view (FOV). A typical FOV for a static infrared Earth sensor is about 20° to 30°, which may not be sufficient for low-Earth-orbiting micro-satellites. A novel...
Citations
... Compared to conventional scanning horizon sensors, which contain moving components, imaging horizon sensors are less difficult to develop. A number of imaging horizon sensitizers, each with its own characteristics, were developed [4][5][6]. ...
Horizon edge localization accuracy and speed are key factors in the performance of horizon sensors. This paper proposes a high-performance sub-pixel edge localization algorithm base on Field Programmable Gate Array (FPGA) for horizon sensors. The algorithm is carefully designed and simplified according to the computational capabilities and limitations of FPGAs. By making full use of the parallel computing capability of FPGA and carrying out multi-stage pipeline design, the algorithm can complete image acquisition, rough edge localization, sub-pixel edge localization, and projections from pixel points to unit vectors at the same time, which greatly reduces the delay caused by image processing. The experimental results show that FPGA-based image processing shows a significant superiority in terms of speed compared to traditional embedded processors.
... The infrared Earth sensor is an important attitude measurement component for satellites in space [1] that takes the Earth as the target source for the satellite attitude's reference. Different attitude information of the satellite with respect to the Earth is obtained by means of infrared optical detection, which enables the measurement of satellite roll and pitch attitude deviation angles [2]. ...
In a laboratory environment, in order to test the attitude recognition capability and accuracy of the satellite attitude sensor—the infrared Earth sensor—the infrared Earth simulator is fixed on a five-axis turntable to enable multi-angle testing. In the past, the temperature control system of the Earth simulator was water cooled, which not only affected the working accuracy of the Earth simulator but also affected its size and portability and made it more difficult to use on the turntable. Therefore, we designed a cooling method for the cold plate based on semiconductor cooling technology combined with air cooling, and we designed a fuzzy PID control algorithm to accurately control the temperature according to this cooling method. In this article, we use SOLIWORKS to build the system model for the system and use the ANAYS Workbench to perform temperature analysis of the Earth simulator. The results show that the cold plate temperature can be maintained at 20.089 °C when the hot plate temperature is 85 °C. The overall temperature uniformity of the hot plate is better than ±0.3 °C, which meets the index requirements of the Earth simulator. We found that this cooling method can replace water cooling, giving the simulator the advantage of being miniaturized, and it can be adaptable to the turntable, which can be widely used in various sizes of Earth simulators and in various complex environments and operating conditions.
... The perspective projection of an ellipsoid planet or moon is an approximate ellipse, so many ellipse fitting algorithms have been used for the problem of horizon-based OP-NAV [12,20]. In some applications, the celestial body with low ellipticity is directly approximated as a sphere, resulting in a simple and robust solution at the expense of some accuracy [21,22]. The traditional method of direct ellipse fitting in the image plane will incorrectly converge and introduce large errors in the case of a short-arc horizon. ...
Horizon-based optical navigation (OPNAV) is an attractive solution for deep space exploration missions, with strong autonomy and high accuracy. In some scenarios, especially those with large variations in spacecraft distance from celestial bodies, the visible horizon arc could be very short. In this case, the traditional Christian–Robinson algorithm with least-squares (LS) estimation is inappropriate and would introduce a large mean residual that can be even larger than the standard deviation (STD). To solve this problem, a simplified measurement covariance model was proposed by analyzing the propagation of measurement errors. Then, an unbiased solution with the element-wise total least-squares (EW-TLS) algorithm was developed in which the measurement equation and the covariance of each measurement are fully considered. To further simplify this problem, an approximate generalized total least-squares algorithm (AG-TLS) was then proposed, which achieves a non-iterative solution by using approximate measurement covariances. The covariance analysis and numerical simulations show that the proposed algorithms have impressive advantages in the short-arc horizon scenario, for the mean residuals are always close to zero. Compared with the EW-TLS algorithm, the AG-TLS algorithm trades a negligible accuracy loss for a huge reduction in execution time and achieves a computing speed comparable to the traditional algorithm. Furthermore, a simulated navigation scenario reveals that a short-arc horizon can provide reliable position estimates for planetary exploration missions.
... In our previous work [22], an Earth sensor composed of a panoramic annular lens (PAL) and a complementary-metal-oxide-semiconductor (CMOS) infrared camera was designed. The Earth sensor has been used on multiple missions [23]. ...
... The proposed nadir vector estimation algorithm (TLS and WTLS) was tested on simulated images along with the circle fitting algorithm [22] and non-iterative nadir vector estimation algorithm [19]. The orbit altitude was set to 600 km. ...
