Star image processing of SINS/CNS integrated navigation system based on 1DWF under high dynamic conditions

Angular velocity is a critical parameter for satellites during on-orbit operation. Current gyro-free angular velocity estimation methods based on star sensors predominantly rely on multiple frames of star images and are effective under relatively small maneuvers of the star sensor. This paper proposes an angular velocity estimation approach utilizing single-frame star image data captured by a high-dynamic star sensor operating under rolling shutter exposure mode. By analyzing the motion patterns of star points in single-frame images, an angular velocity estimation optimization model was established with inter-star angular distances as the objective function. Accurate angular velocity estimation was achieved through the simulated annealing algorithm. To evaluate the star sensor's performance under high-dynamic conditions, three representative operational working conditions were simulated numerically. Experimental results demonstrate: under composite motion with dual-axis angular velocity of 15°/s and angular acceleration of 0.8°/s², the root mean square errors (RMSE) for triaxial angular velocity estimation are 0.0378°/s (X-axis), 0.0365°/s (Y-axis), and 0.1947°/s (Z-axis). Notably, when subjected to sinusoidal/cosinusoidal dynamic angular velocity excitation with amplitude of 15°/s, the maximum comprehensive error of triaxial angular velocity estimation does not exceed 0.103°/s, validating the algorithm's robustness in complex motion environments.

In this paper, INS/CNS (CINS) is integrated into a module, and then CINS and BDS are further combined to form a deep integrated BDS/INS/CNS navigation system, which can significantly improve the navigation, positioning, and attitude measurement accuracy under high dynamic and strong interference conditions. It has broad application prospects for specific users such as high-altitude long-endurance Unmanned Aerial Vehicle (UAV) and high-maneuvering glider. In order to verify and analyze the algorithm and performance of the deep integrated navigation system, the design and implementation of BDS/INS/CNS deep integrated navigation simulation platform are presented and the overall architecture, information flow, and the composition of each subsystem of the simulation platform are introduced. The simulation results show that, under high dynamic conditions, the position accuracy of the BDS/INS/CNS deep integrated navigation system is better than 1 m, the speed accuracy is better than 0.1 m/s, and the overall performance is better than the BDS/INS deep integrated navigation system. It also verifies the availability of the simulation platform, which has guiding significance for the next design of BDS/INS/CNS deep integrated navigation prototype.

Under the dynamic working conditions of a star sensor, motion blur of the star will appear due to its energy dispersion during imaging, leading to the degradation of the star centroid accuracy and attitude accuracy of the star sensor. To address this, a restoration method of a blurred star image for a star sensor under dynamic conditions is presented in this paper. First, a kinematic model of the star centroid and the degradation function of blurred star image under different conditions are analyzed. Then, an improved curvature filtering method based on energy function is proposed to remove the noise and improve the signal-to-noise ratio of the star image. Finally, the Richardson Lucy algorithm is used and the termination condition of the iterative equation is established by using the star centroid coordinates in three consecutive frames of restored images to ensure the restoration effect of the blurred star image and the accuracy of the star centroid coordinates. Under the dynamic condition of 0~4°/s, the proposed algorithm can effectively improve the signal-to-noise ratio of a blurred star image and maintain an error of the star centroid coordinates that is less than 0.1 pixels, which meets the requirement for high centroid accuracy.

The accuracy of star centroid extraction and identified star number is both crucial features for star sensor precision. Motion blur and fracture are introduced when star sensor works under high dynamic conditions, which affect the accuracy of star centroid extraction and further reduce the precision of the star sensor. To improve the precision of star sensor, this paper proposes an adaptive window star map restoration method based on energy equalization. The local degradation function is estimated for the star point energy distribution region, and dynamic star map simulation and restoration are performed. The simulation process is divided into three steps. Firstly, establish the motion trajectory of the star point centroid in the detector plane during the exposure time, according to the trailing trajectory size and direction adaptive selection window. Secondly, accumulate the star image point energy in the adaptive window to achieve star point recovery, and finally the recovery effect was evaluated by star extraction results.

