星际着陆自主障碍检测与规避技术

 为了在具有科学价值的复杂地形区域实现安全着陆,未来的星际着陆器必须具备自主障碍检测与规避的能力。从星际着陆导航传感器技术、自主障碍检测方法和自主障碍规避技术3个方面出发,对星际着陆自主障碍检测与规避技术进行较全面的分析和总结。首先,对适用于星际着陆自主障碍检测的各种主动式和被动式传感器的工作原理、优缺点进行较深入的阐述;接着,基于不同传感器的测量信息,对各种自主障碍检测方法的障碍检测能力、优缺点进行较详细的对比分析;然后,基于多信息融合的自主障碍检测方法,对安全着陆点选择的原则进行阐述;最后,对星际着陆自主障碍规避流程和适用于星际着陆自主障碍规避的制导控制方法进行较系统的总结。     

Vision-aided inertial navigation for pinpoint planetary landing

Autonomous and safe landing spacecraft on moon and planetary bodies is a rather difficult and risky task. Accurate relative navigation between the spacecraft and the planetary surface is essential, together with the autonomous hazard detection and avoidance. This paper describes the vision-aided inertial navigation (VAIN) scheme to meet the pinpoint landing requirement of the next generation planetary lander. Images of distinctive surface feature called feature points/landmarks are detected and tracked autonomously to improve the performance of inertial navigation. Landmark image information derived from optical navigation camera and the spacecraft state information sensed by IMU (Inertial Measurement Unit) are integrated in extended Kalman filter algorithm. The validity of the proposed navigation scheme is confirmed by computer simulation.     

Determination of Spacecraft Landing Footprint for Safe Planetary Landing

A methodology is developed based on a ballistic analysis to estimate the landing footprint associated with the powered terminal descent phase of a spacecraft soft landing. The analysis is based on an idealized two-impulse thrust maneuver and leads to an analytical expression for the elliptical boundary of the landing footprint. The objective is to develop a computationally efficient method to estimate the landing footprint for use in an on-board fuzzy-logic based inference engine for real-time hazard avoidance. The inference engine combines an estimate of the landing footprint with information about the safeness of the landing terrain to construct an overall landing site quality index. The landing site quality index is a critical parameter that enables the spacecraft to make intelligent real-time decisions about landing safely on unknown and hazardous terrains. The footprint generated from the ballistic analysis is also compared with the footprint resulting from numerically integrating a representative guidance law.     

A fusion and learning algorithm for landing aircraft tracking:compensating for exhaust plume disturbance

An algorithm is presented for tracking a landing aircraft using fusion of two different passive sensors, a laser range finder (LRF) and a forward-looking infrared (FLIR) camera. The main feature of this algorithm is its ability to identify and compensate for an exhaust plume disturbance. The algorithm is based on the extended Kalman filter (EKF) and the filtering confidence function (FCF) which introduces a learning approach to the tracking problem. The results of a simulation using the learning tracking algorithm and the EKF alone are presented and compared     

一种基于相邻模块化加权D-S的融合诊断方法

常规D-S (Dempster-Shafter)决策融合方法由于其自身理论不足,不能很好直接处理决策结果偏差大、冲突大的传感器融合问题,因而对于信息高冲突情况下的转子微弱故障融合诊断存在着失效问题。针对该类问题与不足,借鉴复杂网络的舆论传播、社会学习理论及多智能体一致性决策的相关概念与思路,从避免决策结果冲突大的传感器直接进行融合的角度进行改进,提出相邻模块化加权D-S融合方法。该方法首先根据初步结果进行相邻节点与模块划分,只有决策距离在相邻界限值范围内的相邻模块节点才能进行决策融合;对于同一模块内相邻节点,根据各节点决策权重及初步决策结果采用加权D-S融合方法进行决策融合;针对融合结果再进行相邻节点模块划分与融合,依此步骤进行循环划分与融合,直到所有模块与节点均不相邻;最后采用专家权威决策方法确定权重和最大的模块融合结果作为最终的传感器网络一致性决策结果。通过多传感器网络的转子故障模拟实验对所提方法进行验证,应用结果表明:所提方法可以较好解决少数传感器诊断正确、而多数诊断错误的信息高冲突条件下的局部微弱故障融合诊断问题。     

