ENGOS Software Receiver
The need of accuracy and integrity of a GPS position led to the development of European satellite based augmentation system EGNOS. A software receiver is a flexible implementation of a receiver, where most of the signal processing is done in software. New algorithms and signals can be easily added or modified in this receiver. This project presents an EGNOS software receiver based on modifying an existing GPS software receiver. The receiver was implemented in post processing mode with the signal obtained from the GNSS L1 front end. EGNOS corrections were applied to GPS raw data measured by Topcon dual frequency receiver. The results showed the position accuracy reaching 1 meter level in stand-alone mode. This is a considerable improvement in the accuracy of GPS positioning.
Differential GPS in marine and ideal environments
Unlike any other positioning method differential GPS made a breakthrough in global positioning and made it applicable to such science and industry spheres which require highest precision possible. However new applications rises new requirements and DGPS implementations become more and more complex. One of late applications is monitoring ocean surface level to a millimeter level with a help of GPS. The marine environment is unfriendly to GPS becauseof heavy multipath, increased humidity and constant variations in antenna normal, thus making DGPS a sentient matter. The aim of this project is to analyze DGPS and apply it to the data collected in two different environments on the surface of the Mediterranean Sea by the Barcelona University and at Aalborg University. DGPS methods and Kalman filters were implemented in MATLAB environment. The precision difference in both environments was investigated.
Combined Differential GPS and RTK to position a Gokart using Kalman Filtering
The project describes tracking of a gakart in real time, using GPS receivers. The positions obtained are kalman filtered and further used for track analysis. This projectis done in cooperation with SnofruTech, an Aalborg based company, which proposed the project as a case study. In addition SnofruTech provided the equipment and field for testing. The main focus of this project, is to find a accurate and cheap way for SnofruTech to get a precise position o its gokart system. During the project two stages of testing were performed, the initial experiments (A) and the experiments with the company (B). Initial testing was performed at campus, while experiments with company were done at Mou a suburb of Aalborg. Radio links were used to transmit correction data from the base GPS receiver to the rover ans coordinates from the rover to computer. Direct communication between GPS receiver and computer was done using HyperTerminal, while all data processing was done using Matlab version 7. Since all results are affected by noise, several filters, such as Kalman, Max/Min, Average, to name a few, were implemented to reduce the noise of the sensors and improve positions of Gokart. It was concluded that the kalman filter performed better if sensor where combined with GPS positions. If additional sensors are implemented, the performance of the filters increases, if right parameters of noise have been chosen.
EGNOS Software Receiver
Recent devellopments and modifications in satellite-based positioning systems and new augmentation systems raise the need for a flexible and easily modifiable technology to cope with the amendments. The software receiver is an enabling technology for flexible implementation of a receiver in which significant amount of signal processing is accomplished in software rather than in hardware. This report documents a prototype software EGNOS receiver (EGNOS receiver stands for EGNOS-capable GPS receiver). The CDMA signal structure associated with GPS and EGNOS provides demanding computational requirements, therfore, the receiver design is considered in post process mode. Receiver is able to do GPS and EGNOS signal acquisition and tracking. Real GPS and EGNOS data obtained from a RF frrontend is used for simulation of this algorithms. Satellites ranging capabilities are not considered. Obtained EGNOS signal trackingperformance is not satisfactory enough to extract real EGNOS data from the signals and requires improvements. Simulation of EGNOS corrections application to GPS pseudorangesis done by using real EGNOS data recorded from hardware EGNOS receiver. Raw GPS measurements obtained from the same hardware receiver is used for this simulation as well. This allowed testing and devellopment of algorithms with actual GPS and EGNOS data to verify their performance. Results show considerable improvement in the GPS positioning accuracy. Future refinement will include the transition from a prototype to a complete GPS EGNOS-enabled software receiver. The applicationhas been designed in order to show advantages of software receivers, where new algorithms and signals can be easily added or previously modified.
