星点坐标辅助的全天区三角形星图识别算法

随着当前星敏感器视场（FOV）的增大,探测能力的提高,一帧图中拍摄到的恒星更多。但是受星敏感器光谱范围的限制及空间环境干扰影响,星等测试精度一般不高于0.2 mV。为了充分发挥当前星敏感器视场和探测能力的优势,并避免星等误差的影响,提高全天区星图识别算法在线应用的适用性,提出了一种星点坐标辅助的全天区三角形星图识别算法。该方法采用"全局初步搜索识别—局部精细匹配验证—最优结果选取"的算法思想。首先,根据星敏感器探测到的极限星等范围构建导航星表,选取亮星构建角距星表,既确保了星表的完备性,又有利于充分利用星敏感器的探测能力。然后,在三角形约束条件下进行角距匹配识别,得到一个或多个导航三角形,在该识别环节提出了非线性矢量法查找星表,既提高了定位精度,又能采用单精度数据类型降低存储空间。最后,提出局部天区星点坐标匹配算法进一步消除冗余匹配,同时又识别出视场内更多的观测星,有利于提高识别率和定姿精度。试验结果表明,与其他一些经典的星图识别算法相比,所提算法在识别率和星表容量方面更有优势。识别率可达99.9%,且随着星等的增加,存储容量增加的最少。所提算法更加适于大视场、高星等敏感范围的星敏感器在线应用。     

亮星辅助下基于坐标转换的快速星图识别方法

数字天顶仪作为一种地面使用的星敏感器，主要用于高精度定位。为提高仪器的工作效率需要对星图识别的快速性进行研究。通过对恒星像点理论坐标与图像坐标的分析，构建坐标转换模型。依据星表中恒星的分布及星等筛选出视场范围内的亮星，并构建导航星表。结合导航星表完成3颗亮星的准确识别，在识别亮星的基础上解算坐标转换模型的参数。通过构建的坐标转换模型对视场范围内的恒星进行坐标转换，将转换后的星点坐标与提取的星点图像坐标进行匹配完成星图的识别，这样能够提高星图识别的快速性。实验数据表明：在保证识别星点数量的基础上，采用亮星辅助下基于坐标转换的星图识别方法使时间缩短为改进三角形星图识别算法的五分之一。     

Rapid Star Tracking Algorithm for Star Sensor

A rapid star tracking algorithm is proposed. In order to speed up the tracking, three techniques includng parallel star centroiding, sorting, and star catalogue partition are designed for three time-consuming portions in tracking algorithms. The parallel star centroiding is implemented with Field Programmable Gate Array (FPGA) which avoid image storage and transmission. Update rate of star sensor is improved. Sorting star coordinates in star image plane, and then matching, which avoid matching between stars with a long distance in image plane. Star catalogue partition divides the celestial sphere into many small partitions. In star mapping, guide stars are searched in the partitions near the direction of star sensor's boresight is not in the whole celestial sphere and therefore reduced the total number of searched guide stars. The software and hardware performance of tracking algorithms are simulated. Tracking robustness and the tracking speed comparison are tested in the software simulation. In hardware tests, the tracking time in every step is obtained.     

Recursive mode star identification algorithms

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.     

Star trackers for attitude determination

One problem comes to all spacecrafts using vector information. That is the problem of determining the attitude. This paper describes how the area of attitude determination instruments has evolved from simple pointing devices into the latest technology, which determines the attitude by utilizing a CCD camera and a powerful microcomputer. The instruments are called star trackers and they are capable of determining the attitude with an accuracy better than 1 arcsecond. The concept of the star tracker is explained. The obtainable accuracy is calculated, the numbers of stars to be included in the star catalogue are discussed and the acquisition of the initial attitude is explained. Finally the commercial market for star trackers is discussed     

一种结合角距特征的改进栅格星图识别算法

针对栅格算法易受邻域星点影响导致误匹配的问题,提出了一种结合角距特征的改进栅格星图识别算法。首先介绍了改进栅格算法的原理,其次设计了融合栅格识别模式和星角距识别模式的算法实现流程,最后开展了基于不同视角下的大视场仿真星图的算法试验验证和性能分析。结果表明,由于角距特征具有旋转不变性和不易受观测星邻域星点分布影响等特点,结合角距特征对失效观测星进行再匹配的改进栅格算法,在兼顾存储量需求小、运行速度快等优势的同时,识别率和鲁棒性也得到了提升,最高识别率可达98.88%,在位置噪声干扰以及缺失星干扰下,改进算法的识别率仍可保持在95%,说明算法鲁棒性强,具有较好的应用前景。     

基于帧间角距匹配的跟踪模式星图识别

为了提高星敏感器的跟踪匹配速率,提高星敏感器姿态更新率,本文提出了一种基于帧间角距匹配的跟踪模式星图识别方法.该方法充分利用上一时刻的角距匹配信息构建了一个实时跟踪星库,并把当前时刻的角距信息在实时跟踪星库中进行匹配识别,识别成功后利用识别时用到的信息对实时跟踪星库进行更新.仿真实验表明,该方法具有匹配时间短、匹配成功率高的优点.     

