Low cost inertial/GPS integrated position and orientation systemfor marine applications

This paper describes the Low Cost Position and Orientation System (LCPOS), comprising the integration of a low cost “tactical grade” inertial measurement unit with GPS position, velocity and heading aiding data. LCPOS was designed to be a cost-effective alternative to a high performance costly ship INS (SINS). The demonstrated accuracy of the LCPOS integrated navigation solution is comparable to that of the SINS     

GPS/INS integration on the Standoff Land Attack Missile (SLAM)

The Standoff Land Attack Missile (SLAM) is a worldwide, all-weather, precision-strike weapon system deployed from carrier-based aircraft. In the primary mode of operation, target location and other mission data are generated from intelligence sources available on the aircraft carrier and loaded into the missile prior to aircraft takeoff. After missile launch, the SLAM inertial navigation system (INS) guides the missile along the planned trajectory. Updating the missile INS from the Global Positioning System (GPS) during flight provides precise midcourse navigation and enhances target acquisition by accurate, on-target pointing of the SLAM Maverick seeker. The GPS/INS avionics and software integration used for SLAM are described in detail, along with some of the design tradeoffs that led to the approach. The avionics configuration integrates the Harpoon midcourse guidance unit, which includes a strapdown inertial sensor package and digital processor, with a Rockwell-Collins single-channel, sequential GPS receiver processor unit (RPU), a derivative of the GPS phase-III user equipment. In addition to the GPS receiver elements the RPU contains the navigation processor, which executes the SLAM navigation, Kalman filter algorithms, and other guidance algorithms including seeker pointing. Flight-test results of the SLAM GPS-aided INS are also included     

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.     

Navigation sensors and systems in GNSS degraded and denied environments

Position, velocity, and timing(PVT) signals from the Global Positioning System(GPS)are used throughout the world but the availability and reliability of these signals in all environments has become a subject of concern for both civilian and military applications. This presentation summarizes recent advances in navigation sensor technology, including GPS, inertial, and other navigation aids that address these concerns. Also addressed are developments in sensor integration technology with several examples described, including the Bluefin-21 system mechanization.     

Online INS/GPS integration with a radial basis function neural network

Most of the present navigation systems rely on Kalman filtering to fuse data from global positioning system (GPS) and the inertial navigation system (INS). In general, INS/GPS integration provides reliable navigation solutions by overcoming each of their shortcomings, including signal blockage for GPS and growth of position errors with time for INS. Present Kalman filtering INS/GPS integration techniques have some inadequacies related to the stochastic error models of inertial sensors, immunity to noise, and observability. This paper aims to introduce a multi-sensor system integration approach for fusing data from INS and GPS utilizing artificial neural networks (ANN). A multi-layer perceptron ANN has been recently suggested to fuse data from INS and differential GPS (DGPS). Although being able to improve the positioning accuracy, the complexity associated with both the architecture of multi-layer perceptron networks and its online training algorithms limit the real-time capabilities of this technique. This article, therefore, suggests the use of an alternative ANN architecture. This architecture is based on radial basis function (RBF) neural networks, which generally have simpler architecture and faster training procedures than multi-layer perceptron networks. The INS and GPS data are first processed using wavelet multi-resolution analysis (WRMA) before being applied to the RBF network. The WMRA is used to compare the INS and GPS position outputs at different resolution levels. The RBF-ANN module is then trained to predict the INS position errors and provide accurate positioning of the moving platform. Field-test results have demonstrated that substantial improvement in INS/GPS positioning accuracy could be obtained by applying the combined WRMA and RBF-ANN modules.     

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%。     

Analysis of upgraded GPS internal Kalman filter

GPS receivers with provisions for inertial navigation system (INS) aiding are designed with internal Kalman filters that model generic INSs and process the basic GPS pseudorange and deltarange (range-rate) data to produce an output of inertially-smoothed, “GPS-derived” position and velocity. These Kalman filters model only the basic nine INS errors (position, velocity, and tilt) and do not model any INS gyro or accelerometer errors. It was found that a significant performance improvement could be achieved under conditions of degraded GPS satellite availability by augmenting this type of filter with the six INS gyro and accelerometer bias errors. It is, therefore, recommended that serious consideration be given to incorporating these states into the design of the GPS internal Kalman filter     

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.     

Rapid development of tightly-coupled GPS/INS systems

This paper addresses the question: “Why aren't tightly-coupled OPS/INS systems everywhere, on aircraft, ships and land vehicles?” Two barriers to the widespread use are cited. One is the high cost of the INS, and the other is the cost and complexity of tightly-coupled OPS/INS integration. One of those two barriers has recently been diminished drastically with the development of a standardized software package for tightly-coupled integration. In the past, only the largest corporations have been able to pay the initial development cost for tightly-coupled OPS/INS integration, usually with funding from a large defense program. Using the new software package, integration and van test can be accomplished in a matter of days, and this has been demonstrated with field trials. The package is intended primarily for small companies that otherwise would not be able to build tightly-coupled OPS/INS systems at all. What would have been a prohibitive 3- or 4-man year development effort is reduced to a few man weeks. To accomplish an integration, the system integrator has to find a way, through serial interfaces or by some other means, to get the INS measurements of acceleration (accumulated velocity change ΔV) and attitude rate (accumulated angle change Δ&thetas;) into a processor, along with the raw data of a GPS receiver. He also has to find a way to time tag the INS ΔV, Δ&thetas; with GPS time. The rest of tightly-coupled OPS/INS integration is predominately accomplished in the standardized software package. That leaves the cost of the INS as the only remaining barrier to the very widespread use of OPS/INS, and invites new development of low cost inertial sensors. The focus of this paper is on the software package, and how it achieves standardization and ease of use while retaining the flexibility to produce optimal results with a variety of INS and GPS receiver types     

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     

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.     

