George E. Taylor

Road Reduction Filtering for GPS‐GIS Navigation

A novel method of map matching using the Global Positioning System (GPS) has been developed for civilian use, which uses digital mapping data to infer the systematic position errors of less than 100m which result largely from ‘selective availability’ (S/A) imposed by the US military. Selective availability was switched off on the 2nd of May 2000, and is to be replaced with ‘regional denial capabilities in lieu of global degradation’. The system tracks a vehicle on all possible roads (road centre-lines) in a computed error region, then uses a method of rapidly detecting inappropriate road centre-lines from the set of all those possible. This is called the Road Reduction Filter (RRF) algorithm. Point positioning is computed using C/A code pseudorange measurements direct from a GPS receiver. The least squares estimation is performed in the software developed for the experiment described in this paper. Virtual differential GPS (VDGPS) corrections are computed and used from a vehicles previous positions, thus providing an autonomous alternative to DGPS for in-car navigation and fleet management. Height aiding is used to augment the solution and reduce the number of satellites required for a position solution. Ordnance Survey (OS) digital map data was used for the experiment, i.e. OSCAR 1 m resolution road centre-line geometry and Land Form PANORAMA 1:50,000, 50 m-grid digital terrain model (DTM). Testing of the algorithm is reported and results are analysed. Vehicle positions provided by RRF are compared with the ‘true’ position determined using high precision (cm) GPS carrier phase techniques. It is shown that height aiding using a DTM and the RRF significantly improve the accuracy of position provided by inexpensive single frequency GPS receivers.

GPS accuracy estimation using map matching techniques: Applied to vehicle positioning and odometer calibration

A test-bed application, called Map Matched GPS (MMGPS) processes raw GPS output data, from RINEX files, or GPS derived coordinates. This developed method uses absolute GPS position- ing, map matched, to locate the vehicle on a road centre-line, when GPS is known to be sufficiently accurate. MMGPS software has now been adapted to incorporate positioning based on odometer derived distances (OMMGPS), when GPS positions are not available. Relative GPS positions are used to calibrate the odometer. If a GPS position is detected to be inaccurate, it is not used for posi- tioning, or for calibrating the odometer correction factor. In OMMGPS, GPS pseudorange obser- vations are combined with DTM height information and odometer positions to provide a vehicle position at ‘1 s’ epochs. The described experiment used GPS and odometer observations taken on a London bus on a predefined route in central of London. Therefore, map matching techniques are used to test GPS positioning accuracy, and to identify grossly inaccurate GPS positions. In total, over 15,000 vehicle positions were computed and tested using OMMGPS. In general, the position quality provided by GPS alone was extremely poor, due to multipath effects caused by the urban canyons of central London, so that odometer positioning was used much more often to position the vehicle than GPS. Typically, the ratio is 7:3 odometer positions to GPS positions. In the case of one particular trip, OMMGPS provides a mean error of position of 8.8 m compared with 53.7 m for raw GPS alone.

Accuracy and reliability of map-matched GPS coordinates: the dependence on terrain model resolution and interpolation algorithm

The global positioning system (GPS) has become the most extensively used positioning and navigation tool in the world. Applications of GPS abound in surveying, mapping, transportation, agriculture, military planning, GIS, and the geosciences. However, the positional and elevation accuracy of any given GPS location is prone to error, due to a number of factors. This has serious implications for some applications, such as real-time navigational systems. GPS accuracy can be significantly improved with additional data, possibly from multiple sources, and especially from multiple receivers. In the case of a single GPS receiver, its position and elevation can be considerably improved with the use of spatial data. For vehicle tracking, map matching can be employed to intelligently snap the GPS location to a road centreline, while height aiding can augment the GPS solution by utilising a digital terrain model (DTM), thereby reducing the number of satellites required to determine a position. This paper describes the use of map matching and height aiding, and examines the effect of different terrain resolutions (Ordnance Survey 1:50,000 and 1:10,000 scale DTMs) on plan position and elevation accuracy for vehicle tracking. Furthermore, the users choice of interpolation algorithm for estimating heights from the DTM is investigated. The results of the experiments described in this paper demonstrate that height aiding alone reduces the mean error in elevation from 22.5 to 17.5m for of a single GPS receiver, and the mean error in plan position from 6 to 5m. However, map matching and height aiding combined, reduces the elevation RMSE of a single GPS receiver from 22.5m to approximately 4m (1:50,000 scale DTM) and down to 0.8m (1:10,000 scale DTM), while the plan position RMSE is reduced from 5.9 to 3.2m (either DTM). It is also demonstrated that when the number of satellites visible to the receiver is reduced, or the satellite geometry is poor, map matching and height aiding considerably improves the plan and elevation accuracy. The use of a higher-order interpolant (e.g. a bicubic or biquintic polynomial) is shown to slightly improve performance, compared to a bilinear interpolant, for the lower-resolution DTM, but has little overall benefit for the higher resolution DTM.