Star-configuration searching for satellite attitude computation

A star pattern recognition algorithm is described which recovers attitude information by processing data obtained from a modular star sensor (MOSS) mounted on a spacecraft information is obtained by matching the stars detected by the MOSS with those inside a stellar catalogue. The system performance has been evaluated both from the point of view of computation time and error probability. The effect of errors in the MOSS measurements and multiple matches cases are also discussed     

弹道导弹中段目标/背景红外图像建模与仿真

提出了一种针对弹道导弹中段目标和背景的动态红外辐射特性仿真方法。首先,建立了弹头目标^秀饵的三维模型,并结合其运动位置分析了影响弹头目标／诱饵红外辐射的因素,建立了较为完善的弹头目标/诱饵红外物理模型;其次,基于红外星表数据对恒星大气层外的辐照度进行了计算,根据红外传感器视轴指向和红外传感器视场,确定了红外传感器视场中的可见恒星,并根据拟生成背景图像的空间分辨率计算出这些恒星在背景图像中的相对位置分布,对星空背景直接进行了动态图像生成;然后,对成像过程中红外探测系统的噪声效应进行了建模与分析,同时给出了噪声的计算机模拟方法;最后,将生成的弹头目标,诱饵的红外图像与星空背景红外图像在灰度和空间2个层次上进行合成形成完整的弹头目标赝饵／星空背景的红外仿真图像,可为弹道导弹中段红外电子对抗突防提供较为准确的数据支持。     

根据同时观测信息确定航天器 姿态四元数的一种解析方法

介绍根据星敏感器同时观测几颗恒星的方向信息,用最小二乘法确定飞行器姿态的经典Wehba问题.针对用四元数描述飞行器姿态的情况,推导了的一种解析算法.观测5颗恒星实例的仿真结果表明,该算法能保证飞行器体轴系相对惯性系姿态的高精度.     

寡星条件下的半球谐振陀螺与星敏感器 组合姿态测量算法

针对半球谐振陀螺与星敏感器松组合系统在寡星条件下无法正常工作的问题,采用新的星图识别算法和新的数据融合观测方程,使星敏感器在观测到的导航星数量为1或2颗的情况下完成星图识别,从而能够完成组合测姿。     

Star recognition algorithm for APS star tracker: oriented triangles

An efficient star pattern recognition algorithm is presented. The purpose of this algorithm is to make sure of the compatibility of the software and the imaging sensor noise level. The new CMOS APS sensors have not currently reached the same accuracy as the former CCD sensors in position as well as in magnitude determination, especially in the dynamic stages. This algorithm allows the system to recognize the star pattern 20% faster than with reference algorithms. No false recognition has been noticed. Used databases have a size 5 to 10 times smaller, depending on other reference algorithms. Oriented triangles are used to compare the measured star pattern with the catalogue stars. The triangle's characterization criteria propose several solutions in a first time. A unique solution is selected by means of identification and validation methods in a second time. First results, presented hereinafter, are very encouraging, and this algorithm may be used in the future APS star trackers. APS star tracker robustness is significantly enhanced by this method during the critical navigation phases     

Pattern recognition of star constellations for spacecraftapplications

A software system for a star imager for online satellite attitude determination is described. The system works with a single standard commercial CCD camera with a high aperture lens and an onboard star catalog. It is capable of both an initial coarse attitude determination without any prior knowledge of the satellite orientation and a high-accuracy attitude determination based on prediction and averaging of several identified star constellations. In the high-accuracy mode the star image aims at an accuracy better than 2 arc sec with a processing time of less than a few seconds. The star imager has been developed for the Danish Oersted satellite     

