Integration of GPS with Inertial Navigation Systems (INS) can provide reliable and complete positioning and geo-referencing parameters including position, velocity and attitude for dynamic platforms for a variety of applications. This research has been focusing on four modelling and implementation issues for a GPS/INS integrated platform in order to improve the overall integration performance, in particular: a) Time synchronization Having recognised that having a precise time synchronisation of measurements is fundamental in constructing a multi-sensor integration platform and is critical for achieving high data fusion performance, various time synchronisation scenarios and solutions have been investigated. A criterion for evaluating synchronisation accuracy and error impacts has been derived; an innovative time synchronisation solution has been proposed; an applicable data logging system has been implemented with off-the-shelf components and tested. b) Noise suppression of INS raw measurements Low cost INS sensors, especially MEMS INS, would normally exhibit much larger measurement noise than conventional INS sensors. A novel method of using vehicle dynamic information for de-noising raw INS sensor measurements has been proposed in this research. Since the vehicle dynamic model has the characteristic of a low pass filter, passing the raw INS sensor measurements through it effectively reduces the high frequency noise component. c) Adaptive Kalman filtering The present data fusion algorithms, which are mostly based on the Kalman filter, have the stringent requirement on precise a priori knowledge of the system model and noise properties. This research has investigated the utilization issues of online stochastic modelling algorithm, and then proposed a new adaptive process noise scaling algorithm which has shown remarkable capability in autonomously tuning the process noise covariance estimates to the optimal magnitude. d) Integration of a low cost INS sensor with a standalone GPS receiver To improve the performance where a standalone GPS receiver integrated with a MEMS INS, additional velocity aiding and a new integration structure has been adopted in this research. Field test shows that velocity determination accuracy could reach the centimetre level, and the errors of MEMS INS have been limited to such a level that it can generate stable attitude and heading references under low dynamic conditions.

Integration of GPS with Inertial Navigation Systems (INS) can provide reliable and complete positioning and geo-referencing parameters including position, velocity and attitude for dynamic platforms for a variety of applications. This research has been focusing on four modelling and implementation issues for a GPS/INS integrated platform in order to improve the overall integration performance, in particular: a) Time synchronization Having recognised that having a precise time synchronisation of measurements is fundamental in constructing a multi-sensor integration platform and is critical for achieving high data fusion performance, various time synchronisation scenarios and solutions have been investigated. A criterion for evaluating synchronisation accuracy and error impacts has been derived; an innovative time synchronisation solution has been proposed; an applicable data logging system has been implemented with off-the-shelf components and tested. b) Noise suppression of INS raw measurements Low cost INS sensors, especially MEMS INS, would normally exhibit much larger measurement noise than conventional INS sensors. A novel method of using vehicle dynamic information for de-noising raw INS sensor measurements has been proposed in this research. Since the vehicle dynamic model has the characteristic of a low pass filter, passing the raw INS sensor measurements through it effectively reduces the high frequency noise component. c) Adaptive Kalman filtering The present data fusion algorithms, which are mostly based on the Kalman filter, have the stringent requirement on precise a priori knowledge of the system model and noise properties. This research has investigated the utilization issues of online stochastic modelling algorithm, and then proposed a new adaptive process noise scaling algorithm which has shown remarkable capability in autonomously tuning the process noise covariance estimates to the optimal magnitude. d) Integration of a low cost INS sensor with a standalone GPS receiver To improve the performance where a standalone GPS receiver integrated with a MEMS INS, additional velocity aiding and a new integration structure has been adopted in this research. Field test shows that velocity determination accuracy could reach the centimetre level, and the errors of MEMS INS have been limited to such a level that it can generate stable attitude and heading references under low dynamic conditions.

Made available in DSpace on 2014-06-12T16:24:58Z (GMT). No. of bitstreams: 2 arquivo2024_1.pdf: 6911746 bytes, checksum: e026d8282474f1c0e926aa0bfa61f254 (MD5) license.txt: 1748 bytes, checksum: 8a4605be74aa9ea9d79846c1fba20a33 (MD5) Previous issue date: 2010 / O uso de imagens aéreas é uma das maneiras mais rápidas de se obter dados cartográficos de uma região e a demanda tem crescido nos últimos anos nos mais diversos campos da engenharia ou fora dela, como o projeto e fiscalização de obras ou análise de impactos ambientais. Por outro lado o processo convencional de levantamento aéreo é caro e demorado, restringindo o seu uso a projetos de maior porte. Muito do custo do processo convencional está relacionado aos equipamentos e software utilizados. Sendo assim, tem-se estudado formas de reduzir esses custos utilizando câmaras digitais não métricas de pequeno formato para levantamentos de pequenas áreas e aplicações especiais. Portanto, o objetivo deste trabalho é especificar e implementar um sistema de aquisição de imagens, com hardware e software de baixo custo, no sentido de facilitar o uso de câmaras não métricas na aquisição de imagens aéreas. O sistema é composto de câmara digital de pequeno formato, integrado com receptor GPS para controle do disparo e sistema inercial formado por giroscópios e acelerômetros