Infrared Earth sensors with large-field-of-view (FOV) cameras are widely used in low-Earth-orbit satellites. To improve the accuracy and speed of Earth sensors, an algorithm based on modified random sample consensus (RANSAC) and weighted total least squares (WTLS) is proposed. Firstly, the modified RANSAC with a pre-verification step was used to remove the noisy points efficiently. Then, the Earth’s oblateness was taken into consideration and the Earth’s horizon was projected onto a unit sphere as a three-dimensional (3D) curve. Finally, the TLS and WTLS were used to fit the projection of the Earth horizon. With the help of TLS and WTLS, the accuracy of the Earth sensor was greatly improved. Simulated images and on-orbit infrared images obtained via the satellite Tianping-2B were used to assess the performance of the algorithm. The experimental results demonstrate that the method outperforms RANSAC, M-estimator sample consensus (MLESAC), and Hough transformation in terms of speed. The accuracy of the algorithm for nadir estimation is approximately 0.04° (root-mean-square error) when Earth is fully visible and 0.16° when the off-nadir angle is 120°, which is a significant improvement upon other nadir estimation algorithms
... In the fields of aerospace equipment, optical imaging systems are usually built with weak-stiffness mirrors in order to meet the need for light weight. A specially shaped aluminum mirror is used in the infrared horizon system to realize the imaging function of the optical system [1]. The shape accuracy of the mirror surface determines the performance of the instrument, and the higher the shape accuracy, the higher the imaging resolution of the optical system. ...
Weak-stiffness mirrors are widely used in various fields such as aerospace and optoelectronic information. However, it is difficult to achieve micron-level precision machining because weak-stiffness mirrors are hard to clamp and are prone to deformation. The machining errors of these mirrors are randomly distributed and non-rotationally symmetric, which is difficult to overcome by common machining methods. Based on the fast tool servo system, this paper proposes a high-precision machining method for weak-stiffness mirrors. Firstly, the clamping error and cutting error compensation strategy is obtained by analyzing the changing process of the mirror surface morphology. Then, by combining real-time monitoring and theoretical simulation, the elastic deformation of the weak-stiffness mirror is accurately extracted to achieve the compensation of the clamping error, and the compensation of the cutting error is achieved by iterative machining. Finally, a weak-stiffness mirror with a thickness of 2.5 mm was machined twice, and the experimental process produced a clamping error with a peak to valley (PV) value of 5.2 µm and a cutting error with a PV value of 1.6 µm. The final machined surface after compensation had a PV value of 0.7 µm. The experimental results showed that the compensation strategy proposed in this paper overcomes the clamping error of the weak-stiffness mirror and significantly reduces cutting errors during the machining process, achieving the high precision machining of a weak-stiffness mirror.
... Calculating the three-axis attitude. For a full Earth coverage from low Earth orbits (LEO) either a multi-head camera concept [12] or a camera with a large field of view [13] is required. We assume that the satellite is equipped with the latter one in this study. ...
Limitations for small satellite missions encourages researchers and engineers to use on-board equipment for multiple tasks. Thus, both space can be saved and the equipment redundancy can be prevented. For Earth-imaging satellites a prominent equipment that can be used for multiple purposes is the camera. Other than the observation, the taken images can be used as measurements for determining the absolute or relative attitude of the spacecraft. Depending on also the content of the image (e.g. stars, Earth, Moon) a camera can be an alternate attitude sensor that is capable of providing high accuracy attitude measurements in low cost. This research aims at designing an attitude estimation algorithm, which can aid the coarse attitude estimates with the attitude information extracted from Earth images. Whenever an image is available to be used for attitude estimation, reference Earth data is matched with the ellipsoid that Earth image forms on the sensor frame to estimate the three-axis attitude of the spacecraft. This estimated attitude is fed to a multiplicative extended Kalman filter (MEKF) algorithm that runs as the main block of the attitude estimator. The measurements from the conventional attitude sensor block, which is formed of a three-axis magnetometer and Sun sensor, are pre-processed with QUEST algorithm to unify the measurement update process of the filter. This paper introduces the architecture of the proposed algorithm together with the details on possible methods to extract the attitude information from the obtained Earth images. Preliminary results to demonstrate the success of the algorithm are presented.
Inadequate geometric accuracy of cameras is the main constraint to improving the precision of infrared horizon sensors with a large field of view (FOV). An enormous FOV with a blind area in the center greatly limits the accuracy and feasibility of traditional geometric calibration methods. A novel camera calibration method for infrared horizon sensors is presented and validated in this paper. Three infrared targets are used as control points. The camera is mounted on a rotary table. As the table rotates, these control points will be evenly distributed in the entire FOV. Compared with traditional methods that combine a collimator and a rotary table which cannot effectively cover a large FOV and require harsh experimental equipment, this method is easier to implement at a low cost. A corresponding three-step parameter estimation algorithm is proposed to avoid precisely measuring the positions of the camera and the control points. Experiments are implemented with 10 infrared horizon sensors to verify the effectiveness of the calibration method. The results show that the proposed method is highly stable, and that the calibration accuracy is at least 30% higher than those of existing methods.
