基于3D Zernike矩的巡检器与空间站的相对导航算法

针对航天器相对导航问题,以空间站表面为"特殊地形",提出一种基于大型航天器表面巡检的相对导航算法。首先,运用巡检飞行器上的TOF （Time of Flight）相机测量空间站表面局部点云数据,以该点云数据为实时图,以空间站表面先验点云数据为基准图。然后,利用3D Zernike矩与三维地形间的一一对应关系,将三维地形匹配转化为基于3D Zernike矩的特征向量匹配。在此基础上求解实时图与匹配上的基准图间的相对位置、相对姿态,从而确定两航天器间的相对导航参数,并通过实验分析了匹配精度及速度的主要影响因素。最后,将该相对导航参数与惯性系统推算的相对导航参数在扩展卡尔曼滤波器的框架下实现信息融合,估计了巡检飞行器与空间站间的相对位置、相对姿态,实验结果表明,相对位置精度优于0.002 m,相对姿态精度优于0.1°。     

地形辅助制导系统

本文叙述一种地形辅助制导系统,用来修正惯性系统或其它导航系统的误差,以提高飞行器的制导精度。这种辅助系统含有一个卡尔曼滤波器,它将飞行器所飞过的实际地形信息与预存的地图进行比较和处理,从而估计出导航系统的误差。对于一般的丘陵地形,辅助制导后的精度可达到数十米的范围。它适用于飞机、巡航导弹、弹道导弹和其它武器运载系统,而且所需的设备简单,易于实现。     

水下重力匹配定位算法综述

随着重力测量和水下导航技术的发展,惯性/重力匹配导航技术因其精度高、自主性强和航时长等优点,已成为水下自主导航的重要研究方向。惯性/重力匹配导航系统主要由惯性导航系统、重力实时测量、海洋重力场背景图和重力匹配定位算法构成。重力匹配定位算法通过将实时测量的重力异常值与构建的重力场背景图进行匹配,得到水下运载体当前时刻的位置信息,是惯性/重力匹配导航技术的核心。本文详细介绍了重力匹配算法的技术发展现状,重点分析了具有代表性的ICCP算法、SITAN算法、矢量匹配算法及其衍生算法,并对惯性/重力匹配水下自主导航技术的未来发展进行了展望。     

Robotic Air Vehicle: A Pilot's Perspective

This paper focuses on concepts and technologies required to develop a robotic air vehicle (RAV). A vehicle of this type has the capability to be a launch and forget weapon system. The authors are engineers and pilots so they view both the technical approach and piloting issues with equal importance. RAV must have the machine intelligence to make decisions within the mission and battlefield constraints. This requires a piloting expert system and route planner to perform passive terrain following, terrain avoidance, obstacle avoidance, and autonomous navigation based on low cost sensor inputs such as a multifunction FLIR, digital terrain map, and directional reference systems. RAV is a cost effective way to fight in a threat environment where aircrew loss rates would be unacceptable. RAV provides the Air Force a means to expand its combat capabilities.     

大动态干扰下基于光学图像的自主导航技术

针对高超声速飞行器在平流层内飞行过程中自主天文导航时,气动光学效应及运动模糊等大动态干扰严重影响观星和高精度导航的问题,提出一种基于正则化思想的高超星图半盲复原改进算法。该算法首先借助已有的高超星图模糊核提取算法获得先验模糊核,为复原提供便利条件。接着结合天文图像灰度及梯度的稀疏先验分布特性,设计了一种针对高超星图的正则化盲复原模型,并结合先验模糊核所提供的信息,构建了改进的半盲复原方法,能在先验模糊核精度较低或缺失时转化为盲复原方法,提高了算法的鲁棒性。将本算法与传统星图复原算法、其他最新正则化复原算法进行星图复原与导航效果比较,数值仿真结果显示本算法的复原效果更佳,峰值信噪比（PSNR）达到36.97,并且质心提取成功率达到99.23%,能够明显改善星图识别的成功率,从而大幅提升高超声速飞行器在平流层中的大动态干扰下的自主导航能力。     

