International Telemetering Conference Proceedings / October 25-28, 1999 / Riviera Hotel and Convention Center, Las Vegas, Nevada / In this paper, a devising scheme of Autonomous Vehicle Location and Navigation System is introduced firstly. Then, several key technologies used in the devising scheme are presented, which includes a data fusion method based on extended decentralized kalman filter technology, a map-matching method used to compensate the positioning error, and a digital map data processing method used to realize route planning algorithm. By this time, a sample machine based on the devising scheme introduced in this paper has already been worked out successfully. The availability and the advantages of these technologies have been demonstrated.

Unmanned ground mobile robots are land-based robots which do not have a human passenger on board. They can be either autonomous, or controlled via telecommunication. For navigational purposes, GPS is often used. However, the GPS signal can be distorted in obstructive environments such as tunnels, urban canyons, and dense forests. IMUs can be used to provide an internal navigational solution, free from external input. However, low cost IMUs are prone to various intrinsic sources of error, which leads to large errors in the long run. Using the short term accuracy of the IMU, and the long term accuracy of the GPS, these two technologies are often integrated to combine the aforementioned aspects of the two systems. For integration of the two, various methods are implemented. Such integration methods include Particle Filters, and Kalman Filters. Kalman Filters are commonly used due to their simplicity in calculations. However, the Kalman Filter linearizes the nonlinear error estimates which are inherent with low cost IMUs. The Kalman Filter also does not account for IMU measurement drift, which is present when the measurement unit is used for a long period of time. In this thesis, a Parallel Cascade Identification (PCI) algorithm is augmented with the Kalman Filter (KF) to model the nonlinear errors which are intrinsic to the low cost IMU. The method of integration used was 2D GPS/RISS loosely coupled integration using a Kalman Filter. The PCI algorithm modelled the nonlinear error for the z-axis gyroscope while the GPS signal was available. During a GPS outage, the PCI nonlinear error model was combined with the KF estimated error and the mechanization error, to provide a corrected azimuth. The KFPCI algorithm showed an improvement over the KF algorithm in RMS position error, maximum position error, RMS azimuth error, and maximum azimuth error by an average of 30.76%, 34.71%, 66.76%, and 53.58% in each of the respective areas. / Thesis (Master, Electrical & Computer Engineering) -- Queen's University, 2013-06-11 18:13:12.625

Name of the author: Bc. Miroslav Jurič Supervisor: Mgr. Lenka Kovářová, Ph.D., MBA Title: Functional verification of selected running Sport-Testers equipped with GPS Objectives: The main object of this thesis is to compare an accuracy between compared sport testers using GPS to measure distance and geodetic devices in different environments and conditions. Followed by attesting or disproving hypothesis about measure accuracy in each instrument and the influence of technological instrumental advancement on speed of connection and measuring accuracy. Methods: The measure divergency of the used sport testers was thanks to % counted from the difference of measured values on different tests and different conditions beside of the golden standard. Measured values were statistically evaluated. Results: During the accuracy measurement on straightforward dial-up section was found in Garmin 910 TX with the average deviation -0,15%, Garmin 620 -0,19%, Polar RC3 -0,25 %, Suunto Ambit 2R -0,26%, Adidas Smart Run -0,43 %. On the curvilinear section was the average deviation of Garmin 910 TX -0,48 %, Garmin 620 -1,025%, Polar RC3 -0,8 %, Suunto Ambit 2R -0,755%, Adidas Smart Run -2,885 %. Keywords: GPS, sport tester, sports training, navigation system.

This thesis deals with the possibility of connecting inertial navigation sensors (accelerometer, magnetometer and gyroscope) to determine with the highest precision the position of the user without the help of GPS or other networks. This is inherently connected with the need to deal with many sources of errors, which are connected with this positioning method. The research section describes the principle and history of selected navigation methods and current trends in the use of inertial positioning or navigation methods. The methodical part deals with the design of a system able to determine with the highest accuracy the current position of the user from different input conditions. It is designed to obtain the necessary data from both the sensors and the user and their subsequent processing and use to render the user's position. The application section then describes the practical procedure for creating an Android mobile OS application output and in the discussion part is presented and evaluated the knowledge of testing both during the creation and in the final survey among the test users. The conclusion evaluates the goals and summarizes the practical possibilities and limits of the usability of these positioning methods in mobile phones. It also provides suggestions for further development and...

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In this thesis, the integration of a MEMS based inertial measurement unit and a three axis solid state magnetometer are studied. It is a fact that unaided inertial navigation systems, especially low cost MEMS based navigation systems have a divergent behavior. Nowadays, many navigation systems use GPS aiding to improve the performance, but GPS may not be applicable in some cases. Also, GPS provides the position and velocity reference whereas the attitude information is extracted through estimation filters. An alternative reference source is a three axis magnetometer, which provides direct attitude measurements. In this study, error propagation equations of an inertial navigation system are derived / measurement equations of magnetometer for Kalman filtering are developed / the unique method to self align the MEMS navigation system is developed. In the motion estimation, the performance of the developed algorithms are compared using a GPS aided system and magnetometer aided system. Some experiments are conducted for self alignment algorithms.

