Yongqi Chen

Effects of Sensor Errors on the Performance of Map Matching

Map matching has been widely applied in car navigation systems as an efficient method to display the location of vehicles on maps. Various map-matching algorithms have been proposed. Inevitably, the correctness of the map matching is closely related to the accuracy of positioning sensors, such as GPS or Dead Reckoning (DR), and the complexity of the road network and map, especially in urban areas where the GPS signal may be constantly blocked by buildings and the road network is complicated. The existing map matching algorithms cannot resolve the positioning problems under all circumstances. They sometimes give the wrong position estimates of the car on road; the result is called mismatching. In order to improve the quality of map matching, a deep understand of the accuracy of sensor errors on mismatching is important. This paper analyses various factors that may affect the quality of map matching based on extensive tests in Hong Kong. Suggestions to improve the success rate of map matching are also provided.

Potential Benefits of GPS/GLONASS/GALILEO Integration in an Urban Canyon – Hong Kong

With the existing GPS, the replenishment of GLONASS and the launching of Galileo there will be three satellite navigation systems in the future, with a total of more than 80 satellites. So it can be expected that the performance of the global navigation satellite system (GNSS) will be greatly improved, especially in urban environments. This paper studies the potential benefits of GPS/GLONASS/Galileo integration in an urban canyon – Hong Kong. The navigation performances of four choices (GPS alone, GPS+GLONASS, GPS+Galileo and GPS+GLONASS+Galileo) are evaluated in terms of availability, coverage, and continuity based on simulation. The results show that there are significant improvements in availability, coverage and continuity, by using GPS+GLONASS+Galileo compared with the other choices. But the performance is still not good enough for most navigation applications in urban environments.

A Simplified Map-Matching Algorithm for In-Vehicle Navigation Unit

Abstract GPS has been widely used for land, sea and air navigation. However, due to signal blockage and severe multipath environments in urban areas, GPS alone cannot satisfy most land vehicle navigation requirements. Dead Reckoning (DR) systems have been widely used to bridge the gaps of GPS and to smooth GPS position errors. However, the DR drift errors increase with time rapidly and frequent calibrations are required. As land vehicles have to be on roads, digital map can be used to constrain the locations of vehicles, known as map-matching, which is an efficient way to improve the performance of positioning systems while working under urban environment. In this paper, a simplified map-matching algorithm is proposed for an in-vehicle navigation unit, as the processing power of in-vehicle processor is limited. Extensive field tests have been conducted in Hong Kong and Macau. The results reveal this map-matching algorithm can improve the performance of the vehicle navigation unit significantly.

Application and evaluation of a GPS multi-antenna system for dam deformation monitoring

This paper describes GPS multi-antenna device (one GPS receiver links multiple antennas) developed by authors, and the experimental results are presented. GPS has already proven to be an efficient tool for monitoring dam deformations and stability of high-risk slopes. It offers greater accuracy than other surveying techniques. However, GPS has its disadvantages when employing for slope and dam monitoring. The major drawback has been high cost due to large-scale GPS deployments are required in monitoring sites. The conventional GPS monitoring methods, where a permanent GPS receiver must be located at each point, have significant limitations of the cost. A new approach that a single GPS receiver links multiple antennas mounted at the monitoring points, has been employed to solve these problems in this paper. A dedicated switching device has been developed by authors for this approach. Field testing results show that the dedicated switching device for GPS multi-antenna system has excellent performances. Post-processing positioning accuracy is around 1–2 mm for the deformation monitoring of the Xiaolangdi dam on the Yellow River.

An Integrated Map-Match Algorithm with Position Feedback and Shape-Based Mismatch Detection and Correction

Global Positioning System (GPS)-based vehicle navigation systems have been rapidly developed over recent years. In urban areas, due to the problems of satellite signal blockage and severe multipath effects, GPS may not be available for a long period of time. Integrated GPS/Dead Reckoning (DR) systems are commonly used to bridge GPS position gaps. Moreover, map-matching (MM) techniques can be implemented to improve positioning accuracy by locating an estimated vehicle position (from GPS/DR) on road; however, the reliability of map-matching methods is still a problem because vehicle position may be located to an incorrect road section (mismatch) due to large vehicle positioning errors from GPS/DR and complexity of road network, which is a typical environment in urban areas. In this article, we present a tightly integrated vehicle navigation system to overcome these problems. Performance of any MM algorithms is closely linked with position data quality. In our approach, we integrate MM results with GPS/DR output at the sensor level for data quality control and optimal estimation of sensor errors and vehicle position. Thus quality of position input to MM unit is significantly improved. Furthermore, GPS/DR output, together with road network, is used to detect and to automatically correct any mismatches occurred. We have implemented this integrated approach to a prototype vehicle navigation system and extensive tests have been carried out in Hong Kong urban areas. Testing results demonstrate that the performance of the new system is significantly improved in terms of accuracy, coverage, and reliability.