Made available in DSpace on 2014-06-12T16:30:47Z (GMT). No. of bitstreams: 2 arquivo506_1.pdf: 6911746 bytes, checksum: e026d8282474f1c0e926aa0bfa61f254 (MD5) license.txt: 1748 bytes, checksum: 8a4605be74aa9ea9d79846c1fba20a33 (MD5) Previous issue date: 2010 / SERVIÇO FEDERAL DE PROCESSAMENTO / O uso de imagens aéreas é uma das maneiras mais rápidas de se obter dados cartográficos de uma região e a demanda tem crescido nos últimos anos nos mais diversos campos da engenharia ou fora dela, como o projeto e fiscalização de obras ou análise de impactos ambientais. Por outro lado o processo convencional de levantamento aéreo é caro e demorado, restringindo o seu uso a projetos de maior porte. Muito do custo do processo convencional está relacionado aos equipamentos e software utilizados. Sendo assim, tem-se estudado formas de reduzir esses custos utilizando câmaras digitais não métricas de pequeno formato para levantamentos de pequenas áreas e aplicações especiais. Portanto, o objetivo deste trabalho é especificar e implementar um sistema de aquisição de imagens, com hardware e software de baixo custo, no sentido de facilitar o uso de câmaras não métricas na aquisição de imagens aéreas. O sistema é composto de câmara digital de pequeno formato, integrado com receptor GPS para controle do disparo e sistema inercial formado por giroscópios e acelerômetros

The integrated GPS/INS system has become an indispensable tool for providing precise and continuous position, velocity, and attitude information for many positioning and navigation applications. Although the integrated GPS/INS system provides augmented solutions that make use of the complementary features of each component system, its performance is still limited by the quality of GPS measurements, and the geometric strength of the satellite constellation. To address such a problem this research has focussed on the integration of GPS, Pseudolite and INS technologies. The main research contributions are summarised below: (a)A cost effective GPS/INS integration approach has been developed and tested, consisting of a single-frequency L1 GPS receiver and a tactical-grade strapdown INS. Results of field experiments demonstrate that this approach is capable of delivering position accuracies of the order of a few centimetres under a benign operational environment and provides continuously positioning at sub-decimetre accuracy during GPS signal blockage lasting up to about five seconds. (b) A novel kinematic positioning and navigation system based on GPS/Pseudolite/INS integration has been proposed as an alternative to existing GPS/INS systems. With this integration approach, the continuity, integrity, and precision of the GPS/INS system can be significantly improved as the inclusion of pseudolite signals enhances the GPS signal availability and the geometry strength. (c)The impact of pseudolite location errors in such pseudolite-augmented systems has been investigated. Theoretical and numerical analyses reveal that the error effects on measurement models, and on final positioning solutions, can be minimised by selecting optimal pseudolite location(s). (d)A new ambiguity resolution procedure has been developed for use in the proposed GPS/Pseudolite/INS system. It is designed to rapidly and reliably resolve the single-frequency ambiguities due not only to the aiding by pseudolites and INS, but also by adopting a realistic stochastic model and a statistically rigorous ambiguity validation test. The proposed procedure can indeed improve the performance of the single-frequency ambiguity resolution algorithm in terms of both reliability and time-to-fix-ambiguity. (e)An effective cycle slip detection and identification algorithm has been developed, which is suitable for the integrated GPS/Pseudolite/INS system. Test results indicate that induced cycle slips can be reliably detected and instantaneously identified, even if the slips occur at successive epochs. (f)Flight trials have been conducted to evaluate the overall performance for aircraft approach and landing using the GPS/Pseudolite/INS system. Results from these trials show that an enhancement in the accuracy and reliability of the vehicle navigation solution can be achieved with the employment of one or more pseudolite.

The global Positioning System (GPS) provides location and time information as long as there are unobstructed lines of sight to four or more GPS satellites. However, when this is not the case the signal may be inaccurate or sometimes even completely blocked. In these situations the Inertial Navigation System (INS) is an appropriate choice for positioning.  An INS has already been proposed in a previous thesis by Erik Andersson and the objective of this thesis is to fuse the GPS with the INS in a proper way. A part of this project is to decide the reliability of the GPS.Three methods for GPS reliability detection have been proposed. One method based on the statistical properties of each of the separate systems, and two methods based on the statistical properties of the residuals between the GPS and INS. Two methods for GPS/INS integration have been proposed. One method based on a bank of parallel running Kalman filters and one method based on an adaptive observer.The method based on Kalman filter diverged. By adding a state that was suppose to represent the bias of the noise an attempt was to fix this problem made. The filter still diverged and was not examined any further. Among the other two algorithms did the one that uses both magnetometer and gyroscope presents a better result than the one that uses only gyroscope. However, the result differences between the two algorithms were not big and the result may change if a better INS is used.