Soft landing stability analysis of a Mars lander under uncertain terrain

Safe soft landing of the lander is vital to the Mars surface exploration mission. Analysis and verification of the landing stability under uncertain terrain play an important role in lander design. However, the effect of uncertain terrain is ignored in most existing studies, making the analysis incomprehensive and increasing the risk of landing failure in practice. In this paper, a Mars lander with 10 attitude control thrusters is introduced and its dynamics model is then established considering...     

Data mining as a foundation for science-enabling autonomy

In-situ exploration by spacecraft and planetary rovers will increasingly require knowledge "on demand" in the future as downlinlk constraints limit the amount of information that can be transmitted from these platforms back to Earth. Several on-board processing methods have the potential to significantly enhance scientific results in these settings. They include automatic detection Of natural satellites of planetary bodies, investigation of possible surface motions on planets and planetary moons, and directed acquisition Of scientific data by planetary rovers. The key ingpredient in all three cases is the need to process scientific data directly on-board, so that information can be rapidly provided to an automated spacecraft ex~ecutive and/or to ground-based Principal Inesiators (pis). We discuss, herein, recent developments in data mining technology that were designed initially for ground-based scientific data analysis. We then outline how these ideas can be migrated to on-board platforms to dramatically enhance the scientific capabilities of autonomous spacecraft.     

Terrain modeling for microwave landing system

A powerful analytical approach for evaluating the terrain effects on a microwave landing system (MLS) is presented. The approach combines a multiplate model with a powerful and exhaustive ray tracing technique and an accurate formulation for estimating the electromagnetic fields due to the antenna array in the presence of terrain. Both uniform theory of diffraction (UTD) and impedance UTD techniques have been employed to evaluate these fields. Innovative techniques are introduced at each stage to make the model versatile to handle most general terrain contours and also to reduce the computational requirement to a minimum. The model is applied to several terrain geometries, and the results are discussed     

基于CCD着陆相机的行星软着陆岩石检测与规避方法

 提出了一种基于CCD相机的行星软着陆岩石检测与规避方法。首先,利用多分辨率分析方法对着陆区图像进行快速处理,根据着陆区的光照特性检测出着陆区的岩石,针对着陆过程的时间需求,多灰度阈值分割方法被采用;其次,基于无监督聚类算法对着陆区的岩石进行识别并标记,构建着陆区岩石分布的拓扑图;再次,利用激光测距仪得到的高度信息和着陆相机的参数,计算着陆区岩石拓扑图的实际危险区域面积,从而根据着陆器的需求安全范围和探测任务需要,利用安全着陆点的螺旋式搜索方法选择具有冗余度的安全着陆点;最后,建立着陆器安全规避策略,制导控制着陆器进行安全着陆,通过对安装侧向发动机和利用万向节调节推力方向的主发动机两种情况的仿真,实验结果令人满意。     

某型轰炸机空滑迫降分析

某型轰炸机空滑迫降的可能性是存在的，但其中涉及到飞行安全的问题。为了保证迫降安全，讨论了空滑迫降性能的估算方法，分析了迫降航线的建立和飞行方法。针对场内迫降、场外迫降和水上迫降等不同迫降场的特点，系统研究了迫降操纵的主要问题，提出了迫降操纵建议，为飞行员提供参考。     

基于联邦卡尔曼滤波的测量船导航信息处理方法

为了提高航天测量船导航系统提供的位置、姿态及速度的精度,以满足飞行器测控的特殊要求,从信息融合的角度进行分析,针对多传感器信息融合技术在工程中的应用作进一步探讨,提出了基于信息融合技术的组合导航方案,构造了INS／CNS／GPS／DVL组合导航系统滤波体系结构,构建了误差模型,阐述了融合算法。仿真及实测数据证明,设计的联邦滤波器可以充分利用各种冗余信息,提高导航的数据精度。     