Modelling and prediction of GPS availability with digital photogrammetry and LiDAR

This paper describes an automated method for predicting the number of satellites visible to a GPS receiver, at any point on the Earths surface at any time. Intervisibility analysis between a GPS receiver and each potentially visible GPS satellite is performed using a number of different surface models and satellite orbit calculations. The developed software can work with various ephemeris data, and will compute satellite visibility in real time. Real‐time satellite availability prediction is very useful for mobile applications such as in‐car navigation systems, personal navigations systems and LBS. The implementation of the method is described and the results are reported.

Automated Production of Schematic Maps for Mobile Applications

The advent of high-end miniature technology, together with the increasing availability of large scale digital geographic data products, has created a demand for techniques and methodologies that assist in the automated generation of maps specifically tailored to mobile GIS applications. This paper concerns itself with the problem of automatic generation of schematic maps. Schematic maps are diagrammatic representations based on linear abstractions of networks. In the context of mobile mapping they are seen as being a particularly useful means of displaying transportation networks. This paper describes an algorithm that automates the production of schematic maps. The algorithm makes use of the simulated annealing optimisation technique. An implementation of the algorithm is also presented, together with experimental results.

Modular neural networks for map-matched GPS positioning

This paper provides an overview of work undertaken over the past year to develop artificial neural network (ANN) techniques to improve the accuracy and reliability of road selection during map-matching computation. Map matching positions provided by low-cost GPS receivers have great potential when integrated with hand-held or in-vehicle geographical information system (GIS) applications, especially those used for tracking and navigation, on path and road networks. Initial results indicate that improvements in map-matching and positional accuracy can indeed be achieved by using simple ANNs over traditional methods. This earlier work is extended to incorporate more complex procedures and, hopefully, produce further improvements. Recent results are presented, and planned research is explained. Further results and conclusions of this on-going research are published in due course.

An analysis of the performance of a hierarchical wayfinding computational model using synthetic graphs

Abstract This paper describes a set of experiments, which use different levels of hierarchical shortest path computations. We investigate a graph–subgraph structural hierarchy as a mechanism imposed on an input data set, allowing a human or computer to access only a subset of the data necessary for a task like path retrieval. It challenges the selection of relevant data further used by people and, in turn, by computers for a particular analytical purpose. Consideration of the main principles for the design of such hierarchies raises a number of theoretical and practical research questions related to spatial information. The paper introduces the idea of adapting the principles of hierarchical wayfinding to modeling decision making, which is becoming increasingly important for advanced applications like Geographic Information Systems (GIS). The results of the experiment, which utilizes three kinds of synthetic graphs, are described. A number of important conclusions are presented, not leastwise that the benefits of hierarchical wayfinding over non-hierarchical wayfinding algorithms increases as the number of nodes in a graph increases, particularly in graphs with recognizable form.

Surface modelling for GPS satellite visibility

This paper describes an automated method for predicting the number of satellites visible to a GPS receiver, at any point on the earths surface at any time. Intervisibility analysis between a GPS receiver and each potentially visible GPS satellite are performed using a number of different surface models and satellite orbit calculations. The developed software can work with various ephemeris data, and will compute satellite visibility in real-time. Real-time satellite availability prediction is very useful for mobile applications such as in-car navigation systems, personal navigations systems and LBS. The implement- tation of the method is described and the results are reported.

Prediction and visualization of GPS multipath signals in urban areas using LiDAR Digital Surface Models and building footprints

This paper explains a ray tracing method which is applied to prediction and visualization of diffracted and reflected GPS signals in dense urban areas. Reflected and diffracted signals can have a detrimental effect on GPS positioning accuracy especially in highly built‐up areas. The ray tracing technique implemented in this paper is specially geared to LiDAR height pole data at 1‐m spatial resolution and 2D building footprints in raster and vector format, respectively. Such a simple data format allows for rapid implementation of 3D ray tracing in a GIS without further processing so that detailed 3D urban models in vector format are not required. Issues of spatial uncertainty in the data used are also addressed in relation to the identification of multipath signals. Some preliminary results obtained from fieldwork are presented and analysed in detail.

Data Integration Issues for a Farm Decision Support System

This paper explores data integration and compatibility issues raised during the development of a prototype spatial decision support system (SDSS) as a support tool for the farm manager of the University of Central Lancashires farm at Newton Rigg and as a teaching resource for staff and students on campus. Metadata concerns and interoperability problems are addressed in detail. The paper outlines the proposed model for the SDSS and issues identified during the investigation of the users’ requirements and the analysis of the underlying spatial data sets. The initial data issues relate to the identification of existing and missing data sets (Parker et al. 1996) and the creation of metadata describing the data sets. The second area to be explored concerns interoperability issues. This is relevant when users must access more than one dataset using distributed computing resources (Sondheim et al. 1999).