GPS/运动方程组合导航

提出了一种不增加硬件设备而仅用软件（运动方程）－－全球卫星定位系统／运动方程（GPS／EM）组合导航方案，分析了其适用范围和特点。根据传统运动方程建模中的各种误差源，了包含误差源在内的飞行器扰动方程，并得出其解析解。建立了GPS／EM组合系统状态方程和观测方程，并进行仿真，验证了其可行性。结果表明，GPS／EM组合系统导航精度高于GPS，而且较单独GPS增加了信息冗余度。     

基于脉冲星的空间飞行器自主导航技术研究

研究了利用X射线脉冲星实现空间飞行器自主导航的原理,指出通过测量脉冲星发射的脉冲到达航天器与到达太阳系质心的时间差可以确定该航天器的位置。给出了两种适合用于处理脉冲星观测量的方法,即基于最小二乘(LS)的方法和基于卡尔曼滤波(KF)的方法。通过数值仿真验证了X射线脉冲星自主导航技术的可行性,并且说明采用KF算法能够有效利用卫星轨道运动方程中包含的导航信息,从而获得更高的导航精度。     

用GPS评定IMU（惯性测量装置）误差

在导弹飞行试验时，基于ＧＰＳ的弹道基准系统可替代常规雷达。由于ＧＰＳ弹道基准的精度高，所以可用来评定导弹惯性测量装置的性能。在两发现役的和平保卫者导弹发射前配置了ＧＰＳ转发器和三波段天线。根据ＧＰＳ测量的矩离、矩离增量数据，用卡尔曼滤波方法评定各个ＩＭＵ误差，结果证明ＧＰＳ优于雷达。     

Adaptive Square-Root Cubature–Quadrature Kalman Particle Filter for satellite attitude determination using vector observations

A novel algorithm is presented in this study for estimation of spacecraft?s attitudes and angular rates from vector observations. In this regard, a new cubature–quadrature particle filter (CQPF) is initially developed that uses the Square-Root Cubature–Quadrature Kalman Filter (SR-CQKF) to generate the importance proposal distribution. The developed CQPF scheme avoids the basic limitation of particle filter (PF) with regards to counting the new measurements. Subsequently, CQPF is enhanced to adjust the sample size at every time step utilizing the idea of confidence intervals, thus improving the efficiency and accuracy of the newly proposed adaptive CQPF (ACQPF). In addition, application of the q-method for filter initialization has intensified the computation burden as well. The current study also applies ACQPF to the problem of attitude estimation of a low Earth orbit (LEO) satellite. For this purpose, the undertaken satellite is equipped with a three-axis magnetometer (TAM) as well as a sun sensor pack that provide noisy geomagnetic field data and Sun direction measurements, respectively. The results and performance of the proposed filter are investigated and compared with those of the extended Kalman filter (EKF) and the standard particle filter (PF) utilizing a Monte Carlo simulation. The comparison demonstrates the viability and the accuracy of the proposed nonlinear estimator.     

用GPS信息的惯导快速对准方法

如何快速、准确地完成惯导系统的初始对准一直是惯导系统研究的关键技术，方位对准精度和对准时间的矛盾至今未能很好地得到解决。为解决这一问题，本文提出了双全球定位系统（ＧＰＳ）同惯性导航系统（ＩＮＳ）进行深组合的方法。仿真结果表明，该方法使方位对准时间缩短为不到２ｍｉｎ，精度达到１４．６７（″），较好地解决了方位对准问题，同时也提高了导航精度。     

Robust extended Kalman filter with input estimation for maneuver tracking

This study investigates the problem of tracking a satellite performing unknown continuous maneuvers. A new method is proposed for estimating both the state and maneuver acceleration of the satellite. The estimation of the maneuver acceleration is obtained by the combination of an unbiased minimum-variance input and state estimation method and a low-pass filter. Then a threshold-based maneuver detection approach is developed to determinate the start and end time of the unknown maneuvers. During the maneuvering period, the estimation error of the maneuver acceleration is modeled as the sum of a fluctuation error and a sudden change error. A robust extended Kalman filter is developed for dealing with the acceleration estimate error and providing state estimation. Simulation results show that, compared with the Unbiased Minimum-variance Input and State Estimation (UMISE) method, the proposed method has the same position estimation accuracy, and the velocity estimation error is reduced by about 5 times during the maneuver period. Besides, the acceleration detection and estimation accuracy of the proposed method is much higher than that of the UMISE method.     

DESIGN & REALIZATION ON GPS/INS INTEGRATED NAVIGATION SYSTEM

讨论了应用卡尔曼滤波器的ＧＰＳ／ＩＮＳ组合导航系统，其中包括理论、方案与实际的ＩＮＳ和ＧＰＳ接收机的结合，研究的重点是对系统误差的建模及组合的实现，以及松组合和紧组合等各种组合方式等。该ＧＰＳ／ＩＮＳ组合导航开发系统，可以有效和经济地用于组合导航系统的研究和设计，在实际应用中起到了非常有效的作用。该系统不仅仅是一个计算机辅助设计软件，而且可以对实际获得的惯导和ＧＰＳ数据进行半物理仿真。开发系统的核心软件可以方便地转换成实际组合系统中的工程应用软件。应用结果表明，开发系统的设计思想和组合方案是成功的，可以取得良好的导航结果。     

一种基于强机动的目标跟踪改进算法

针对传统目标跟踪算法鲁棒性较差等问题,提出了一种基于当前统计模型的无迹卡尔曼滤波交互式多模型(IMM-CS-UKF)融合算法。在交互式多模型算法框架内,计算当前统计模型的概率,提高了统计模型的目标加速度和自适应性。该算法结合了交互式多模型和无迹卡尔曼滤波算法,具有对不同机动模式目标的自适应跟踪能力和精度高等优点。仿真结果表明,该算法对以多种机动策略实时机动的目标具有较好的跟踪性能。     

基于星间测距的编队卫星一致性导航算法

针对多航天器编队飞行的自主导航问题,利用高精度的相对距离测量手段,结合较少的参考卫星位置信息,对未知卫星的相对和绝对位置进行估计.针对扩展卡尔曼滤波算法的局部不稳定性,采用了一种误差补偿算法,使在系统可观度较低时仍有较稳定的输出.并将编队系统视为一个无线网络,提出了一种分布式一致性卡尔曼滤波算法,该算法结合一致性理论和分布式卡尔曼滤波器,可明显提高解算精度并消除高频噪声干扰,仿真结果验证了该方法的有效性与可靠性.     

Filters for manufacturability in design optimization of variable stiffness composites

In the design optimization of variable stiffness composites, manufacturing constraints imposed by the automated fiber placement technology must be considered. In the present paper, two filters are proposed to address this issue, and they are incorporated into the Shepard interpolation-based design optimization framework developed in our previous studies. The fiber angle arrangement of a composite is represented by a continuous function that interpolates fiber angles at scattered design points. Two filters are appointed for each design point to deal with two typical manufacturing constraints, i.e., fiber curvature and gap/overlap. At each design point, the sensitivity is first filtered in a rectangular region around this point, and by this means the fiber curvature is controlled; then in another rectangular region around this design point, the filtered sensitivities are averaged, and the result is used to update the corresponding design variable. Several numerical examples are investigated, and the results show that the proposed method is effective.