Optimal and self-tuning information fusion Kalman multi-step predictor

Based on the optimal fusion algorithm weighted by matrices in the linear minimum variance (LMV) sense, a distributed optimal information fusion for the steady-state Kalman multi-step predictor is given for discrete linear stochastic control systems with multiple sensors and correlated noises, where the same sample period is assumed. When the noise statistics information is unknown, the distributed information fusion estimators for the noise statistics parameters are presented based on the correlation functions and the weighting average approach. Further, a self-tuning information fusion multi-step predictor is obtained. It has a two-stage fusion structure. The first-stage fusion is to obtain the fused noise statistics information. The second-stage fusion is to obtain the fused multi-step predictor. A simulation example shows the effectiveness.     

低能量状态对飞行安全的危害及改出方法

对民机在进近着陆阶段可能诱发飞行事故的低能量状态和驾驶员的改出操纵方法进行了研究。根据近年的民机事故分析报告,结合运输类飞机适航标准CCAR-25-R4、飞行试验指南AC25-7C、军用规范及相关行业标准,较系统地提出了涉及着陆拉平、侧风着陆和可控撞地的低能量状态的定量判定准则。以某型支线客机为例,采用数字仿真计算的方法,分别研究了在进近着陆过程中低动能和低势能状态可能导致的飞行安全问题及其特点。针对低动能改出提出了增加速度并抑制爬升的方法,针对低势能改出提出了增大俯仰姿态并保持速度的方法,最后通过仿真计算验证了两种改出方法的有效性。研究结果可为低能量告警系统的设计和驾驶员的改出操纵培训等提供理论参考。     

基于仿生的适于特殊地形的直升机起落架设计

现阶段直升机起落架主要采用轮式起落架和滑撬式起落架,由于机动性和灵活性较差,导致直升机起降时对地面的平整度及坡角要求较高,在遇到某些特殊地形如乱石滩、斜坡坡度较大地带可能面临无法正常起降这一困难。本文受某些仿生无人机起落架设计启发,提出了一种新型直升机起落架的设计方法,此种起落架采用三立柱支撑结构,主体是三个位于机身底部的液压伸缩支撑杆,在直升机降落时杆端的传感器与主控配合来动态控制支撑杆的伸缩长度。此种起落架通过控制每根液压杆伸缩不同的长度来适应不同环境下的崎岖地形,使直升机在乱石滩及大坡度地面起降成为可能。经过设计举例及受力分析,得出本设计方法在工程上是可以实现的,并且在直升机抗震性能的提升方面也有一定作用。     

航天器返回地球的气动特性综述

航天器返回地球的飞行过程中,气动特性是实现将宇宙飞行速度减到落地前速度、保证再入飞行得到有效控制以及再入防热安全可靠的关键因素。针对简单旋成体气动外形、半弹道式再入控制、烧蚀防热类返回航天器,综述了返回地球过程中变化的空气流域特性、航天器周围的气体绕流环境、空气与航天器作用产生的动力学与热效应等。系统地给出了该类航天器的再入气动特性参数与飞行性能的共性规律,包括:气动阻力与再入减速、气动升力与再入轨迹控制、配平攻角与飞行稳定性、气动加热与防热,以及再入过程中不同气动特性航天器、气象条件变化等对再入飞行性能的影响规律。为航天器开展返回飞行过程的跨流域气动性能工程研制提供设计参考。     

