A Robust Navigation System Using GPS, MEMS Inertial Sensors and Rule-based Data Fusion PDF Download

Author: Zexi Liu
Publisher:
ISBN:
Category : Global Positioning System
Languages : en
Pages : 416

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Author: Priyanka Aggarwal
Publisher: Artech House
ISBN: 1608070441
Category : Technology & Engineering
Languages : en
Pages : 213

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Book Description
Due to their micro-scale size and low power consumption, Microelectromechanical systems (MEMS) are now being utilized in a variety of fields. This leading-edge resource focuses on the application of MEMS inertial sensors to navigation systems. The book shows you how to minimize cost by adding and removing inertial sensors. Moreover, this practical reference provides you with various integration strategies with examples from real field tests. From an introduction to MEMS navigation related applicationsOC to special topics on Alignment for MEMS-Based NavigationOC to discussions on the Extended Kalman Filter, this comprehensive book covers a wide range of critical topics in this fast-growing area."

Author: Chong Shen
Publisher: Springer Nature
ISBN: 9813345160
Category : Technology & Engineering
Languages : en
Pages : 131

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Book Description
This book introduces typical inertial devices and inertial-based integrated navigation systems, gyro noise suppression, gyro temperature drift error modeling compensation, inertial-based integrated navigation systems under discontinuous observation conditions, and inertial-based brain integrated navigation systems. Integrated navigation is the result of the development of modern navigation theory and technology. The inertial navigation system has the advantages of strong autonomy, high short-term accuracy, all-day time, all weather, and so on. And it has been applied in most integrated navigation systems. Among them, the information processing of inertial-based integrated navigation system is the core technology. Due to the effect of the device mechanism and working environment, there are errors in the output information of the inertial-based integrated navigation system, including gyroscope noise, temperature drift, and discontinuous observations, which will seriously reduce the accuracy and robustness of the system. And the book helps readers to solve these problems. The intelligent information processing technology involved is equipped with simulation verification, which can be used as a reference for undergraduate, graduate, and Ph.D. students, and also scientific researchers or engineers engaged in navigation-related specialties.

Author: J. Fletcher
Publisher:
ISBN:
Category :
Languages : en
Pages : 13

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Book Description
As evidenced by many biological systems, the fusion of optical and inertial sensors represents an attractive method for passive navigation. In our previous work, a rigorous theory for optical and inertial fusion was developed for precision navigation applications. The theory was based on a statistical transformation of the feature space based on inertial sensor measurements. The transformation effectively constrained the feature correspondence search to a given level of a priori statistical uncertainty. When integrated into a navigation system, the fused system demonstrated performance in indoor environments which were comparable to that of GPS-aided systems. In order to improve feature tracking performance, a robust feature transformation algorithm "Lowe?s SIFT" was chosen. The SIFT features are ideal for navigation applications in that they are invariant to scale, rotation, and illumination. Unfortunately, there exists a correlation between feature complexity and computer processing time. This limits the effectiveness of robust feature extraction algorithms for real-time applications using traditional microprocessor architectures. While recent advances in computer technology have made image processing more commonplace, the amount of information that can be processed is still limited by the power and speed of the CPU. In this paper, a new theory which exploits the highly parallel nature of General Programmable Graphical Processing Units "GPGPU" is developed which supports deeply integrated optical and inertial sensors for real-time navigation. Recent advances in GPGPU technology have made realtime, image-aided navigation a reality. Our approach leverages the existing OpenVIDIA core GPGPU library and commercially available computer hardware to solve the image and inertial fusion problem. The open-source libraries are extended to include the statistical featur.

Author: Aboelmagd Noureldin
Publisher: Springer Science & Business Media
ISBN: 3642304656
Category : Technology & Engineering
Languages : en
Pages : 324

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Book Description
Fundamentals of Inertial Navigation, Satellite-based Positioning and their Integration is an introduction to the field of Integrated Navigation Systems. It serves as an excellent reference for working engineers as well as textbook for beginners and students new to the area. The book is easy to read and understand with minimum background knowledge. The authors explain the derivations in great detail. The intermediate steps are thoroughly explained so that a beginner can easily follow the material. The book shows a step-by-step implementation of navigation algorithms and provides all the necessary details. It provides detailed illustrations for an easy comprehension. The book also demonstrates real field experiments and in-vehicle road test results with professional discussions and analysis. This work is unique in discussing the different INS/GPS integration schemes in an easy to understand and straightforward way. Those schemes include loosely vs tightly coupled, open loop vs closed loop, and many more.

