Using natural features for vision based navigation of an indoor-VTOL MAV

The use of natural features for vision based navigation of an indoor Vertical-Take-Off-and-Landing (VTOL) Micro Aerial Vehicle (MAV) named Air-Quad is presented. Air-Quad is a small four-rotor helicopter developed at the ITE.Such a helicopter needs reliable attitude information. The measurements of the used MEMS gyroscopes and accelerometers are corrupted by strong noise. To be useful, the MEMS sensors have to be part of an integrated navigation system with aiding through complementary sensors like GPS or the computer vision module presented here.In the computer vision module, feature points are detected and tracked through the image sequence. The relative rotation and translation of the camera are estimated using the two-dimensional motion of the feature points.The three-dimensional points in the scene are modeled with the image coordinates of their first sighting and their inverse depths. Only these inverse depths are estimated for the feature points. An efficient sparse bundle adjustment algorithm is used to improve the estimation of the scene structure and the navigation solution.It is shown that the use of the computer vision module greatly improves the navigation solution compared to a solution based only on MEMS sensors.     

Prototype personal navigation system

Honeywell Laboratories recently funded the development of a prototype personal navigation system based on MEMS technologies. The system components include a MEMS inertial measurement unit, a three-axis magnetometer, a barometric pressure sensor, and a SAASM GPS receiver. The system also uses Honeywell's human motion-based pedometry algorithm. The navigation process is based on a strap-down inertial navigator aided by feedback from a Kalman filter using typical measurements from the GPS, magnetometer and barometer when available. A key innovation is the addition of an independent measurement of distance traveled based on the use of a human motion algorithm. The navigation system combines the best features of dead reckoning and inertial navigation, resulting in positioning performance exceeding that achieved with either method alone. Subsequent to the Honeywell effort, DARPA funded an individual Personal Inertial Navigation System (iPINS) seedling program. Honeywell worked to improve the baseline personal navigation system with the objective of demonstrating the feasibility of reliably achieving navigation accuracy < 1 % of distance traveled in GPS-denied scenarios. In addition, an analysis was conducted to determine the benefit of incorporating terrain correlation into the personal navigation system. The results of this analysis indicate that overall navigation accuracy can be significantly improved through the application of terrain correlation. This presents an are presented. In addition, conclusions from the terrain correlation analysis conducted under the iPINS seedling program are included.     

MEMS惯测技术在管道测绘系统中的应用

针对小口径管道的测绘问题,提出了一种MEMS惯测装置在小管道测绘系统中应用的方法,直接利用地标点信息为MEMS惯测装置装订初始方位,采用因子图理论对惯性/里程计组合导航信息进行处理,通过后续处理对装订误差进行修正,解决了MEMS惯测装置无法完成初始对准的问题。给出了惯性/里程计组合导航的因子图以及和积算法递推公式,并通过牵引试验对所提方法进行了验证。试验结果表明,提出的应用方法能够有效解决小口径管道的测绘问题,在100m间隔的路标点条件下,单边定位精度能够达到5cm。     

微小型飞行器惯性组合姿态确定与航路导航研究

构建了微小型飞行器(MAV)导航、制导与控制(GNC)系统。研究了微惯性导航测量单元零偏的温度建模及非正交误差的多位置标定补偿方法,提出微小型飞行器导航、制导与控制系统闭环条件下,利用导航、制导与控制回路的飞行状态特征信息的微惯性组合导航系统滤波算法,根据微小型飞行器飞行状态实时调整卡尔曼滤波器的观测噪声方差,有效提高了动态过程中姿态测量精度和微小型飞行器的飞行平稳度。完成了组合导航系统滤波算法验证飞行试验及自主姿态稳定和航路飞行试验。飞行试验表明:微小型飞行器实现了自主姿态稳定与长距离超视距航路点导航飞行,航路点导航误差小于30 m,惯性组合姿态确定与航路导航系统及算法满足微小型飞行器自主飞行对导航系统的需求。     

