Integrating Differential GPS data into an Embedded GIS ... - CiteSeerX

7th EC-GI & GIS WORKSHOP EGII -Managing the Mosaic Potsdam, Germany, June 13-15, 2001

Integrating Differential GPS data into an Embedded GIS and its Application to Infomobility and Navigation Evangelos Kotsakis, Alain Caignault, Wolfram Woehler, and Michalis Ketselidis Joint Research Centre (CCR), TP261, I-21020 Ispra (VA), Italy {Evangelos.Kotsakis, Alain.Caignault, Wolfram.Woehler, Michalis.Ketselidis}@jrc.it

Abstract. The recent advent of the wireless communication and GPS technology have given new impetus for addressing infomobility. Infomobility is mainly expressed through ubiquitous computing and it is very important in some applications such as security operation management, rescue activity supervision and managing crisis situations. This paper proposes an infomobility application for managing security operations. The system has been designed by using commercial of the shelf components, it is extensible and it can be configured to be used in a series of similar applications that require geographical and geo-positioning services. It consists of three modules (visualization, geo-positioning and communications) and it aims at providing positioning and geographical information on mobile terminal. The architecture of the system is discussed and some preliminary results are presented.

Keywords: Infomobility; location based services; satellite navigation; differential positioning; mobile communications; mobile Internet; GIS; high-resolution satellite imagery

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Introduction

The Infomobility is a term used to describe the set of technologies and the applications that allow the “user on the move” to access positioning and geographic information anytime, anywhere. It mainly addresses the needs for acquiring up to date information at any location. It encompasses technologies that support ubiquitous services that can be applied to a wide range of applications including travel assistance, tourist guide, traffic assistance, search and rescue and personalized tracking. The main objective in such applications is to provide the “user on the move” with geographic and geo-positioning information as well as location based services. The convergence of communication and navigation technologies with multi-media content and geo-information creates new opportunities for Infomobility services [5, 6, 11, 8]. Such services integrate the mobile

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devices seamlessly with multimedia content and location-based information. Infomobility services are user-driven, interactive and may extend to every aspect of human activity, from intelligent transport and safety to travel, tourism and leisure. Consequently, the use of geographic information for infomobility creates new opportunities for mobile e-commerce and e-management within a ubiquitous (anytime and everywhere) business model. Embedded Geographic Information Systems (GISs) are specialized systems used mainly in navigation and for assisting mobile users. However, many actual navigation systems have some limitations due to their reduced computational power. The geographic information they can use covers only limited areas and its precision may be insufficient in many situations. Access to distant information sources is limited and the autonomy of the mobile device is inadequate. The advent of new technology changes the way information can be accessed and minimizes the differences between desktop applications and embedded ones by bringing the desktop power into mobile devices [2]. In this paper we propose a GIS based navigation system, which is based on a client-server architecture that allows the system mobile components to access distant information in a dynamic fashion. The architecture of this system is addressed and its main characteristics concerning the possibility to access remote information sources are discussed. The organization of this system consists of two main parts; client and server. The server consists of a relational database management system, vector and raster high-resolution images, which are made available to clients via the Internet. The proposed system provides differential global positioning system (DGPS) corrections. The mobile devices utilize these corrections to correct the GPS data and achieve better accuracy on a map derived from high-resolution earth observation (EO) data. In order to reduce the requirements for communications bandwidth, only information related to a small area (< 1Km2 ) around the mobile user is transmitted. While the access to the distant data server is accomplished via an Internet connection, the underlying physical connection could be GSM, GPRS or wireless LAN, depending on the availability and cost. This paper discusses also the targeted application, which is the SAINT (advancing Security & Anti-fraud by means of Info-mobility and Navigation Technologies) and then it presents the architecture and the main modules of the proposed system. The SAINT has been developed at the Joint Research Center at Ispra, Italy as an experimental effort for providing infomobility services that assist the security officers of the Ispra site. We also present how such an infomobility application facilitates monitoring over the Internet within the framework of security operations. The rest of the paper is organized as follows: Section 2 presents related work. The architecture of the proposed system is discussed in section 3. Some tests and preliminary results are presented in section 4. Conclusions and future directions are discussed in section 5.