Author: Deepak Bhatt
Publisher:
ISBN:
Category : Computer algorithms
Languages : en
Pages : 160

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Book Description
An integrated navigation system consisting of INS and GPS is usually preferred due to the reduced dependency on GPS-only navigator in an area prone to poor signal reception or affected by multipath. The performance of the integrated system largely depends upon the quality of the Inertial Measurement Unit (IMU) and the integration methodology. Considering the restricted use of high grade IMU and their associated price, low-cost IMUs are becoming the preferred choice for civilian navigation purposes. MEMS based inertial sensors have made possible the development of civilian land vehicle navigation as it offers small size and low-cost. However, these low-cost inertial sensors possess high inherent sensor errors such as biases, drift, noises etc. As a result, the accuracy of the integrated system degrades rapidly in a GPS denied environment. Thus, an accurate in-lab calibration and modeling of inertial sensor errors become mandatory before being deployed. This dissertation introduces a Support Vector Regression (SVR) based IMU error modeling approach for improving the low-cost navigation system accuracy. A low-cost MEMS based IMU offered by cloud cap technology, Crista IMU is used to evaluate the SVR based error modeling approach effectiveness. Alternatively, the IMU derived navigation solution and GPS data is fused to output the more reliable navigation solution and model the errors in the inertial navigation solution simultaneously. This fusion and error modeling continues during the GPS signal availability. In the case of GPS outages, the developed error model is utilized to improve the integrated navigation system accuracy. Thus, in a continued effort to improve the standalone low-cost IMU derived navigation solution reliability during GPS outages, an intelligent technique utilizing neural networks and a hybrid of mathematics and support vector based fusion algorithms are proposed fusing INS and GPS data in an open and closed loop fashion. The performance of the proposed techniques and algorithm is evaluated using real field test data utilizing low-cost MEMS IMU, Crossbow IMU 300CC-100 and a Novatel OEM GPS receiver. The test results demonstrated the improved positioning accuracy in comparison to existing techniques and showed a substantial reduction in standalone Inertial Navigation System (INS) position error drift during GPS outages. Further, a feasibility of statistical based approaches consisting of Cubist, Random Forest and Support Vector Regression is evaluated for a low-cost INS and GPS integrated system. Through experimental demonstration, Random forest regression was found to be a suitable candidate for INS and GPS data fusion as it offers the least training time and ability to tuned the parameter automatically.

Author: Yueming Zhao
Publisher: LAP Lambert Academic Publishing
ISBN: 9783659499364
Category :
Languages : en
Pages : 300

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Book Description
A vehicle navigation system can consist of several sensors: GPS, INS, odometers, cameras etc. The Micro Electrical Mechanical Sensors (MEMS) are cheap alternative to more expensive inertial sensors, but they suffer from larger errors. The MEMS stochastic errors are analysed with different methods. GPS/MEMS integration is introduced and navigation errors are analysed based on analytical error propagation studies and on real tests. Moreover, the GPS/MEMS combination is augmented by map matching and camera observations of detected objects (lines and points). The robust BLAVE (Balanced Least Absolute Value Estimator) method is introduced and applied on the estimation of camera motion parameters. Comparisons with the traditional RANSAC algorithm are also presented. Finally the dynamic GPS/MEMS error model is augmented with equivalent coloured noise model and its performance is tested on simulated data coming from multiple MEMS sensors.