基于视觉的惯性导航误差在线修正

陀螺零偏和加速度计零偏是影响惯性测量单元(IMU)积分精度的重要因素。提供一组精确的实时的零偏估计可以提高IMU的积分精度,为视觉导航提供良好的位姿预测,提高整个系统的动态性能。通过合理地建立IMU的噪声模型以及IMU和视觉的组合方程,利用一种基于李群和李代数知识的IMU预积分方法将零偏进行合理的线性化,运用Kalman滤波进行IMU零偏的在线估计。实验结果表明,通过本文的修正方法,惯性导航的平均积累误差由0.034m/s提高到0.0037m/s,精度明显提高。     

机抖激光陀螺捷联系统动力学建模及结构动特性设计方法

机抖激光陀螺捷联系统普遍采用抖频偏频技术消除闭锁效应的影响,这使得激光惯导成为自带激励源的动力学系统,动力学系统结构参数的设计将影响陀螺抖动效率和陀螺测量精度。在陀螺抖动驱动力条件下,建立了包含激光惯导箱体、惯性测量本体、陀螺、减振器、抖轮在内的较为完整的动力学模型,给出了该模型的解答过程和Matlab仿真计算结果,讨论了不同结构参数对抖动效率及惯导精度的影响规律,并在此基础上提出了激光惯导结构基于动特性设计的原则和方法。经验证,该方法能够有效指导结构转动惯量等参数设计,提高了设计质量,有效避免了激光惯导由结构设计不足而导致的动力学问题。     

MEMS惯性器件及系统发展研究综述

将MEMS惯性系统分为ISA、IMU和INS三级,分别介绍了国内外的研究概况,并对MEMS INS的发展趋势进行了讨论,供广大惯性导航研究人员参考。     

An integrated GPS/MEMS-IMU navigation system for an autonomous helicopter

During the last years, there is an increasing demand for cheap and easy to operate platforms for surveillance and reconnaissance purposes. Therefore, the development of micro aerial vehicles is receiving an increasing attention. However, VTOL-MAVs often show an inherent instability that makes at least an automatic stabilization necessary, because otherwise the operator would not be able to keep these vehicles airborne. This requires the availability of navigation information, especially the vehicle's attitude has to be known.This paper addresses the development of an integrated navigation system based on MEMS inertial sensors and GPS for a VTOL-MAV. Special attention is paid to the handling of GPS outages. While usually periods without GPS aiding can be bridged using the unaided strapdown solution, the poor quality of the MEMS inertial sensors prohibits this approach here. Therefore, during GPS outages the accelerometer data is interpreted as approximate measurements of the local gravity vector. Additionally, the usage of a magnetometer providing measurements of the Earth's magnetic field is motivated and discussed. Finally, flight test results illustrate the performance of the resulting system, proving that the achieved attitude accuracy is sufficient for the automatic control of the MAV. This holds in situations with permanent GPS loss and dynamic maneuvering, too.     

微机电惯性测量元件在导航系统的应用研究

介绍了微机电(MEMS)惯性测量元件(IMU)的基本情况，总结了误差主要来源，根据公开文献介绍的性能测试参数，建立了动态误差模型，并与GPS测量的速度和位置组合，进行了导航系统的数学仿真。仿真结果表明，MEMS—IMU尚不能独立构成导航系统，但与GPS组合，则可满足低精度的导航要求。     

Design and Development of a Real-Time DSP and FPGA-Based Integrated GPS-INS System for Compact and Low Power Applications