AUV的图优化海底地形同步定位与建图方法

海底地形辅助导航技术可为智能水下机器人(AUV)的长时间水下作业提供有界精确导航结果,且无需声学基阵辅助。然而,地形辅助导航需要已知高精度先验海图,这大大限制了其应用范围。为解决海底地形未知条件下的海底地形辅助导航问题,提出了海底地形同步定位与建图技术。利用水深预测手段和地形匹配方法进行帧间数据关联构建和闭环检测,并通过图优化技术进行海底地形同步定位与建图问题求解。仿真试验结果显示,在航行1h后,海底地形同步定位与建图系统的建图结果中所有测深点定位误差均值约为13m。     

Adaptations of a comparison technique for terrain navigation

This paper deals with a terrain navigation technique based on the comparison of terrain height measurements with a reference map. The comparison can be either based on minimum absolute differences, minimum square differences or on cross correlations. This paper will give an introduction to these methods and state some important adaptations. The first adaptation increases the independence of the terrain navigation system by calculating the position hypothesis only based on previous position measurements and the strap-down velocity. The second adaptation uses a detailed search to increase the performance and the reliability of the terrain navigation system. Both adaptations are important steps to a higher integrity of modular terrain navigation systems.     

Fuzzy corrections in a GPS/INS hybrid navigation system

A new concept regarding GPS/INS integration, based on artificial intelligence, i.e. adaptive neuro-fuzzy inference system (ANFIS) is presented. The GPS is used as reference during the time it is available. The data from GPS and inertial navigation system (INS) are used to build a structured knowledge base consisting of behavior of the INS in some special scenarios of vehicle motion. With the same data, the proposed fuzzy system is trained to obtain the corrected navigation data. In the absence of the GPS information, the system will perform its task only with the data from INS and with the fuzzy correction algorithm. This paper shows, using Matlab simulations, that as long as the GPS unavailability time is no longer than the previous training time and for the scenarios a priori defined, the accuracy of trained ANFIS, in absence of data from a reference navigation system, is better than the accuracy of stand-alone INS. The flexibility of model is also analyzed.     

雷达威胁环境下的无人机三维航迹规划

提出了一种雷达威胁环境下应用A*算法进行低空突防三维航迹规划的方法。首先对地形高程数据进行综合平滑处理,建立满足无人机机动性能要求的安全飞行曲面,并结合雷达威胁量化模型,计算出地形遮蔽雷达盲区的范围,最后在满足地形遮蔽雷达盲区的安全飞行曲面上运用A*算法规划出三维飞行航迹。仿真结果显示,该算法能简单、快速地获得三维最优航迹,易于工程实现。     

On-Line Vehicle Motion Estimation from Visual Terrain Information Part I: Recursive Image Registration

This paper addresses estimation of motion from the optical flow observed by an airborne down looking electro-optical sensor. The paper is in two parts. Part I addresses the development and analysis of a velocity-to-height ratio estimation algorithm and its principal error characteristics. In part II, it is shown how the information provided by the motion estimator can be integrated with additional on-board sensors to provide a complete autonomous navigation system. Part I as presented here is a summary version of the full length paper.? The algorithm implements recursive registration of successive images by using the gradient of a similarity function between them to control the tracking of their relative shift. The shift estimate provides velocity/height information. Substantial saving in memory and computation as compared to conventional full frame registration is achieved by using only a single line in the TV frame. Stochastic mathematical models for the image, terrain and vehicle velocity perturbations are used in the analysis. The choice of the most appropriate similarity function in the registration algorithm is addressed. Performance analysis indicates very small error variances, as illustrated by numerical examples.     

