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.     

Autonomous GPS/INS navigation experiment for space transfer vehicle

An experiment is described to validate the concept of developing an autonomous integrated spacecraft navigation system using onboard Global Positioning System (GPS) and inertial navigation system (INS) measurements. Previous work by the authors (1988, 1990) has demonstrated the feasibility of integrating GPS measurements with INS measurements to provide a total improvement in spacecraft navigation performance, i.e., improvement in position, velocity and attitude information. An important aspect of this research is the automatic real-time reconfiguration capability of the system, which is designed to respond to changes in a spacecraft mission under the control of an expert system     

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.     

航天器惯性及其组合导航技术发展现状

航天器是在地球大气层以外运动的飞行器,也包括部分从宇宙空间返回地球的飞行器。在航天器的飞行过程中,惯性敏感器是实现航天器姿态确定、速度变化测量的关键敏感器之一。随着航天器任务的不断扩展,航天器对惯性器件的使用日趋复杂,高精度定姿、惯性导航、组合导航等技术在应用深度和广度上不断发展。以此为背景,对航天器惯性技术的发展脉络进行了全面的梳理和总结,包括惯性技术的使用方式、技术现状以及未来发展等几个方面的内容。     

基于运动捕捉系统的多旋翼飞行器实时测姿算法

旋翼飞行器的室内自主飞行是目前研究的热点之一。在室内飞行过程中,飞行器姿态和位置信息可以通过运动捕捉系统（Motion Capture System,MCS）来进行实时测量,从而为机载低成本MEMS惯性导航系统提供校正信息。结合四旋翼飞行器的结构特性,提出了一种五点实时测姿算法。相对于目前MCS常用的测姿算法,该算法可以降低标记点安装引起的测姿误差。室内实验结果表明,该算法测姿精度高,并且能够有效实现四旋翼飞行器室内动态实时姿态测量,具有较好的工程应用价值。     

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.     

基于嵌入式平台的MEMS/GPS 组合导航系统实现研究

主要研究基于PC104平台的MEMS/GPS组合导航系统硬件实现方法.首先设计了对MTi-30 MEMS器件与GPS接收机的数据采集软件,基于统计分析方法分析建立了传感器的误差模型参数,构建了MEMS/GPS组合算法模型,基于MEMS惯性器件和GPS接收机实测数据确定了Kalman滤波器的系统噪声阵及量测噪声阵模型参数;然后利用实际测量数据进行了MEMS/GPS组合系统导航性能仿真;最后基于PC 104嵌入式平台,构建了MEMS/GPS组合导航系统原理样机,分别在静态和动态情况下完成MEMS/GPS组合导航算法实时测试,导航结果验证了硬件平台及导航算法的正确性.     

小型无人机的导航与制导仿真系统研究

研究了基于飞行器动力学模型的小型无人机的惯性组合导航与制导系统仿真技术,组合导航系统嵌入了飞行器的轨迹和姿态控制回路,建立了基于MATLAB/AEROSIM的组合导航计算机仿真系统,仿真系统包括惯性组合导航仿真模块、传感器仿真支持模块、飞行器6自由度动力学模型模块、飞行器轨迹生成、轨迹控制与姿态控制模块、导航仿真评估模块。基于该仿真系统,目前已开展惯性/卫星深组合、惯性/大气数据融合等理论算法和技术研究。     

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。     

Relative navigation for multi-spacecraft system with GPS

A type of multi-spacecraft system with kinematical restraint but no structural restraint and force action is considered. Both the absolute and relative navigation information is required for this multi-spacecraft system, but the relative information is more critical and the accuracy requirements for relative information will be much higher than those for the absolute information. In this paper, the Global Positioning System (GPS)/Differential GPS (DGPS) are introduced and used for relative navigation. Relative motion of space vehicles is modeled. Relative position, relative velocity and relative attitude are represented and solved by GPS/DGPS measurements. Using a type of commercial GPS receiver onboard spacecraft and relative differential GPS technique, the relative navigation of space vehicles can be implemented in real-time     

基于零速修正的行人导航关键技术及研究进展

在室内等卫星导航受限场景下，可采用MEMS惯性传感器对行人进行自主导航定位。采用MEMS惯性传感器的行人自主导航技术主要包括基于步长估计的行人航位推算和基于零速修正的行人导航算法两种方式。首先介绍了两种方式的基本原理，然后重点分析了零速修正的行人导航算法，阐述了相关的关键技术和研究进展。最后，对行人自主导航未来的发展趋势进行了展望，并指出了需要重点关注的技术难点。     

基于惯性系双积分的分布式POS抗干扰对准方法

分布式P OS是一种基于惯性/卫星组合技术的柔性基线多节点高精度时空测量系统,是多任务航空遥感载荷高精度成像的关键装置.然而,外部扰动及节点间的柔性连接使得分布式P OS不能采用传统解析粗对准方法进行高精度初始对准.为实现分布式P OS系统在外部扰动下获得高精度初始姿态,提出了基于惯性系双积分的抗干扰对准方法,通过双积分去噪原理极大降低外部扰动影响,最后对算法进行了三轴转台实验和飞行实验验证.实验结果表明,该方法能够有效隔离载体的动态干扰,实现了分布式P OS各节点初始姿态信息的高精度测量.     