Emphasis of the present work is on an elegant real-time solution for GPS/INS integration. Micro-electro mechanical system (MEMS) based inertial sensors are light but not accurate enough for inertial navigation system (INS) applications. An integrated INS/GPS system provides better accuracy compared with either INS or GPS, used individually. This paper describes an improved design and fabrication of a loosely coupled INS-GPS integrated system. The systems currently available use commercial off-the-shelf (COTS) hardware and are, therefore, not optimized for compact, single supply, and low power requirements. In the proposed system, a digital signal processor (DSP) is used for inertial navigation solution and Kalman filter computations. A field programmable gate array (FPGA) is used for creating an efficient interface of the GPS with the DSP. Direct serial interface of the GPS involve tedious processing overhead on the navigation processor. Therefore, a universal asynchronous receiver transmitter (UART) and dual port random axis memory (DPRAM) are created on the FPGA itself. This also reduces the total chip count, resulting in a compact system. The system is designed to give real time processed navigation solutions with an update rate of 100 Hz. All the details of this work are presented.     

基于组合导航技术的光纤捷联系统在线标定

 将光纤捷联系统惯性测量单元（IMU）输出误差分解成零偏误差、标度因数误差、失准角误差和随机白噪声几个部分,建立了系统误差模型,基于此模型设计卡尔曼滤波器引入高精度外部信息源对IMU进行在线标定。将此方法应用于某光纤捷联系统进行跑车试验,结果表明：引入外部信息源进行在线标定与补偿后系统纯惯导精度显著提高,本文建立的系统误差模型和在线估计方式有效估计了IMU输出误差,实现了系统在线标定,提高了系统实用精度。     

行人导航系统中的MEMS误差在线修正技术

在基于微惯性器件的行人导航系统中,陀螺仪和加速度计的偏移是降低系统定位精度的重要因素。传统的标定方法大多在实验室中进行,后续导航解算都是基于标定后的固定模型,然而MEMS器件长时间工作后,标定模型参数发生变化会导致系统导航性能下降。通过分析行人导航系统及MEMS器件的特点,提出了一种基于误差模型的MEMS器件参数在线修正方法。根据行人行走的特点,检测并区分行走过程中的可修正区间与不修正区间。在可修正区间基于逆向解算算法实现了对陀螺仪和加速度计零偏的在线修正,并提出了主航向反馈修正算法,提高了行人导航系统长时间导航性能。实验结果表明,40m行走实验中,系统定位精度提升了9.07%;300m行走实验中,系统定位精度提升了13.14%。     

INS/GNSS组合导航系统空中快速对准方法

针对机载惯性/全球导航卫星系统(INS/GNSS)组合导航系统地面静基座对准时间较长、航向对准精度较低以及惯导空中故障重启后无法快速得到精确姿态信息重新进入导航状态等问题,提出一种快速初始对准方法。该对准方法基于惯性导航比力方程,利用GNSS的定位、测速信息与惯性测量组件(IMU)的输出信息解算载体姿态信息,并结合遗传-牛顿算法与求和自回归滑动平均(ARIMA)模型卡尔曼滤波信号降噪技术提高姿态信息的解算精度。基于实测飞行数据的解算验证了该方法的有效性、对准精度以及在实际工程应用中的优越性。     

微型飞行器控制与导航系统研究

在介绍了微型飞行器的概念及其功能特点的基础上,探讨了固定翼微型飞行器控制与导航系统的结构。针对我校研制的固定翼微小型飞行器,提出了一种控制与导航系统方案。最后,指出了微型飞行器控制与导航所面临的主要技术问题及其解决思路。     

Wavelet de-noising for IMU alignment

Inertial navigation system (INS) is presently used in several applications related to aerospace systems and land vehicle navigation. An INS determines the position, velocity, and attitude of a moving platform by processing the accelerations and angular velocity measurements of an inertial measurement unit (IMU). Accurate estimation of the initial attitude angles of an IMU is essential to ensure precise determination of the position and attitude of the moving platform. These initial attitude angles are usually estimated using alignment techniques. Due to the relatively low signal-to-noise ratio of the sensor measurement (especially for the gyroscopes), the initial attitude angles may not be computed accurately enough. In addition, the estimated initial attitude angles may have relatively large uncertainties that may affect the accuracy of other navigation parameters. This article suggests processing the gyro and accelerometer measurements with multiple levels of wavelet decomposition to remove the high frequency noise components. The proposed wavelet de-noising method was applied on a navigational grade inertial measurement unit (LTN90-100). The results showed that accurate alignment procedure and fast convergence of the estimation algorithm, in addition to reducing the estimation covariance of the three attitude angles, could be obtained.     