基于TERCOM-ICP联合算法的水下地形匹配方法研究

水下地形辅助导航一直是应用于AUV的热点和前沿问题，有助于修正惯导随时间积累的定位误差，以实现精确的导航定位。对经典地形匹配方法TERCOM算法进行了简单的介绍，引入点云配准领域的ICP算法，针对多波束测深系统可以获取地形剖面的特点，提出了一种TERCOM-ICP联合匹配算法。首先使用TERCOM算法粗匹配，将粗匹配后的大致位置作为指示输入ICP算法中进行精匹配，通过仿真实验对TERCOM算法的匹配结果和ICP算法的匹配时间作对比分析。仿真结果表明：TERCOM-ICP算法可以有效提高水下地形匹配精度，经过仿真实验测试，平均匹配误差可以达到20 m以内，所用时间在160 s以内，验证了该算法应用在水下地形匹配领域的可行性，更好地满足了水下辅助导航的要求。     

A Dual-Mode Routing Algorithm for an Autonomous Roving Vehicle

A dual-mode algorithm for routing an unmanned autonomous roving vehicle designed to explore the uncertain terrain of other planets is presented. The algorithm consists of a global mode, which uses dynamic programming and terrain information available from photo reconnaissance data to determine a nominal optimal path, and a local mode, which routes the vehicle around obstacles whose presence, location, and extent are not known in advance. Gaussian probability density functions are used to simulate terrain for examples that illustrate the performance of the algorithm.     

An overview of a Global Positioning System Mission Plannerimplemented on a personal computer

The Global Positioning System (GPS) Mission Planner (GMP) program, which has been implemented on an IBM PC, is described in terms of its features and architecture, and sample outputs are presented. The GMP was written to permit operational units to plan missions and to accomplish survivability and navigation assessments based on realistic trajectories, GPS almanac data, broadband jammer specifications, and digital terrain elevation data (DTED). GMP supports trajectory generation for generic air, land, or naval vehicles and has `sanity' checks for altitude acceleration, terrain slope, and velocity limits. A survivability measure is computed based on exposure time to various threat types. Yuma-type almanac data are used to support the GMP to define GPS satellite orbits. Jammers, threats, and trajectory wavepoints may be defined by either keyboard entry (e.g. longitude, latitude, and altitude) or via mouse and cursor on a displayed pseudo-color DTED map on the PC monitor. Satellite visibility and best dilution-of-precision (DOP) are computed using DTED. jammer visibility and power levels at the vehicle are similarly computed. A realistic body masking and antenna gain model is used to compute carrier-to-noise densities for each visible satellite. A navigation assessment program emulates a multichannel receiver to generate position and velocity measurement uncertainties. An integrated Kalman filter generates position and velocity navigation estimates. Results are graphically displayed to the operator     

一种地图匹配算法的设计与实现

设计一种面向定位定向导航系统的地图匹配算法,首先通过网格划分和建立路段连通性拓扑关系表对电子地图数据进行预处理;然后根据车辆的行驶状态采取不同的候选路段确定方法,计算各候选路段的匹配度,取值最大的作匹配路段;最后采用垂直投影法求取匹配点。通过跑车数据进行仿真试验,验证了该算法具有良好的准确性和实时性。     

On-line Vehicle Motion Estimation from Visual Terrain Information Part II: Ground Velocity and Position Estimation

An algorithm, combining velocity/height estimates, obtained from an airborne body fixed image shift estimator with auxiliary on-board measurements and sparsely stored terrain profile information constitutes an entirely passive autonomous navigation system suitable for moderate-g flight missions. Two versions are addressed. The "naive estimator," in which altitude estimates are multiplied by velocity/height estimaters, yields ground velocity. Position, obtained by integration, diverges with time. The "extended Kalman filter" (EKF) version, in which velocity and position are defined as state space components, locks on the stored terrain profile and does not diverge with time. It degenerates into the "naive estimator" if the terrain is completely flat. Numerical examples indicate excellent performance potential of the EKF estimator.     