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Related Work

Embedded Internet and Web based GISs have been rapidly evolving with the change of the Internet technologies. There are many approaches to represent spatially referenced and multimedia information on a GIS, depending on whether the information is static or dynamic, whether it is provided by the same or different sources locally or stored on distant servers. The embedded system presented in [10] is based on the use of the Internet to access geographical data. It mainly uses a Web browser for data presentation and processing. In this approach, a differential GPS is utilized to obtain the position of the mobile device and the communication between the embedded system and a distant server is based on the use of a cellular phone. 3D spatial data visualization in the context of Web based GIS is discussed in [3]. In this approach VRML has been used to implement a Web based user interface to a 3D GIS. However, the integration of several levels of details into a 3D-GIS seems to be difficult with reasonable response time and bandwidth. An approach for integrating the dynamic aspects of the natural environment into a GIS for decision support is presented in [7]. The architecture of this system focuses on providing decision support in a dynamic real-time situation, where the decision maker is responsible for guiding and directing people in the field. Monitoring urban dynamics by using very high resolution satellite imagery is also discussed in [4]. In [9] a system that integrates GIS and spatial libraries for conducting humanitarian assistance and disaster relief operations in urban environments is presented. This system has been developed as a decoupled component based system where new available components can be added in a plug-and-play fashion. It has been based in Commercial Of The Shelf (COTS) components (such as ArcView and 3D scene VRML viewers)for handling and processing spatial information. Another interesting approach presented in [1] demonstrates the Microsoft TerraServer spatial data warehouse, which is able to handle aerial, satellite and topographic images in a relation database management system (SQL server). The TerraServer system allows users to browse geographic information on the Web and it is mainly based on a mosaic grid system where tiles images are inserted into the database. In our approach, we use COTS components for the development of the system. This has the advantages of shortening the development time and producing robust and customizable modules. Moreover, the architecture of the system allows easy configuration and makes the modules open to future extensions. The proposed system has been designed to work in a distributed environment over Internet or intranet connections and can be easily configured to support Web based infomobility applications.

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System Architecture

The system integrates in-house tools and Commercial-Of-The-Shelf (COTS) components and provides the ability to rapidly assemble a custom repository of information about a geographic area. A major challenge is to provide a framework into which the best available tools can be integrated with minimal effort

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and in which these components can be connected to each other to create new applications. With this in mind, we designed SAINT as a component based system that will be able to support a continuous increase of functionality as new and more sophisticated tools become available. The SAINT system is based on a client server architecture paradigm. It is a distributed system where embedded visualization tools can be running on multiple clients, while the server delivers on demand any spatial information based on user’s requests. The server contains much of the data and whether the client asks for it, data is shipped over a communication link to the client. However, this solution may not suffice in the case where the communication link is too slow and the bulk of data is large. In such a case more functionality may be added to the client side to assist fast user responses by utilizing the local cache. There are currently available many techniques for managing such a cache (predictive caching, off-line synchronization and replication are few of them). However, an optimum solution here depends upon the rate at which a user moves and the rate at which traffic is generated for him. The server is composed of the following modules: 1. Communication module (for transferring data) 2. Visualization module 3. Geo-spatial database The figure 1 shows the client-server architecture of the SAINT system. The client contains a DGPS module and a local cache for storing temporal data. The service provided by the server include: – Access to the geographic repository through an interface, which specifies what geographic information can be accessed. – Query facilities by which the user is able to interrogate the spatial database. The core functionality of SAINT is based on COTS software (such as ArcPad and ArcView). In the under development version of the system, the communications between client and server is achieved by using Java Remote Method Invocation (RMI) and scripting HTTP (CGI, XML) modules. Conventional visualization of the geographic information and other typical GIS functions can be performed using ArcPad and ArcView software. We have also initiated work towards implementing a 3D visualization tool that would allow the navigation of a geographic region and the terrain. The 3D components are currently implemented by using VRML over a satellite image. The 3D scene in VRML has been made by using a proprietary VRML builder and its integration with the rest of the system is under investigation. 3.1

Communication and Data Transfer

Both the DGPS module and the visualization module require a communication system to send the GPS corrections and maps to the mobile terminal. Communications is very critical in infomobility applications and it has its own merit in developing a system that provides geo-positioning services.