基于高斯伪谱法的翼伞系统复杂多约束轨迹规划

翼伞系统在实际环境中飞行时易受到风场以及地形环境等复杂干扰的影响,无法精确归航,控制难度较大。针对该问题,提出了一种针对复杂多约束条件的翼伞系统的最优控制轨迹规划方法,可同时实现翼伞系统在复杂环境下逆风对准、精确着陆以及控制量全局最优的控制目标。首先,建立了风场干扰下的翼伞系统模型;然后,通过引入地形环境曲面,将复杂环境转化为实时路径约束,将轨迹着陆偏差以及逆风雀降转化为终端约束,并考虑控制量消耗最小为目标函数,以此将复杂环境下的翼伞系统的轨迹优化转化为一系列非线性的带有复杂约束的最优控制问题;最后,采用高斯伪谱法将多约束最优控制问题转化为易于求解的非线性规划问题。通过设立3组复杂环境仿真实例和实验验证,表明本文方法使翼伞系统在多种较恶劣的复杂环境中有效应对多类约束条件,规划出控制量全局最优的可行轨迹。与已有的混沌粒子群优化算法相比,本文方法具有较好的最优性和较高的精度。     

着陆小行星的视线测量自主光学相对导航算法及其可观性分析

 以软着陆小行星为工程应用背景,提出了基于视线(LOS)测量的自主光学相对导航算法,并对导航算法的可观性进行了比较深入的分析研究。首先,基于透视投影模型的共线方程,给出了导航测量方程和测量敏感矩阵;接着,通过多个视线矢量的测量,应用高斯最小二乘微分修正(GLSDC)和龙贝格-马尔塔(LM)算法对探测器的位置和姿态参数进行了估计。然后,通过对误差方差阵逆矩阵秩的分析,比较详尽地分析了不同数量视线观测条件下导航算法的可观度和可观性。最后,通过数学仿真对所提出的自主导航算法的可行性进行了验证。     

Architectures and algorithms for track association and fusion

Target tracking using multiple sensors can provide better performance than using a single sensor. One approach to multiple target tracking with multiple sensors is to first perform single sensor tracking and then fuse the tracks from the different sensors. Two processing architectures for track fusion are presented: sensor to sensor track fusion, and sensor to system track fusion. Technical issues related to the statistical correlation between track estimation errors are discussed. Approaches for associating the tracks and combining the track state estimates of associated tracks that account for this correlation are described and compared by both theoretical analysis and Monte Carlo simulations     

Tracking with distributed sets of proximity sensors using geometric invariants

We propose a new approach to forming an estimate of a target track in a distributed sensor system using very limited sensor information. This approach uses a central fusion system that collects only the peak energy information from each sensor and assumes that the energy attenuates as a power law in range from the source. A geometrical invariance property of the proximity of the distributed sensors relative to a target track is used to generate potential target track paths. Numerical simulation examples are presented to illustrate the practicality of the technique.     

基于改进D-S证据理论的航空发动机转子故障决策融合诊断研究

针对单一传感器的测量信息难以准确、全面地反映航空发动机转子、轴承和齿轮的工作状况,进而造成振动故障诊断难度大的问题,提出安装多个振动传感器组成传感器网络,建立基于多传感器信息的发动机转子故障决策融合诊断系统。由于多传感器系统不可避免地会存在各传感器信息不一致、信息冲突的情形,因此针对该融合诊断系统的信号测量、信息预处理、特征提取、故障诊断及决策融合5个环节,重点研究了决策融合环节的Dempster-Shafer（D-S）证据决策融合方法存在的冲突证据融合失效问题。通过分析原因,从避免“一票否决”现象和证据加权平均两个方面进行改进,提出了改进D-S证据融合方法,并应用于航空发动机转子的模拟故障决策融合诊断中。结果表明基于D-S证据理论对3个传感器的单一诊断结果进行决策融合,能得到比任一单个传感器更准确、可靠的结果;而改进D-S证据融合方法由于能在一定程度上克服冲突证据融合带来的失效问题,且能同时兼顾处理好非冲突证据的融合,故其对于证据冲突和非冲突情形都取得了较好的融合效果,因此总的分类正确率要高于常规D-S算法和PCR5算法。