一种通过观测两颗恒星确定飞行器姿态的算法

本文介绍了通过固联安装在飞行器本体上的星跟踪器观测两颗恒星,确定飞行器姿态的一种算法,建立了相应的坐标系,推导了恒星观测角与描述飞行器姿态的四元数之间的关系。     

一种全天时星跟踪器相对惯导的安装阵在线快速估计方法

全天时星跟踪器与捷联惯导组成的惯性/天文组合导航系统具有精度高、自主性强等优点，在飞机、无人机、船舶等领域具有广泛的应用前景。组合导航系统长时间工作中力热变化导致安装矩阵漂移进而影响导航系统精度，全天时星跟踪器由于天空光影响视场小，一次只能观测一颗恒星，无法根据一副星图直接进行安装阵估计。提出了一种基于Levenberg-Marquart （L-M）算法的捷联惯性/天文组合导航系统安装阵在线快速高精度估计方法，利用捷联惯导姿态测量值，将不同时刻的观测星矢量转移到同一时刻同一坐标系中，构造多颗观测星的观测矢量误差与导航星矢量最小二乘目标函数，利用自适应步长的L-M算法对其进行迭代求解，实时得到系统安装矩阵的变化量。试验结果表明，使用该方法后星跟踪器在捷联惯导本体坐标系的输出恒星投影矢量精度提升了1倍以上，在线估计时间优于5 ms，满足用户实时性和高精度要求。     

An all-sky autonomous star map identification algorithm

The attitude of the spacecraft can be obtained with accuracy by using star sensors. Its key technology is how to identify stellar maps. Triangle algorithm is used most widely in the current star map identification algorithms. In the field of physical geography modelling, Delaunay triangulation cutting algorithm has been widely used because of its important characteristic; the result of this triangulation cutting method is unique from a random set of points. This triangulation algorithm is first applied to identify star map for its particular character. In final, the proposed method is applied to simulation; the results show that compared with the current star map identification algorithms, the algorithm presented in this paper has the advantage of real-time properties and robustness. It needs a smaller database of guidance stars and matches more rapidly.     

Image Smearing Modeling and Verification for Strapdown Star Sensor

To further extend study on celestial attitude determination with strapdown star sensor from static into dynamic field, one prerequisite is to generate precise dynamic simulating star maps. First a neat analytical solution of the smearing trajectory caused by spacecraft attitude maneuver is deduced successfully, whose parameters cover the geometric size of optics, three-axis angular velocities and CCD integral time. Then for the first time the mathematical law and method are discovered about how to synthesize the two formulae of smearing trajectory and the static Gaussian distribution function (GDF) model, the key of which is a line integral with regard to the static GDF attenuated by a factor 1/ L s (L s is the arc length of the smearing trajectory) along the smearing trajectory. The dynamic smearing model is then obtained, also in an analytical form. After that, three sets of typical simulating maps and data are simulated from this dynamic model manifesting the expected smearing effects, also compatible with the linear model as its special case of no boresight rotation. Finally, model validity tests on a rate turntable are carried out, which results in a mean correlation coefficient 0.920 0 between the camera images and the corresponding model simulated ones with the same parameters. The sufficient similarity verifies the validity of the dynamic smearing model. This model, after parameter calibration, can serve as a front-end loop of the ground semi-physical simulation system for celestial attitude determination with strapdown star sensor.     

Star identification algorithms: novel approach & comparison study

A novel approach to the problem of star identification for spacecraft attitude determination based on data provided by a star camera is proposed. The algorithm is based on pattern matching ideas and provides improved reliability with respect to similar methods available in the literature. The achievable performance is demonstrated via a comparison study with two published algorithms     

Pattern recognition of star constellations for spacecraftapplications

A software system for a star imager for on-line satellite attitude determination is described. The system works with a single standard commercial CCD-camera with a high aperture lens and an onboard star catalogue. It is capable of both an initial course attitude determination without any prior knowledge of the satellite orientation and a high-accuracy attitude determination based on prediction and averaging of several identified star constellations. In the high accuracy mode the star imager aims at an accuracy better than 2 arc sec with a processing time of less than a few seconds. The star imager is developed for the Danish microsatellite Oersted     

Precession–nutation correction for star tracker attitude measurement of STECE satellite

Space Technology Experiment and Climate Exploration(STECE) is a small satellite mission of China for space technology experiment and climate exploration. A new test star tracker and one ASTRO 10 star tracker have been loaded on the STECE satellite to test the new star tracker's measurement performance. However,there is no autonomous precession–nutation correction function for the test star tracker,which causes an apparent periodic deflection in the inter-boresight angle between the two star trackers with respect to each other of up to ±500 arcsec,so the precession and nutation effect needs to be considered while assessing the test star tracker. This paper researches on the precession–nutation correction for the test star tracker's attitude measurement and presents a precession–nutation correction method based on attitude quaternion data. The periodic deflection of the inter-boresight angle between the two star trackers has been greatly eliminated after the precession and nutation of the test star tracker's attitude data have been corrected by the proposed method and the validity of the proposed algorithm has been demonstrated. The in-flight accuracy of the test star tracker has been assessed like attitude noise and low-frequency errors after the precession–nutation correction.