Visualization Module ArcPad

GSM (9.6 Kbps) GPRS(110 Kbps) WLAN (11 Mbps)

Local cache Mobile device (client)

Communications Module

DGPS module

Communications Module

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Visualization Module ArcView

Geo-spatial Database Geo-spatial Server

Fig. 1. SAINT client-server architecture.

In the SAINT system, we have adopted Wireless Local Area Network (WLAN) technology for transferring data from the mobile terminals to the server and vice versa. WLAN communications provides the necessary bandwidth for transmitting long stream of data, such as video stream, from the handheld devices to the headquarter. In addition, if the handheld devices are equipped with a video camera, users could point their terminals in a specific direction and acquire in real-time an on-scene view. This will allow a team of users to see in real-time what is going on at a remote site facilitating in this way decision making and exploring the situation in real-time. The high data transfer rate of WLAN facilitates the transfer of large quantities of data and allows the system to accommodate more complex services such as real time video stream transmission and geographic messaging. Geographic messaging is the ability to send a message to specific geographic areas (in our case to a subset of mobile users). The headquarter might want to send messages only to users within a certain geographic range. Such a service can be used when the headquarter wants to notify only a few mobile users according to their position. This is also the case when people are requested to evacuate a particular geographic area due to some disaster or large accident. Alternatively, users could use geographic messaging to locate resources within a geographical region, which is defined as an arbitrary polygon. A “who is around service” would locate and identify the users present in a given geographical area. 3.2

GIS module and data content

This section describes the main types of data used in the system and the way of visualizing them. Furthermore a basic outline of the proposed database structure is given. For the visualization of the data, a fully functional desktop GIS (ArcView) is used on the server side and a lightweight GIS (ArcPad) is installed on the mobile handheld devices. For the current system a two-dimensional display of

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raster and vector layers on the headquarter and on the mobile GIS is foreseen. In parallel, tests have been done using 3D visualization tools, which allow free navigation within a three-dimensional environment and could provide additional visual information to the user who is not familiar with two-dimensional views. The file size of the raster data is reduced from about 10 MB to 300 KB by using wavelet based compression algorithms so that a visualization on the mobile device is possible. First results show that the use of very high-resolution satellite data and overlaid vector layers can provide a wealth of visual information also on the mobile terminal with its limited screen size and computing power All of the displayed layers have been assigned with a scale range in which they can be displayed to assure a maximum of information content on the screen. The following main data types have been embedded in the GIS of the proposed system: Raster data: are used for visualization of the study area and serve as a basis for the creation of additional vector data. High-resolution satellite data acquired in May 1999 by Space Imagings IKONOS satellite are tested, which can detect objects of 1-meter square in digital data. The data were provided as pan-sharpened, standard geometrically corrected in UTM/ WGS 84. Out of the four bands delivered (NIR, Red, Green, Blue), the band-combination used is RGB (red, green, blue) to obtain a natural colour image. To meet the requirements, which arise from including DGPS navigation and positioning information into the system information, the geometric quality of the raster data needs further enhancement. As no accurate DTM (Digital Terrain Model) for the study area is available, 2nd order polynomial transformation was applied by using DGPS control points. As the terrain shows only minor elevations, sub pixel accuracy could be achieved. In order to make the raster image usable also on mobile devices with limitations arising from computing and storing capacities, the image size is reduced by using MrSid, a wavelet based compression algorithm. Vector data: The vector data are used for visualization and to facilitate basic querying functions of the system. Three main object classes are present: buildings (polygons), streets (poly lines) and additional points of interest. They are derived from the raster image by using the on-screen digitizing capabilities of ERDAS Imagine and transforming them into ArcView shape files which then can also be viewed on the mobile device using ArcPad. Ancillary data: The ancillary data provide additional information from different sources on spatial and other properties of the displayed objects. To keep the data structure as clear as possible, the data stored in relational databases are divided into a main data table and a number of extra data tables, which are joined to the main table. The main data table contains static data. It is directly linked to the vector objects and provides information on their basic physical properties as position, size and name. This information is available to all users of the system without any restrictions. Querying can be done by pinpoint interrogation on the screen or with the help of common database query possibilities provided by ArcView and ArcPad. An additional field of