In recent years, Land vehicle navigation system (LVNS) technology is a subject of great interest due to its potential for both consumer and business vehicle markets. GPS/INS ( Global Positioning System/ Inertial Navigation System ) integrated system is an effective solution to realize the LVNS. And how to keep communication between the vehicle and satellite while the vehicle is running in a bad environment is the main task in this thesis. The thesis provides an introduction to beam tracking system and two algorithms of how to improve the performance, then compare these two algorithms and choose the suitable one and implement it on ArduPilotMega board using Arduino language, at last test the integrated GPS/INS system in practice in order to estimate the performance. The requirements of the project are the maximum angular speed and angular acceleration speed of the vehicle are  and , respectively. Two algorithms which are Direction Cosine Matrix (DCM) and Euler Angle are evaluated in the system. In this thesis, there are many rotations due to the hostile environment, and DCM algorithm is not suitable for the requirement according to the results of simulation. Therefore, an innovated method which is Euler Angle Algorithm can be one effective way to solve the probelm. The primary idea of Euler Angle algorithm is to calculate the difference between the reference direction vector and the measurement direction vector from GPS and accelerometers, once there is an error rotation, take the cross product and rotate the incorrect direction vector back to original direction. The simulation results show that by implementing EA algorithm, system requirements can be achievable with a 10kHz update rate antenna and a 4000Hz sampling rate gyroscope, also with EA implementation in ArduPilotMega board, the real system tracking ability can be enhanced effectively.

Attitude estimation of unmanned aerial vehicles is of great importance as it enables propercontrol of the vehicles. Attitude estimation is typically done by an attitude-heading refer-ence system (ahrs) which utilises different kind of sensors. In this thesis these include agyroscope providing angular rates measurements which can be integrated to describe the at-titude as well as an accelerometer and a magnetometer, both of which can be compared withknown reference vectors to determine the attitude. The sensor measurements are fused usinga gps augmented 7-state Extended Kalman filter (ekf) with a quaternion and gyroscope bi-ases as state variables. It uses differentiated gps velocity measurements to estimate externalaccelerations as reference vector to the accelerometer, which significantly raises robustnessof the solution. The filter is implemented in MatlabTM and in c on an ARM microprocessor.It is compared with an explicit complementary filter solution and is evaluated with flightsusing a fixed-wing uav with satisfactory results.

ABSTRACT The purpose of this thesis is to examine the Sit-in movement in Chattanooga, Tennessee during the early 1960s in the context of a perpetuating tradition of protest in the African American community spanning more than a century. The study will also illustrate how it was a unique episode in the annals of the Civil Rights Movement in that it was strictly orchestrated by high school students without the input or support of adults, yet it has largely been neglected by historians. The research conducted includes oral histories, newspaper clippings, private manuscript collections, books, videos, and periodicals which provide great insight into the minds, motives, and methods of those involved. The study also depicts the galvanizing spirit, ignited by the students, which compelled the community to act and resulted in monumental social changes.

Wireless sensor network technology has now been widely adopted. In many applications, distributed sensor nodes collect data at different locations and the location information of each node is required. The Global Positioning System is commonly used to identify the location of the nodes in such networks. Although GPS localization has consistent long-term accuracy, it is limited by the inherent dependency on a direct line of sight to 4 or more external satellites. The increasing demand for an embedded system providing reliable navigation solutions regardless of its operational environment has motivated investigations into the use of integrated systems that combine inertial sensors with GPS receivers. This research proposes a hardware architecture for location-based wireless sensor networks. In this architecture, each sensor node consists of a GPS receiver, a reduced set of low cost micro-electro-mechanical-system-based INS and a wireless transceiver. Sensor nodes in WSN are often equipped with irreplaceable batteries, which makes the power consumption crucial. To reduce the energy consumption, a microcontroller is used to control the power supply. Besides, a motion detection scheme is proposed by taking advantage of the ultra low-power wake-up function of the microcontroller. A low-power featured digital signal processor is used to accomplish the navigation computation using the Kalman filter for GPS/INS data fusion. Non-Holonomic Constraints derived velocity updates are applied to reduce the position errors. Field tests are conducted to verify the real-time performance of the proposed system with a positioning update rate of 20 Hz. The first test shows that the 2D INS/GPS integration can maintain the average system position error within 5 meters during a 60-second GPS outage. The second test used low cost inertial sensors. The average position error was 10.17 meters during a 20-second outage. The largest RMS value of position errors among these outages was within 14.5 meters. Furthermore, additional accuracy improvements of approximately 1.4 meters were achieved by utilizing NHC during GPS outages. The third test shows that the average error during a 30-second outage is approximately 20.6 meters for the on-foot scenario and 26.7 meters for the in-vehicle scenario. / Thesis (Master, Electrical & Computer Engineering) -- Queen's University, 2012-01-13 14:46:45.44