High Precision Tracking System for Virtual Reality Using GPS
The key elements in this project was to investigate the dynamics of a kinematic system, and the real-time determination of the system's pose (position & orientation). To direct our investigations, we chose to focus on the development of a specific application. For this, we chose the virtual environment. Some virtual environment systems require a spatial tracking application for pose purposes. Several methods are currently used such as magnetic trackers etc. However, most of these systems only work in a restricted laboratorial environment. With the use of GPS technology, an outdoor system could be made. For such a system, the orientation and position are rather critical, and if there is a lag between head movement and visual feedback, the user perceives a temporal distortion effect. It is therefor necessary to develop a system that includes a predictive filtering technique such as the Kalman Filter. Real-Time Kinematic (RTK) GPS is used for the estimation of the user's position in the virtual environment. The problems concerning system orientation were not addressed in this project. Download project
Comparison of Methods of Accuracy Improvement in Kinematic GPS
This project documents the analysis and possible improvements of the positioning accuracy in static as well as in kinematic GPS setups using simple GPS receivers. The project describes a set of experiments performed by the group, and the results of post processing methods, including a code DGPS and Kalman filtering. Possible applications of Kalman filter trying to improve the accuracy of estimation of the position in static and kinematic setups are investigated. Algorithm for moving object coordinate estimation using Kalman filtering is derived. A filter, which is implemented in this project, tries to predict further moving object trajectory considering that a movement is linear with zero acceleration in X, Y, Z components. The filter algorithm decides what to believe more: the predicted movement trajectory. The errors and mismatches in the algorithm flow are discussed. Possible other improvement methods are briefly discussed. The code DGPS method of improving of positioning accuracy is applied for coordinates, and not for pseudo ranges, considering that measurement conditions are exactly the same for the rover and reference receivers. It is concluded that simple methods of GPS accuracy improvement, such as code DGPS are not very efficient or do not increase accuracy that much. Kalman filter applied for coordinates is not efficient, because kinematic GPS “noisy” measurements are not normally distributed about the mean value.
Implementation of Kalman filter for double differenced real-time setup
This project work describes how a centimeter level accuracy can be obtained in real-time setup. The real-time set up was achieved by using a serial communication prot to read the GPS receiver data from the Matlab workplace. In the report, the first part describes the communication protocol between the serial communication port and the receiver and this shows how Matlab can write to an read data from the receiver in real-time set up. The second part describes how data was processed using developed tool box and how a centimeter levelaccuracy was obtained for the rover position. To help provide current estimates of the position coordinates, we use the Kalman filter. It also determines up-to date uncertainties of the estimates for real-time quality assessments. Because of its optimum performance, we have adopted its use in reducing the associated noise in measurements.
Precise Real Time Positioning in Kinematic Mode
The purpose of this project was to investigate the real-time precise positioning in kinematic mode. It was found that a centimetre level accuracy is obtained using relative positioning and carrier phase pseudorange observables. Unfortunately, this method brings difficulties in measuring ambiguities and also needs expensive equipment - at least two GPS receivers with radio modems.
Implementation of the Kalmn filter for double differenced phase and/or code observation in a kinematic setup
Today the satellite navigation technology, with its capability to provide accurate position information, plays a key role for a more efficient management of the available transport resources. A user having a GPS receiver, fitted to a vehicle, is able to constantly determine its location. But there are some users that need more accurate position then usual GPS receiver gives. The project was made in case to show the extensive opportunities of using GPS receivers in the precise kinematic applications. So the investigation was undertaken in advance to implement a system, which gets the actual and accurate position of the ground vehicle in real time and plots it on the map. The simulation of real time system in a kinematic setup was implemented. The objectives of this project are to use the Ashtech Z-12 GPS receiver in moving vehicle and improve accuracy of the position by using Double differential GPS and Kalman filtering. Corrected positions are to be plotted on the digital map. Measurements for dual point positioning were undertaken to fulfill a static and a kinematic experiments. Before starting to simulate real-time, the static experiment was realized to ensure that the Kalman filter and double differenced GPS data processing techniques are functioning. Afterwards, the kinematic experiment accomplished to simulate the real-time. The computed positions were plotted on the digital map.
|Designed by Lars G. Johansen. DGC 1999-2003|