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 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     

一种改进的星图降噪算法研究

在星敏感器的使用过程中，由于外界环境的影响及传感器自身的限制，拍摄出来的星图不可避免地存在一些噪声，因此对星图进行去噪处理是一项非常重要的工作。针对传统高斯模板滤波存在的引入邻域噪声、无法自行根据星图特性修正等造成去噪效果不好的问题，提出了一种改进的星图降噪算法。该方法在滤波前先进行坏点剔除工作，并采用高斯低通滤波与高通滤波结合的方式对图像进行处理，在抑制噪声的同时有效地保留了星点信号。通过阐述星敏感器的工作原理，分析星图的噪声特性，对星图滤波去噪算法进行研究，并进行模拟星图影像提取星点坐标实验。结果表明：使用该算法进行滤波比传统的高斯滤波算法提取的质心坐标精确度更高，较传统方法横坐标提高0.00538个像素点，纵坐标提高0.0077个像素点，证实了图像处理算法的有效性。     

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。     

P向量实现快速星图识别的方法

 提出了一种快速的星图识别方法。该方法识别时提取出描述观测三角形的一维特征量P，根据该值快速检索到对应的导航三角形，减少了计算过程。由于获得星点位置的时候存在误差，所以将一定误差范围内的三角形均作为待选三角形考虑。上述识别后引入了验证识别环节，保证识别的准确性。随机实验统计表明，同等星点位置噪声方差下，该方法和栅格算法相比识别率提高约1%，识别时间约为后者的1/5。     

一种改进的三角形星图识别方法

首先提出在直角坐标系下将天球球面均匀地分成486个分区的方法——"内接正方体法",实现导航星的快速检索。然后按照星对角距的大小升序排列,直接存储星对角距,并通过设置星对角距状态标识,完成星对角距的快速匹配搜索。最后,引入验证识别环节有效地解决观测三角形与匹配的导航三角形产生的冗余问题。仿真实验表明,改进的三角形星图识别方法对星点位置噪声和星等(亮度)噪声均具有较强的抗干扰能力,且在识别时间和存储空间的需求方面均比传统的三角形算法也具有较大的优势。     

一种快速的星敏感器星跟踪方法研究

阐述了星敏感器中星跟踪方法的重要性,指出了目前国内外星跟踪方法的不足。针对这些不足,提出了一种全新的、快速的星跟踪方法。新的跟踪方法采用现场可编程门阵列(FPGA)实现了实时的星点定位;正是由于这种技术的采用,加快了星点位置信息的获取,摈弃了跟踪窗的跟踪方法,采用简单的匹配识别的跟踪方法;对于新星的识别,由于有初始姿态而采用匹配组的识别方法。最后给出了星跟踪过程的实验结果。     

IDENTIFICATION OF GYRO DRIFTS UNDER THREE AXIS ATTITUDE COUPLING

ＩＤＥＮＴＩＦＩＣＡＴＩＯＮＯＦＧＹＲＯＤＲＩＦＴＳＵＮＤＥＲＴＨＲＥＥＡＸＩＳＡＴＴＩＴＵＤＥＣＯＵＰＬＩＮＧＪＩＮＧＷｕｘｉｎｇ（荆武兴），ＷＡＮＧＸｕｅｘｉａｏ（王学孝），ＷＵＹａｏｈｕａ（吴瑶华）（ＨａｒｂｉｎＩｎｓｔｉｔｕｔｅｏｆＴｅｃｈｎ...     

A grid algorithm for autonomous star identification

An autonomous star identification algorithm is described that is simple and requires less computer resources than other such algorithms. In simulations using an 8/spl times/8 degree field of view (FOV), the algorithm identifies the correct section of sky on 99.7% of the sensor orientations where spatial accuracy of the imaged star is 1 pixel (56.25 arc seconds) in standard deviation and the apparent brightness deviates by 0.4 units stellar magnitude. This compares very favorably with other algorithms in the literature.     

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。     

液体火箭发动机启动过程实时在线故障检测算法

利用神经网络技术实现了液体火箭发动机启动过程的非线性辩识；提出并实现了一种基于辩识误差检验的故障检测策略。经大量实际发动机热试车数据验证表明，所提出的检测算法十分有效。由于算法所利用的监测参数均系实际发动机地面试车中所测量的参数，且检测算法在线工作时计算量十分小，因而所提出并实现的检测算法可以直接应用于工程实际。     

基于分层栅格地图的移动机器人路径规划

针对传统A-Star算法与模糊控制算法单独应用于移动机器人路径规划时各自的局限性,提出一种基于分层栅格地图并将两种算法融合的移动机器人路径规划新方法.融合后的新算法先利用A-Star算法在高层栅格地图中整体规划出一条概括性路径,再利用模糊控制算法以概括性路径中的点为导航点,在底层栅格地图中进行局部规划,从而得出最终的路径.仿真结果表明,与传统的A-Star算法与模糊控制算法相比较,新算法所规划路径距离较短且平滑可行,具有较高的品质.     

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     

Hybrid Simulation System Study of SINS/CNS Integrated Navigation

In flight tests, to demonstrate the performance of integrated navigation systems, which are strapdown inertial navigation systems/celestial navigation systems (SINS/CNS), will involve a lot of effort and a heavy financial budget. So, it is important to design a functional self-contained hardware in a loop simulation system on the ground for solving the verification of SINS/CNS integrated navigation systems. Aiming at solving the main program, a high precision, versatile and better real-time performance hybrid simulation system of SINS/CNS integrated navigation is presented. The system adopts the design of hardware-functional modularization and software-flow integration, and makes use of a trajectory generator to produce simulated nominal trajectory data which is a uniform reference to signal process, and employs unique time synchronization algorithms to collect actual errors data of inertial sub-system and celestial sub-system. By combining with nominal trajectory data, the data smoothing, all-sky autonomous star map identification and integrated navigation algorithm based on unscented Kalman filtering (UKF), this system can accomplish a lot of system performance testing. It has the features of flexibility and extensibility and can be used to effectively reduce the experimental expense and shorten the development time of integrated navigation system, which is significant for studying algorithm performance, system speciality, and practical application of integrated navigation system.     