High accuracy navigation and landing system using GPS/IMU systemintegration

In this paper, the accuracy, integrity and continuity of function requirements for automatic landing systems using satellite navigation systems are discussed. Such a landing system is the integrated navigation and landing system (INLS) developed by Deutsche Aerospace (DASA/Ulm, Germany). The system concepts of the INLS are presented. It is shown how an INLS, based on system integration of a satellite navigation system (e.g., GPS) in realtime differential mode with an inertial measurement unit (IMU) in the accuracy class of an attitude and heading reference system (AHRS), can meet the requirements: the results given are mainly devoted to the accuracy issues. Using Kalman filter techniques, an in-flight calibration of the IMU is performed. The advantage of system integration, especially in dynamic flight conditions and during phases of flight with satellite masking, is explained. The accuracy, integrity and continuity of function of the INLS were proven by means of flight tests in a commuter aircraft using a laser tracker as a reference. These flight tests have shown that the short-term accuracy (<60 seconds) of the AHRS used within the INLS has been improved from low cost sensor quality to the accuracy of a high quality laser inertial navigation system (LNIS). With the presented INLS, a landing at any airfield, not equipped with conventional Instrument Landing System (ILS) or Microwave Landing System (MLS), is possible by using a very cost effective system. The INLS is a high accuracy navigation and landing system designed to be used instead of conventional landing systems at small airfields and to fill operational gaps of conventional navigation and landing systems in cruise and approach on large airports     

带FDI算法的无人机组合导航姿态确定控制系统设计

无人机导航系统的作用是提供导航数据给飞控计算机作为制导和控制用,因为飞控计算机的性能在很大程度上依赖于导航数据,导航系统的某一个错误可能会导致整个无人机的失败,因此,导航系统应具有故障检测和隔离(FDI)算法,介绍了一种用于无人机导航的FDI和低成本的组合导航系统,硬件包括低成本商业用MEMSIMU、GPS接收器、磁力计和导航计算机,软件包括带FDI算法的卡尔曼滤波。     

Constructive neural-networks-based MEMS/GPS integration scheme

This article exploits the idea of developing an alternative data fusion scheme that integrates the outputs of low-cost micro-electro-mechanical systems (MEMS) inertial measurements units (IMUs) and receivers of the global positioning system (GPS). The proposed scheme is implemented using a constructive neural network (cascade-correlation network (CCNs)) to overcome the limitations of conventional techniques that are predominantly based on the Kalman filter (KF). The CNN applied in this research has the advantage of having a flexible topology if compared with the recently utilized multi-layer feed-forward neural networks (MFNNs) for inertial navigation system (INS)/GPS integration. The preliminary results presented in this article illustrate the effectiveness of proposed CCNs over both MFNN-based and Kalman filtering techniques for INS/GPS integration.     

On the Treatment of Inertial Measurement Unit Data in Optimal Linear Navigation Policies

The inclusion of the integrated nongravitational acceleration outputs from an inertial measurement unit in an optimal linear navigation policy is treated. This formulation appears to be considerably different nt from the treatments of IMU data for space vehicle navigation that have previously been discussed and promises to yield considerably better results in many instances. It has the advantage that the data are processed in an optimal fashion that makes the best use of knowledge of the general system characteristics. Further, the IMU enters the formulation in the same manner as any other sensor and, therefore, provides a more uniform method of treatment. Two methods of dealing ng with the IMU are discussed and then applied to a simple example. The advantages of the second formulation are observed to be quite significant.