Analysis of single-platform passive emitter location with terraindata

Frequency measurements made at a moving platform can be used to locate an emitter. An error ellipsoid analysis is used to compare the performance under three levels of a priori information on the emitter's altitude: (1) no knowledge, (2) terrain data, and (3) complete knowledge of the emitter's altitude. The analysis is performed for two simple platform paths that provide frequency measurements that are approximately time reversed versions of one another. When no a priori knowledge is available there is little difference between the performance when the platform maneuvers on a concave circular path or on a convex circular path and the performance depends very Little on the platform altitude. However, when some a priori altitude information is available the performance is markedly different on the two paths and is highly dependent on the platform altitude. Thus, this analysis provides the unexpected result that for seemingly similar platform paths, the performance can vary markedly when the emitter altitude is assumed known. Also, an interesting result is that for some cases it is possible to achieve better x-y accuracy when using terrain data than when the emitter's z location is known, because the terrain data provides terrain slope information. These cases are characterized in terms of the terrain slope at the emitter     

地形景象匹配辅助导航可视化仿真研究及软件实现

为了直观有效验证地形景象匹配算法和演示地形辅助导航的过程,设计了地形景象辅助导航可视化仿真软件系统.利用Visual C 和OpenGL的功能实现了对导航数据和飞行过程的动态二维可视化曲线显示,对匹配区域中的实测图和参考图进行动态显示,能够直观地分析匹配结果的正确性;并在此基础上着重对地形景象匹配辅助导航过程实现了可视化仿真显示,能形象直观地演示地形景象辅助导航的过程及其性能.通过多次试验表明,该软件能很好地演示地形景象辅助导航系统的全过程及其性能,具有很好的实际应用价值.     

GPS based prediction of the instantaneous impact point for sounding rockets

As part of the range safety operations during a sounding rocket launch, a real-time prediction of the instantaneous impact point (IIP) is performed to monitor the expected touch down point in case of a boost termination. Supplementary to traditional radar tracking, the IIP prediction is nowadays based on GPS navigation data, which offer an inherently higher accuracy and reduced data noise. To comply with the increased tracking performance, a consistent set of equations suitable for real-time computation of the approximate IIP is established. Aside from a consideration of gravitational forces, reference frame rotation and Earth curvature, the model can also account for drag during the ascent trajectory provided that a priori information on the ballistic properties of the launch vehicle is available. The algorithm is tested for a representative set of mission profiles and applied to GPS flight data of an Improved Orion rocket and a Maxus rocket launched at Esrange, Kiruna.     

基于联邦滤波的SINS/GNSS/OD/高度计多源组合导航算法研究

针对城市情况下车载导航时单一导航源易受干扰的问题,提出了一种基于自适应联邦Kalman滤波的多源组合导航算法.该模型具有两级结构,由子滤波器进行各信息源局部估计后,通过主滤波器进行最优融合估计.融合具有不同工作特点的导航传感器的输出信息组成多源信息组合导航系统,从而提高了导航系统的精度和鲁棒性,且通过故障诊断算法实时检测并隔离故障信息源.给出了联邦滤波算法设计,并进行了实际车载实验.实验结果表明,该算法能够提高导航系统的稳定性及精度.     

基于室内合作场景智能识别的行人导航算法

基于足绑式惯性测量单元(IMU)的惯性导航系统被广泛应用于行人导航中,其通过零速修正(ZUPT)算法可对速度估计误差进行较好的补偿,然而其位置误差会随时间发散。针对于此,提出了一种基于室内合作场景智能识别的行人导航算法。通过随机森林算法,对行人在室内平地步行、上楼梯、下楼梯等不同步态进行训练与辨识,并结合室内先验地图对行人导航的结果进行校正。通过实验表明,行人在室内行走1100m时最大定位误差为1.85m(总行程0.17%),相对无场景识别的方法精度提高了6倍,可以有效提高行人导航精度。