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the main database contains hyperlinks, which can be addressed directly from the screen. They may link to 3-D views of selected buildings, etc. The dynamic data (data which need regular updating) and security relevant data are stored in separate data tables, which are joined to the main data table. In this way maintaining and handling of the data is facilitated. For maintaining and querying of the data on the server side, specific user profiles can be created which regulate access to i.e. security relevant data. DGPS data: The DGPS data are used to visualize the actual position of a mobile user. The data are stored as separate ArcView shape files and can be visualized on the mobile and on the headquarter side. 3.3

Positioning and DGPS

To achieve their goals, infomobility applications need to know the position of the user. Different positioning system can be used, depending on the speed, environment, area of operation and accuracy needed by the application. There are at least four distinct families of positioning systems that may be potentially used in such applications. The first system family is called dead reckoning. It is based on sensors (accelerometers, gyroscopes or compass, odometers, etc) and provides the user with a position calculated step by step from an initialization position. The accuracy of such a system is deteriorating very quickly, and is function of the quality of the sensors. Even when using very expensive sensors, military systems cannot achieve a good accuracy (but they are mainly used because they are autonomous). An alternative positioning system family is called terrestrial radio-navigation and is mainly represented by the LORAN-C. This system uses transmitters to generate signals modulated by information related to the beacon. A mobile receiver uses these signals to calculate time to arrival, or difference of times to arrival (equivalent to distances between the transmitter and the receiver). As the position of the beacons is known, one can easily calculate the position of the receiver. The disadvantages of such a system are the limitation of coverage (essentially coastal), and the low accuracy, which is affected by the geographic situation. A promising positioning system family is the global navigation satellite system (GNSS). GNSS is a term used for worldwide positioning systems based on a constellation of satellites and their ground stations. The first component of GNSS is the American global positioning system (GPS) and the Russian global navigation satellite system GLONASS. Both are military systems with civilian access. At the moment, the Russian GNSS is not usable any more, due to a low number of satellites. GPS consists of 27 satellites orbiting at 10900 nautical miles, and 5 ground stations put on the equatorial circle to control the constellation. The GNSS receivers use the satellites (and their on-board transmitters) like beacons to calculate their position in the same way it is done for terrestrial radio-navigation systems. The accuracy of GPS is about 10 meters horizontally at 95% in real time. From satellites or aircrafts to pedestrian or birds, this