Integration of GPS and low cost INS for pedestrian navigation aided by building layout

In outdoor environments, GPS is often used for pedestrian navigation by utilizing its signals for position computation, but in indoor or semi-obstructed environments, GPS signals are often unavailable. Therefore, pedestrian navigation for these environments should be realized by the integration of GPS and inertial navigation system （INS）. However, the lowcost INS could induce errors that may result in a large position drift. The problem can be minimized by mounting the sensors on the pedestrian＇s foot, using zero velocity update （ZUPT） method with the standard navigation algorithm to restrict the error growth. However, heading drift still remains despite using ZUPT measurements since the heading error is unobservable. Also, tbot mounted INS suffers from the initialization ambiguity of position and heading from GPS. In this paper, a novel algorithm is developed to mitigate the heading drift problem when using ZUPT. The method uses building lay- out to aid the heading measurement in Kalman filter, and it could also be combined for the initial- ization. The algorithm has been investigated with real field trials using the low cost Microstrain 3DM-GX3-25 inertial sensor, a Leica GS10 GPS receiver and a uBlox EVK-6T GPS receiver. It could be concluded that the proposed method offers a significant improvement in position accuracy for the long period, allowing pedestrian navigation for nearly40 min with mean position error less than 2.8 m. This method also has a considerable effect on the accuracy of the initialization.     

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.     

平流层飞艇升降阶段BPNN惯性导航算法

软式平流层飞艇艇体在上升和下降时经常呈堆叠状态,GPS信号会被艇体间歇性遮挡,因而只能采用惯性导航。为保证在飞艇上升和下降过程中,INS/GPS组合导航系统在被艇体遮挡GPS时仍能够提供满足精度要求的导航信息,设计了一种改进的反向传播神经网络(Back Propagation Neural Network, BPNN）惯性导航算法。采用神经网络,根据惯性导航系统在1s内的速度均值和姿态变化量,预估其在1s末的位置误差和速度误差,并对惯性导航结果进行修正。仿真实验和跑车试验结果表明,在GPS失效的30s内,新算法使得位置误差低于15m,速度误差低于0.7m/s,误差相比纯惯性导航降低了85%。     

基于MEMS传感器的四旋翼组合测姿研究

针对四旋翼无人机机体尺寸较小、带载荷能力有限的特点,设计基于低成本MEMS惯性器件的测姿系统,以满足四旋翼无人机在系统控制方面的需求。但是低成本的MEMS惯性器件具有精度低,随机漂移大,容易受到外界环境干扰等缺点。本文充分发挥四旋翼无人机搭载的MEMS惯性器件的功能,分别利用两种方法测量载体姿态,并通过卡尔曼滤波的方法实现这两种测姿方法的数据融合。经过仿真分析,融合后组合测姿系统的测姿精度得到提高。     

捷联惯导系统圆锥误差分析

捷联惯导系统由于数学平台隔离作用的不完善,当运载体沿机体坐标轴存在同频率的角振动和线振动时,角振动引起的整流效应将在姿态更新计算中产生圆锥误差,角振动和线振动引起的整流效应将在速度计算中产生划桨误差,在位置计算中产生涡卷误差。文中详细分析了圆锥误差产生机理,针对某型飞机装备 SIGMA50 GPS/SINS 组合导航系统对底座安装的精度要求,分析了安装误差、陀螺频带不够宽、姿态更新率过低对姿态精度的影响,并对维护捷联惯导系统提出建议。     

GPS Aided Inertial Navigation

The Global Positioning System is an extremely accurate satellite-based navigation system which, after its completion in 1989, will provide users worldwide, 24 hour. all weather coverage. A joint research project among Boeing, Rockwell-Collins, and Northrop has been completed in which a GPS receiver was integrated with a low-cost strap-down inertial navigation system and a flight computer. A Kalman filter in the latter allows in-fight alignment and calibration of the INS. In addition, feedback from the INS to the GPS receiver improves the system's ability to reacquire satellite signals after outages. The resulting system combines the accuracy of GPS with the jamming immunity and autonomy of inertial navigation. System tests were conducted in which a Boeing owned T-33 jet aircraft was flown through known test pattern to align and calibrate the INS. Earlier tests, including tests against an airborne jammer, were conducted in a modified passenger bus.