Identification of nonlinear flight dynamics: theory and practice

This article presents an innovative time-domain nonlinear mapping-based identification method. The method reported is applied to identify the unknown parameters of multivariable dynamic systems which are mapped by nonlinear differential equations. A systematic identification method is introduced, and a novel algorithm is developed using nonlinear error maps. An analysis of parameter convergence is provided and the regions of convergence can be found using the second method of Lyapunov. Innovative nonquadratic Lyapunov functions are designed and used. Analytical and numerical studies are performed to illustrate and validate the identification concept. The unsteady flight of a high-alpha aircraft in the longitudinal axis is chosen as a nonlinear case study. The unknown parameters are identified. Simulation results show that the model dynamics match the experimental data. The reported example demonstrates that the time-domain nonlinear mapping-based identification method ensures robustness and reduces major shortcomings in stability, convergence, and computational efficiency compared with other algorithms available     

基于Census变换和改进自适应窗口的立体匹配算法

 针对现有立体匹配算法难以在幅度失真图像中获取高匹配精度的问题,提出了一种基于Census变换和改进自适应窗口的立体匹配算法。首先根据图像结构和色彩信息获得基于十字骨架的任意形状和大小的Census变换窗口;其次利用Census变换的Hamming距作为匹配代价,使用两次累加降低计算复杂度,采用局部优化得到初始视差;最后提出一种基于均值偏移的视差提精方法,有效地处理了不可信视差区域,获得高精度的视差图。实验表明,通过该算法获得的视差图与当前优秀的局部算法相比精度相当,特别是能很好地处理现有算法难以解决的幅度失真问题,适用于无人机视觉导航的应用。     

SINS/BD紧组合导航系统故障检测算法研究与实现

由于惯性导航系统和卫星导航系统具有良好的互补性与北斗导航系统的迅速发展,惯性/卫星紧组合导航系统得到广泛应用。但卫星导航系统的时变、易受干扰等特性,极易污染整个组合导航系统。因此,研究了一种新型的惯性/北斗紧组合导航系统的故障检测算法,在传统的卡方故障检测算法基础上,利用新息动态变化特性来识别故障星,并对故障星进行隔离,从而保证整个导航系统的稳定性与精度。最后基于嵌入式PC104平台,利用Qt Creator软件开发了多线程惯性/北斗紧组合导航系统,对所研究的算法进行了可靠验证。实验结果表明,所研究的故障检测算法能够有效地检测出卫星信号故障,能及时剔除故障星,大大降低了漏检、错检的概率,提高了整个导航系统的可靠性与精度。     

Inverse identification of constitutive parameters of Ti2AlNb intermetallic alloys based on cooperative particle swarm optimization

Ti₂AlNb intermetallic alloy is a relatively newly developed high-temperature-resistant structural material, which is expected to replace nickel-based super alloys for thermally and mechanically stressed components in aeronautic and automotive engines due to its excellent mechanical properties and high strength retention at elevated temperature. The aim of this work is to present a fast and reliable methodology of inverse identification of constitutive model parameters directly from cutting experiments. FE-machining simulations implemented with a modified Johnson-Cook (TANH) constitutive model are performed to establish the robust link between observables and constitutive parameters. A series of orthogonal cutting experiments with varied cutting parameters is carried out to allow an exact comparison to the 2D FE-simulations. A cooperative particle swarm optimization algorithm is developed and implemented into the Matlab programs to identify the enormous constitutive parameters. Results show that the simulation observables (i.e., cutting forces, chip morphologies, cutting temperature) implemented with the identified optimal material constants have high consistency with those obtained from experiments, which illustrates that the FE-machining models using the identified parameters obtained from the proposed methodology could be predicted in a close agreement to the experiments. Considering the wide range of the applied unknown parameters number, the proposed inverse methodology of identifying constitutive equations shows excellent prospect, and it can be used for other newly developed metal materials.     

基于红外视觉/激光雷达融合的目标识别与定位方法

近年来,基于可见光图像的目标识别在无人车感知领域得到了广泛应用.然而,可见光图像目标识别无法应用于弱光和黑暗环境.针对于此,提出了一种基于红外视觉/激光雷达融合的目标识别与定位算法.首先,通过基于颜色迁移的数据增强训练方法,提高了红外目标识别算法的泛化性能.继而,提出了一种基于激光雷达修正的单目深度估计方法,通过视觉图...     

基于图的DTAD的简易稳健自动生成算法

二维任意域(含任意多个空腔)的Delaunay三角剖分(简记为DTAD)广泛应用于有限元网格生成等方面。本文提出了一种基于图的DTAD的简易稳健自动生成算法。该算法首先构造任意域中所有边界点集的约束最小生成树,然后将同时满足本文所给三个简易约束算法的边逐次引入初始三角形网格表,形成边界点集的三角剖分,再通过稳健局部优化算法和贴体生成核插入算法自动生成DTAD。本文同时分析了退化及数值计算误差对剖分结果的影响,在提高局部优化的稳健性方面对该算法做了进一步完善,使之能更好地满足任意域网格剖分的要求。文末给出具体应用实例以说明本文所提算法的有效性。