Author: Mohinder S. Grewal
Publisher: John Wiley & Sons
ISBN: 1119547830
Category : Science
Languages : en
Pages : 610

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Book Description
Covers significant changes in GPS/INS technology, and includes new material on GPS, GNSSs including GPS, Glonass, Galileo, BeiDou, QZSS, and IRNSS/NAViC, and MATLAB programs on square root information filtering (SRIF) This book provides readers with solutions to real-world problems associated with global navigation satellite systems, inertial navigation, and integration. It presents readers with numerous detailed examples and practice problems, including GNSS-aided INS, modeling of gyros and accelerometers, and SBAS and GBAS. This revised fourth edition adds new material on GPS III and RAIM. It also provides updated information on low cost sensors such as MEMS, as well as GLONASS, Galileo, BeiDou, QZSS, and IRNSS/NAViC, and QZSS. Revisions also include added material on the more numerically stable square-root information filter (SRIF) with MATLAB programs and examples from GNSS system state filters such as ensemble time filter with square-root covariance filter (SRCF) of Bierman and Thornton and SigmaRho filter. Global Navigation Satellite Systems, Inertial Navigation, and Integration, 4th Edition provides: Updates on the significant upgrades in existing GNSS systems, and on other systems currently under advanced development Expanded coverage of basic principles of antenna design, and practical antenna design solutions More information on basic principles of receiver design, and an update of the foundations for code and carrier acquisition and tracking within a GNSS receiver Examples demonstrating independence of Kalman filtering from probability density functions of error sources beyond their means and covariances New coverage of inertial navigation to cover recent technology developments and the mathematical models and methods used in its implementation Wider coverage of GNSS/INS integration, including derivation of a unified GNSS/INS integration model, its MATLAB implementations, and performance evaluation under simulated dynamic conditions Global Navigation Satellite Systems, Inertial Navigation, and Integration, Fourth Edition is intended for people who need a working knowledge of Global Navigation Satellite Systems (GNSS), Inertial Navigation Systems (INS), and the Kalman filtering models and methods used in their integration.

Author: Mohinder S. Grewal
Publisher: John Wiley & Sons
ISBN: 0470099712
Category : Science
Languages : en
Pages : 416

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Book Description
An updated guide to GNSS and INS, and solutions to real-world GPS/INS problems with Kalman filtering Written by recognized authorities in the field, this second edition of a landmark work provides engineers, computer scientists, and others with a working familiarity with the theory and contemporary applications of Global Navigation Satellite Systems (GNSS), Inertial Navigational Systems (INS), and Kalman filters. Throughout, the focus is on solving real-world problems, with an emphasis on the effective use of state-of-the-art integration techniques for those systems, especially the application of Kalman filtering. To that end, the authors explore the various subtleties, common failures, and inherent limitations of the theory as it applies to real-world situations, and provide numerous detailed application examples and practice problems, including GNSS-aided INS, modeling of gyros and accelerometers, and SBAS and GBAS. Drawing upon their many years of experience with GNSS, INS, and the Kalman filter, the authors present numerous design and implementation techniques not found in other professional references. This Second Edition has been updated to include: GNSS signal integrity with SBAS Mitigation of multipath, including results Ionospheric delay estimation with Kalman filters New MATLAB programs for satellite position determination using almanac and ephemeris data and ionospheric delay calculations from single and dual frequency data New algorithms for GEO with L1 /L5 frequencies and clock steering Implementation of mechanization equations in numerically stable algorithms To enhance comprehension of the subjects covered, the authors have included software in MATLAB, demonstrating the working of the GNSS, INS, and filter algorithms. In addition to showing the Kalman filter in action, the software also demonstrates various practical aspects of finite word length arithmetic and the need for alternative algorithms to preserve result accuracy.

Author: David Titterton
Publisher: IET
ISBN: 0863413587
Category : Technology & Engineering
Languages : en
Pages : 578

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Book Description
Inertial navigation is widely used for the guidance of aircraft, missiles ships and land vehicles, as well as in a number of novel applications such as surveying underground pipelines in drilling operations. This book discusses the physical principles of inertial navigation, the associated growth of errors and their compensation. It draws current technological developments, provides an indication of potential future trends and covers a broad range of applications. New chapters on MEMS (microelectromechanical systems) technology and inertial system applications are included.