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

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.

Transfer Alignment is the process of simultaneously initializing and calibrating a weapon inertial navigation system (INS) using data from host aircraft&rsquo / s navigation system. In general, this process is accomplished by calculating the difference of navigation solutions between aircraft and weapon INSs to form observations which are then used in a Kalman filter to generate desired estimates. Numerous techniques about the problem of transfer alignment exist in the literature. In this thesis, those techniques that can be applied in the presence of elastic motion of aircraft wing were analyzed. Several transfer alignment algorithms each of which process different measurement types were designed and implemented. In order to evaluate the performance of implemented algorithms under realistic conditions, a transfer alignment simulation environment was developed. Using this simulation environment, the advantages and disadvantages of each algorithm were analyzed and the dependence of transfer alignment performance on Kalman filter system model, aircraft maneuvers and alignment duration were investigated.

GPS has become very popular in recent years. It is used in wide range of applications including aircraft navigation, search and rescue, space borne attitude and position determination and cellular network synchronization. Each application places demands on GPS for various levels of accuracy, integrity, system availability and continuity of service. Radio frequency interference (RFI) which results from many sources such as TV/FM harmonics, radar or mobile satellite systems, presents a challenge to the use of GPS. It can affect all the service performance indices mentioned above. To improve the accuracy of GPS positioning, a continuously operating reference station (CORS) network can be used. A CORS network provides all the enabled GPS users in an area with corrections to the fundamental measurements, producing more precise positioning. A threat to these networks is a threat to all high-accuracy GPS users. It is therefore necessary to monitor the quality of the received signal with the objective of promptly detecting the presence of RFI and providing a timely warning of the degradation of system accuracy, thereby boosting the integrity of GPS. This research was focused on four main tasks: a) Detection. The focus here is on a power spectral density fluctuation detection technique, in which statistical inference is used to detect narrowband continuous-wave (CW) interference in the GPS signal band after being captured by the RF front-end. An optimal detector algorithm is proposed. At this optimal point, for a fixed Detection Threshold (DT), probability of false alarm becomes minimal and for a fixed probability of false alarm, we can achieve the minimum value for the detection threshold. Experiments show that at this point we have the minimum computational load. This theoretical result is supported by real experiments. Finally this algorithm is employed to detect a real GPS interference signal generated by a TV transmitter in Sydney. b) Characterization. In the characterization section, using the GNSS signal structure and the baseband signal processing inside the GNSS receiver, a closed formula is derived for the received signal quality in terms of effective carrier to noise ratio ( ). This formula is tested and proved by calculating the C/No using the I and Q data from a software GPS receiver. For pulsed CW, a similar analysis is done to characterize the effect of parameters such as pulse repetition period (PRP) and also duty cycle on the received signal quality. Considering this characterization and the commonality between the GPS C/A code and Galileo signal as a basis to build up a common term for satellite availability, the probability of satellite availability in the presence of CW interference is defined and for the two currently available satellite navigation systems (GPS L1 signal and Galileo signal (GIOVE-A BOC(1, 1) in the E1/L1 band)) it is shown that they can be considered as alternatives to each other in the presence of different RFI frequencies as their availability in the presence of CW RFI is different in terms of RFI frequency. c) Mitigation. The last section of the research presents a new concept of ?Satellite Exclusion Zone?. In this technique, using our previously developed characterization techniques, and considering the fact that RFI has different effects on different satellite signals at different times depending on satellite Doppler frequency, the idea of excluding the most vulnerable satellite signal from positioning calculations is proposed. Using real data and real interference, the effectiveness of this technique is proven and its performance analyzed. d) Hardware implementation. The above detection technique is implemented using the UNSW FPGA receiver board called NAMURU.

Thesis (Ph. D.)--Ohio State University, 2007. / Title from first page of PDF file. Includes bibliographical references (p. 206-216).

Thesis (M.S.)--Ohio University, June, 2000. / Title from PDF t.p.

Thesis(M.S.)--Auburn University, 2006. / Abstract. Vita. Includes bibliographic references (p.84-85).

"Author biographies are available in the expanded on-line version of this article [http://www.insidegnss.com/auto/julyaug09-tetewsky-final.pdf]" / "July/August 2009." Web site title: Making Sense of GPS Inter-Signal Corrections : Satellite Calibration Parameters in Legacy and Modernized Ionosphere Correction Algorithms.

A proposta deste trabalho é contribuir com a construção de uma plataforma de veículo autônomo para viabilizar as pesquisas na área pelo Departamento de Engenharia de Transportes da USP. Até o momento o departamento dispõe de uma plataforma que, a partir de sua posição conhecida, consegue navegar autonomamente até um ponto de destino utilizando apenas uma solução GNSS, no caso, GPS. Para ampliar a mobilidade da plataforma, está sendo sugerida aqui, a adição de sensores inerciais ao veículo, para que ele consiga obter uma solução de posição mesmo em áreas sem cobertura GNSS. Um Sistema de Navegação Inercial não depende de infraestrutura externa, exceto para inicializar suas variáveis, o que neste caso pode ser feito com auxílio de um receptor GPS. Sensores inerciais de alto desempenho são caros, tem alta complexidade mecânica e em geral são de grande porte. A alternativa é o uso de sensores do tipo MEMS que são pequenos, fáceis de serem manipulados e apresentam baixo consumo de energia. A contrapartida é que a solução é mais susceptível a ruído do que seus pares que custam na faixa de centena de milhões de dólares. / The proposal of this paper is to build an autonomous vehicle platform to enable the researches in this area by the Transport Engineering Department of the USP. Until now the Department has a platform that, once its initial position is known, it can navigate autonomously to a destination point using only the GNSS, in this case, GPS. To expand the mobility resources of the platform, it is being suggested here the addition of inertial sensors to the vehicle, enabling it to acquire a position solution even in areas where there is no coverage of the GNSS. An Inertial Navigation System does not depend on an external infra-structure, with the exception on the initial setup, where the GPS can be used to provide this kind of initialization. High performance inertial sensors are expensive, have high mechanical complexity and in general are big. The alternative is the usage of MEMS sensors, which are small, easy to handle and has low power consumption. In the opposite side this solution is more susceptible to noises in comparison to those High performance sensors that cost hundreds of thousands of dollars.

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