MIMS/GPS组合导航系统设计与实验

 GPS 接收机与微型惯性传感器组成的低成本、轻小型组合导航系统可以弥补各自的不足, 防止导航定位误差随时间积累, 并且提高了系统的抗干扰能力。采用状态和偏差去耦估计方法, 在开环卡尔曼滤波器结构的基础上, 引入了偏差反馈补偿; 并利用双GPS 接收机测量方位角解决了组合系统的初始方位对准问题。车载实验表明, 样机的定位精度和GPS 相当, 并具有较好的重复性。尤其是当GPS 短时间失锁时, 系统仍能保持较高的定位精度, 从而增强了系统的可靠性。     

一种用于惯性系统的刚挠背板设计方法

惯性系统是一种电路种类多、电信号复杂的电子产品,电路信号的品质直接决定整个产品的质量,背板对于各个功能电路的高密度信号互连关系着整个系统的性能。提出了背板设计方法,将惯性系统中电气系统的功能模块电路进行合理划分,确定立体化布局。为模块电路所需的二次电源进行集中分配,对于生成二次电源的总电源进行针对性的电磁滤波,实现惯性系统敏感器、执行机构和模块电路的刚挠电气连接。刚挠背板的设计不仅实现了功能电路的三维布局、电路网络的相互连接,还对信号的质量进行了针对性的优化设计。实践表明,该设计方法提升了电路的集成度,缩小了惯性系统的体积,同时还提高了产品的可靠性。     

Multipath-adaptive GPS/INS receiver

Multipath interference is one of the contributing sources of errors in precise global positioning system (GPS) position determination. This paper identifies key parameters of a multipath signal, focusing on estimating them accurately in order to mitigate multipath effects. Multiple model adaptive estimation (MMAE) techniques are applied to an inertial navigation system (INS)-coupled GPS receiver, based on a federated (distributed) Kalman filter design, to estimate the desired multipath parameters. The system configuration is one in which a GPS receiver and an INS are integrated together at the level of the in-phase and quadrature phase (I and Q) signals, rather than at the level of pseudo-range signals or navigation solutions. The system model of the MMAE is presented and the elemental Kalman filter design is examined. Different parameter search spaces are examined for accurate multipath parameter identification. The resulting GPS/INS receiver designs are validated through computer simulation of a user receiving signals from GPS satellites with multipath signal interference present The designed adaptive receiver provides pseudo-range estimates that are corrected for the effects of multipath interference, resulting in an integrated system that performs well with or without multipath interference present.     

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.     

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.     

SINS/DVL水下组合导航系统的误差分析与改进技术

探讨了一种适用于SINS/DVL组合导航系统的滤波原理,通过分别建立捷联惯导系统误差模型和多普勒误差模型,利用间接卡尔曼滤波原理和反馈校正法,对系统进行仿真与分析,由惯性器件的误差方差通过导航系统的误差模型得出导航参数的误差方差,结果表明,该组合导航系统的定位精度要远远高于单纯捷联惯导系统。同时,针对SINS/DVL组合导航系统工作特点及特定情况下AUV的定位精度要求,提出了一种GPS辅助SINS/DVL组合导航系统导航定位的方案。     

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RTS滤波的GPS+BDS 非差非组合PPP/INS紧组合模型

GPS高精度定位技术在动态复杂环境中,其定位精度、可靠性和连续性因卫星信号频繁失锁而变差。为此,提出了采用基于RTS滤波(Rauch-Tung-Striebel Filter)的GPS+BDS非差非组合PPP(Precise Point Positioning)与INS(Inertial Navigation System)紧组合模型的策略来克服GPS在动态定位中的弱点。其中,采用GPS+BDS双系统观测数据,可提高PPP解算中的可用卫星数,改善星站间定位几何强度和提高PPP收敛速度;采用PPP/INS紧组合,利用INS的自主定位特性和短期高精度特性,可有效改善复杂环境下的定位精度和连续性;采用RTS滤波,可进一步提高PPP/INS紧组合性能。首先推导了GPS+BDS非差非组合函数模型、PPP/INS紧组合函数模型和RTS滤波函数模型,然后利用一组车载动态数据,对动态GPS PPP、GPS+BDS PPP、GPS/INS紧组合、GPS+BDS PPP/INS紧组合和基于RTS的GPS+BDS PPP/IMU紧组合的定位、测速和定姿性能进行分析。实验结果表明,该方案可有效提高定位(58%～72%)、测速(74%～82%)和定姿(4%～23%)精度,特别是对卫星失锁期间的定位性能改善尤为明显。