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accuracy permits to achieve quite a good positioning information for many applications worldwide. Some methodologies even permit to obtain accuracy better than a centimeter with signal processing techniques. Another promising positioning system is the Inertial Navigation System (INS). The INS contains triads of gyroscopes and accelerometers and associated analog and digital electronic circuits. The GPS antenna and receiver are mounted on the pointing instrument along with the INS. The GPS signals are used to correct drift errors in the INS position and orientation outputs. The position and orientation data (including GPS corrections) from the INS are sent to a computer, along with GPS time data. The computer selects the relevant data and processes these data through a series of transformation routines to generate command angles or instructions, in a preferred navigation coordinate frame, for pointing the instrument at a known stationary or moving target. For applications in local areas, the GPS accuracy can be narrowed down to a couple of meters by using differential GPS (DGPS) concept. DGPS involves at least two GPS receivers; the first one is stationary, and the rest navigate around making position measurements. The measurements are made between at least four satellites and the receiver; these measurements have some errors due to the trip made by the signal across atmosphere (ionosphere, troposphere) or to the position of satellites (ephemeris). The stationary receiver is placed at accurately known coordinates and calculates the error of each satellite measurement. These errors are then sent to the mobile receiver, which uses them to correct its measurements. Satellites have been recently used for regional coverage. Consequently, regional augmentation systems have been introduced to assist differential corrections. Such augmentation systems are the European Geostationary Navigation Overlay System (EGNOS), the Wide Area Augmentation System (WAAS) in the USA and the Multi-functional Transport Satellite (MTSAT) system in Japan. These regional augmentation systems aim at providing wide area differential corrections and additional satellite measurements as well as signal integrity information. The SAINT system aims at providing positioning information displayed on digital maps on portable handheld computers. The user requirement about accuracy is set to a couple of meters. Because the GPS accuracy (10 m 2D 95%) is not enough, DGPS has been used instead. As lightweight EGNOS receiver does not exist yet, local DGPS has been chosen. The complete JRC DGPS infrastructure needs one reference station (stationary receiver at known location) and one communication system to send the corrections to the mobile receiver. In order to keep the mobile terminal light enough, one PCMCIA GPS receiver has been integrated into the mobile terminal. Such receivers can easily track more than 10 satellites in parallel, and calculate GPS or DGPS in real time. The communication link can be the same as the one used for transmitting data. The figure 2 shows the representation of the differential GPS in the SAINT system as well as how the corrections are forwarded to the mobile handheld devices from the reference station, which resides at the site of Ispra. DGPS processing is accomplished according to the following steps:

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Reference Station

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Corrections pocket PC

Fig. 2. Differential GPS positioning.

– The reference station calculates the DGPS corrections. – DGPS corrections are transmitted (automatically or following a user request). – The mobile GPS receiver calculates its position. – This position is used by the mobile terminal, and sent to headquarters. 3.4

Hardware Architecture

The server of the SAINT system is hosted on a Windows NT system running on an Intel Pentium III. The imagery is maintained on the file system. Oracle has been used as a conventional database system for storing geographical and geo-positioning information. ArcView has been used as desktop GIS in the headquarter. The Handheld devices are Compaq iPAQ H3650 equipped with 32MB of memory, a WLAN interface and a GPS device connected on the serial port. The base station of the WLAN is the Cisco Aironet.

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Test and Results Implementation

GPS has been connected to the serial port. The visible part of the client can show different layers of a map (i.e. vector based layers and raster images). These layers constitute static information. The map on the mobile terminal also contains a dynamic layer corresponding to the position. After receiving GPS data, the system projects these data and visualizes them. Zoom capabilities and scale change are also supported.

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Tests

A prototype of the SAINT system is currently under development. An IKONOS image has been used to produce several GIS layers. The communications between the pocket PC and the distant server is accomplished through a wireless LAN connection. Both geographical and geo-positioning data may be exchanged between client and server over an internet connection. The figure 3 shows samples of the GPS position on a raster image, which is visualized on the ArcPad GIS. For such applications, the Internet connection over a wireless LAN provides a good performance and it guarantees acceptable data transfer rates.

Fig. 3. A pocket personal computer with an embedded GIS.

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Conclusions

The SAINT system is best understood as an initial experimental effort to demonstrate the ability of getting geographic and navigation assistance anytime anywhere. It integrates geo-positioning and geographic information and shows how this combination can greatly enhance site monitoring and security. The current version of the system aims at assisting security officers performing security operations. The long-term objectives of this system include providing humanitarian assistance and disaster relief operations in crisis situations. More work needs to be done on integrating map and other GPS data and on enhancing the query facilities of the system. A future direction also includes the development of new services such as ”who is around ” service. Such a service could be used to perform geographic messaging and execute location based queries.

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SAINT has raised a number of interesting issues in the communication framework needed for transferring data. There are a lot of alternatives that might be used for this purpose; WLAN, GPRS, GSM to name a few. What is the right communication framework for different infomobility applications remains an open issue. For applications whose geographic coverage does not exceed a few Km2 , WLAN seems to be an attractive and easy solution providing high data transfer rates up to 11Mbps. However, for other applications (rescue operations) that need to cover a large geographic area it might not be easy to install WLAN. In that case other communications means such as GPRS and GSM may be used instead.

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