Due to their complementary characteristics, Global Positioning System (GPS) is usually integrated with standalone navigation devices like odometers and inertial measurement units (IMU). Recently, intensive research has focused on utilizing Micro-Electro-Mechanical-System (MEMS) grade inertial sensors in the integration because of their low cost. In this study, a reduced inertial sensor system (RISS) is considered. It comprises a MEMS grade single axis gyroscope, the vehicle built-in odometer, and two optional MEMS grade accelerometers. Estimation technique is needed to allow the data fusion of RISS and GPS. With adequate accuracy, Kalman filter (KF) fulfills this requirement if high-end inertial sensors are used. However, due to the inherent error characteristics of MEMS devices, MEMS-based RISS suffers from the non-stationary stochastic sensor errors and nonlinear inertial errors, which cannot be suppressed by KF alone. To solve the problem, Fast Orthogonal Search (FOS), a nonlinear system identification algorithm, is suggested in this research for modeling higher order RISS errors. FOS algorithm has the ability to figure out the system nonlinearity with a tolerance of arbitrary stochastic system noise. Its modeling results can then be used to predict the system dynamics. Motivated by the above merits, a KF/FOS module is proposed. By handling both linear and nonlinear RISS errors, this module targets substantial enhancement of positioning accuracy. To examine the effectiveness of the proposed technique, KF/FOS module is applied on RISS with GPS in a land vehicle for several road test trajectories. Its performance is compared to KF-only method, both assessed with respect to a high-end reference. To evaluate navigation algorithm in real-time vehicle application, a multi-sensor data logger is designed in this research to collect online RISS/GPS data. KF/FOS module is transplanted on an embedded digital signal processor as well. Both the off-line and online results confirm that KF/FOS module outperforms KF-only approach in positioning accuracy. They also demonstrate reliable real-time performance. / Thesis (Ph.D, Electrical & Computer Engineering) -- Queen's University, 2012-01-22 01:26:11.477

In the next coming years global satellite navigation systems (GNSS) will make part of our daily life, as the world is becoming "GNSS-dependant in the same way that it has become Internet-dependant". Indeed, more than ten years folowing the opening up to civilians of satellite-based navigation systems initially designed for military purposes, civil satellite navigation applications are becoming more and more numerous. The potential benefits have proven enormous in terms of transport safety and efficiency as well as for non-transport-related industries. / Dans les toutes prochaines années, les systèmes globaux de navigation par satellite (GNSS) feront partie intégrante de notre vie quotidienne. En effet, un peu plus de dix ans après la libéralisation de l'accès des civils aux systèmes de navigation par satellite initialement conçus à des fins militaires, les applications civiles permises par la navigation par satellite sont de plus en plus nombreuses et les bénéfices potentiels sont énormes en matière de sécurité et d'efficacité des transports comme pour d'autres secteurs et industries. fr

This thesis describes the theoretical and practical stages through development to testing of an integrated navigation system, specifically composed of an Inertial Navigation System (INS), and Global Positioning System (GPS). Integrated navigation systems combine the best features of independent systems to bring out increased performance, improved reliability and system integrity. In an integrated INS/GPS system, INS output is used to calculate current navigation states / GPS output is used to supply external measurements, and a Kalman filter is used to provide the most probable corrections to the state estimate using both data. Among various INS/GPS integration strategies, our aim is to construct a tightly coupled integrated INS/GPS system. For this purpose, mathematical models of INS and GPS systems are derived and they are linearized to form system dynamics and system measurement models respectively. A Kalman filter is designed and implemented depending upon these models. Besides these, based on the given aided navigation system representation a quantitative measure for observability is defined using Gramians. Finally, the performance of the developed system is evaluated with real data recorded by the sensors. A comparison with a reference system and also with a loosely coupled system is done to show the superiority of the tightly coupled structure. Scenarios simulating various GPS data outages proved that the tightly coupled system outperformed the loosely coupled system from the aspects of accuracy, reliability and level of observability.

ABSTRACT DESIGN AND IMPLEMENTATION OF A MICROPROCESSOR BASED DATA COLLECTION AND INTERPRATATION SYSTEM WITH ONBOARD GRAPHICAL INTERFACE G&ouml / ks&uuml / g&uuml / r, G&ouml / khan M.S., Department of Electric and Electronics Engineering Supervisor : Prof. Dr. Hasan Cengiz G&uuml / ran December 2004, 103 pages This thesis reports the design and implementation of a microprocessor based interface unit of a navigation system. The interface unit is composed of a TFT display screen for graphical interface, a Controller Circuit for system control, a keypad interface for external data entrance to the system and a power interface circuit to provide interface between the battery of the navigation system and the Controller Circuit. This thesis reports high speed design of the Controller Circuit and generation of system functions. Main functions of the interface unit are communicating with navigation computer and providing a graphical interface to the driver of the vehicle containing the navigation system. Communication and graphical data preparation functions are implemented through the use of a microprocessor. Driver function of TFT display is implemented through the use of a Field Programmable Gate Array, which is programmed using the Very High Speed IC Description Language (VHDL). Keywords: Navigation System, Interface Unit, Controller Circuit, Image Generation