During the satellite in-orbit mission, the load platform needs to rotate at an angular velocity of 16°/s at a constant speed. The field of view of the star sensor will be frequently affected by sunlight and earth light. The requirement of high-speed rotation and the restriction of the field of view, as well as the high communication frequency of 10Hz, require the star sensor to have the ability to quickly identify the star map and provide high-precision output information. In this paper, we design a time sequence of the control system to improve the star map recognition speed and data update rate of the star sensor. The falling edge of the synchronization signal is aligned with the integration center of the probe to ensure the accuracy of the exposure time of the star sensor and the accuracy of the predicted attitude, which improves the ability of the star sensor to identify the star map and determine the attitude information quickly. According to the time from the exposure to the calculation of attitude information, the timing design of half-cycle interval between the synchronization signal and the fetching command makes use of the parallel working capability of the star sensor exposure and the star map data processing, which ensures sufficient time for the star map calculation, and improves the data update rate of the star sensor.KeywordsStar sensorHigh dynamic conditionsTime sequence designOutput frequency

The attitude accuracy of a star sensor decreases rapidly when star images become motion-blurred under dynamic conditions. Existing techniques concentrate on a single frame of star images to solve this problem and improvements are obtained to a certain extent. An attitude-correlated frames (ACF) approach, which concentrates on the features of the attitude transforms of the adjacent star image frames, is proposed to improve upon the existing techniques. The attitude transforms between different star image frames are measured by the strap-down gyro unit precisely. With the ACF method, a much larger star image frame is obtained through the combination of adjacent frames. As a result, the degradation of attitude accuracy caused by motion-blurring are compensated for. The improvement of the attitude accuracy is approximately proportional to the square root of the number of correlated star image frames. Simulations and experimental results indicate that the ACF approach is effective in removing random noises and improving the attitude determination accuracy of the star sensor under highly dynamic conditions.

Under dynamic conditions, motion blur is introduced to star images obtained by a star sensor. Motion blur affects the accuracy of the star centroid extraction and the identification of stars, further reducing the performance of the star sensor. In this paper, a star image restoration algorithm is investigated to reduce the effect of motion blur on the star image. The algorithm includes a blur kernel calculation aided by a MEMS gyroscope, blur kernel correction based on the structure of the star strip, and a star image reconstruction method based on scaled gradient projection (SGP). Firstly, the motion trajectory of the star spot is deduced, aided by a MEMS gyroscope. Moreover, the initial blur kernel is calculated by using the motion trajectory. Then, the structure information star strip is extracted by Delaunay triangulation. Based on the structure information, a blur kernel correction method is presented by utilizing the preconditioned conjugate gradient interior point algorithm to reduce the influence of bias and installation deviation of the gyroscope on the blur kernel. Furthermore, a speed-up image reconstruction method based on SGP is presented for time-saving. Simulated experiment results demonstrate that both the blur kernel determination and star image reconstruction methods are effective. A real star image experiment shows that the accuracy of the star centroid extraction and the number of identified stars increase after restoration by the proposed algorithm.

Measurement technology for material emissivity under high temperature dynamic heating conditions

The star sensor is widely used in attitude control systems of spacecraft for attitude measurement. However, under dynamic conditions, the star image acquired by star sensor may appear smearing, which leads to a decline in accuracy or failure of star centroid extraction and attitude determination. In order to improve the performance of the star sensor under high dynamic environment, a Richardson-Lucy (RL) algorithm based on radial basis function neural network (RBFNN) is proposed. First, the Point Spread Function (PSF) is calculated by using the angular velocity information provided by the gyroscope. Then, we use the RBFNN to predict the number of iterations required by the RL algorithm to complete the star image deblurring. Finally, simulation experiments are performed to verify the effectiveness of the proposed algorithm.

Star sensors play an important role in spacecraft attitude determination. It is common for the roll accuracy of a traditional star sensor with single field of view to be significantly worse than the cross-axis accuracy. Many satellites utilize two/three onboard star cameras for their attitude determination in x, y, z 3-axis. The dual-field-of-view star sensor has been proposed, which can image stars from two orthogonal directions on the same CCD simultaneously. This paper focuses on the critical issue of tagging the star spots from one of the fields of view so that these stars can be recognized. Star light from one direction is modulated by an optical grating in order to tag star images from this viewing field and distinguish them from the star images from another direction. Diffraction splits by phase gratings and amplitude gratings are compared in feasibility and complexity by numerical simulations.

The integrated navigation system of strapdown inertial navigation system (SINS) and odometer (OD) is a commonly used vehicle positioning system. The installation errors caused by the difference between the installation positions of SINS and OD mainly include the installation deflection angle and lever arm, which will reduce the positioning accuracy. The traditional calibration method is to expand the installation deflection angle error and lever arm error into state variables, the velocity difference under nonholonomic constraint (NHC) is taken as the measurement to establish the Kalman filter model for online calibration, but this method seriously depends on the sensor accuracy. In order to calibrate the installation errors of low-precision SINS, this paper improves NHC, adds the difference between the centripetal acceleration measured by odometer and calculated by SINS as measurement on the basis of the original measurement, and introduces a low-pass filter to reduce the interference of vehicle vibration on the accelerometer.The experimental results show that the proposed algorithm has better convergence of the installation deflection angle, and the error between the estimation results of the forward lever arm and the actual measurement results is less than 0.1m; After compensating the installation errors of the improved NHC, the maximum positioning errors in the east and north directions are reduced by 63.19% and 43.51% respectively, the height error is also greatly reduced, and the positioning accuracy of the integrated navigation system is significantly improved.

Star Sensor is an avionics instrument used to provide the absolute 3-axis attitude of a spacecraft utilizing star observations. It consists of an electronic camera and associated processing electronics. As outcome of advancing state -of-the-art, new generation star sensor features faster, lower cost, power dissipation and size than the first generation star sensor. This paper describes a star sensor anterior image acquisition and pre-processing hardware system based on CMOS image-sensor and FPGA technology. Practically, star images are produced by a simple simulator on PC, acquired by CMOS image sensor, pre-processed by FPGA, saved in SRAM, read out by EPP protocol and validated by a image process software on PC. The hardware part of system acquires images thought CMOS image-sensor controlled by FPGA, then processes image data by a circuit module of FPGA, and save images to SRAM for test. Basic image data for star recognition and attitude determination of spacecrafts are provided by it. As an important reference for developing star sensor prototype, the system validates the performance advantages of new generation star sensor.

At the same orbital height, the radiation environment in SAA region is worse than that in other regions. The main difference is that the region contains high energy particles. CCD star sensors has been developed for use in the attitude determination and control system of satellites, we have processed star sensors flight data and star images acquired by satellites in orbit in an attempt to characterize the performance of CCD star sensors in the abnormal region of the South Atlantic. This paper also introduces the influence of high energy particles exist in the South Atlantic Anomaly on CCD photoelectric imaging detectors. The abnormal phenomena and generation mechanism in the star images has been analyzed. The improvement measures and suggestions for high precision star sensors to avoid or eliminate the influence of SAA has been given finally, which provides reference for improving the performance of star sensors.

In the integrated inertial navigation system (INS) and celestial navigation system (CNS), the attitudes and positions of probes are estimated based on the auxiliary measurement of an infrared Earth sensor. The poor accuracy of the infrared Earth sensor compared to that of the star sensor significantly limits the navigation accuracy of the integrated navigation system. This paper proposes a novel INS/CNS integrated navigation system that uses the specific force with noncumulative error to correct infrared Earth measurements. The probe azimuth angle and elevation angle relative to the Earth's inertial frame are first estimated according to the specific force provided by the INS to filter the infrared Earth sensor's measurement error. Then, the corrected infrared Earth measurement assists the CNS to obtain accurate celestial measurements. The integrated INS/CNS navigation system in the tightly coupled mode finally estimates the accurate probe attitude and position. Compared to the integrated navigation system, which directly uses the uncorrected infrared Earth measurement, the yaw, pitch, and roll angle are improved under the proposed method by 76.73%, 77.64%, and 75.39% on average, respectively; the latitude and longitude estimation errors improve under the proposed method by 70.44% and 61.92% on average, respectively. In short, the proposed method is a feasible and highly accurate approach to the INS/CNS integrated navigation system.

In order to actualize the fast synchronization of carrier in high dynamic, A New union carrier synchronization algorithm based on FFT and PLL (Phase Locked Loop) is proposed. The basic idea is that firstly get a coarse estimation by using the peak of a period gram and then gain an accurate estimation by using a new interpolation formula about the two lines beside the pea. Next, using the frequency as guide frequency, to control the frequency of the sine signal produced by the NCO (Numerically Controlled Oscillator). And finally achieve the goal of carrier synchronization through the adaptive algorithm of the PLL. With the method of real-time and precise estimation of carrier, it can reduce the tracking time in low signal-to-noise rate and high dynamic condition. The results show that it can effectively achieve the expectations of carrier quickly capture and carrier accurate tracking.