Seafloor Classification of Multibeam Sonar Data Using Neural Network Approach

In this study, the self-organizing map (SOM), which is an unsupervised clustering algorithm, and a supervised proportional learning vector quantization (PLVQ), are employed to develop a combined method of seafloor classification using multibeam sonar backscatter data. The PLVQ is a generalized learning vector quantization based on the proportional learning law (PLL). The proposed method was evaluated in an area where there are four types of sediments. The results show that the performance of the proposed method is better than the SOM and a statistical classification method.

A quantitative measure for the quality of INSAR interferograms based on phase differences

It is well-known that interferometric SAR (INSAR) is a technology for the generation of high-precision digital elevation models (DEM) and the precise measurement of terrain surface deformation. The accuracy of DEM and deformation measurement is highly dependent on the quality of the interferogram generated. Such an interferogram is constructed by a pointwise complex multiplication of corresponding pixels in both datasets, which are respectively contained in master image and registered image. An exanimation of existing literature reveals that there is no, good, quantitative measure for the quality of interferograms, and visual inspection is still the best solutions available so far. By visual inspection, one recognizes those interferograms with continuous fringes as good ones and regards those with many discontinuous interferograms and speckles as being not good. As the pixels in the interferogram represent the phase value values, it is natural to think that, if the quality is good, the phase differences between neighbor pixels should be small, and thus the sum of all phase differences will still be small. This leads to the proposal of “sum of phase differences” (SPD) as a quantitative measure for the quality of interferogram. Two simulation tests have been conducted, and the results show that the SPD is a reliable measure.

Geographical data acquisition

Geographical Data and Its Acquisition (Yuk-Cheung Lee): Introduction The Nature of Geographical Data Define the Nature and Scope of the Database Identify the Types of Features Design the Geographical Database A Survey of Data Acquisition Methods Geo-Reference Data Trends in Spatial Data Acquisition.- Coordinate Systems and Datum (Esmond Mok, Jason Chao): Coordinate Systems Geoid and Mean Sea Level Datum Ellipsoid Geodetic and Plane Coordinate Systems.- Transformation of Coordinates between Cartesian Systems (Xiao-Li Ding): Introduction Basic Concepts of Coordinate Transformations Models for Coordinate Transformation Derivation of Transformation Models Determination of Transformation Parameters.- Map Projections (Yuk-Cheung Lee): Introduction The Shape of the Earth Map Projections as Mathematical Transformations Geometric Distortions on Maps Preserving Some of the Geometric Properties Minimizing Geometric Distortions for a Project Area Naming of Map Projections Rectangular Grid System The UTM Projection The UTM Grid Integrating Maps of Different Projections Map Projection and Digital Maps Conclusions.- Geographical Data from Analogue Maps (Yuk-Cheung Lee, Lilian Pun): Introduction Vector and Raster Models The Choice between Vector and Raster Models Vector Digitizing Raster Scanning Conclusion.- Ground-Based Positioning Techniques (Steve Y.W. Lam, Yong-Qi Chen): Introduction Measurement of Distances and Angles Measurement of Height Reduction of Coordinates to Datum Detail Surveys.- Satellite-Based Positioning (Esmond Mok, Gunther Retscher): Concept of Satellite Positioning Absolute and Relative Positioning Differential GPS (DGPS) Technique Positioning Techniques for Surveying Real-Time Kinematic Positioning Future Developments.- Techniques for Underwater Data Acquisition (Gunther Retscher): Introduction and Overview Tidal and Other Water Level Changes Soundings Survey Preparation and Data Processing Summary and Outlook onFuture Developments.- Image Acquisition (Bruce King, Kent Lam): Introduction Image Types Imaging Devices Air Borne Imagery Space Borne Imagery.- Orthoimage Generation and Measurement from Single Images (Zhilin Li): Introduction The Principles for the Generation of Orthoimages Measurement from Single Image Procedure for Geo-Referencing Image and Measured Data Summary.- Geometric Data from Images (Bruce King): Introduction Stereoscopic Vision Stereo Photographs Height from Stereoscopic Parallax Planimetric Position from a Stereopair Analytical Methods Digital Methodologies.- Thematic Information from Digital Images (Qiming Zhou): Factors to be Considered for Thematic Information Extraction Feature Identification and Image Interpretation Image Processing for Thematic Information Extraction Summary.- Current Trends in Geographical Data Acquisition: An Epilogue (Zhilin Li, Yong-Qi Chen).- References.- Subject Index

Ground settlement of Chek Lap Kok Airport, Hong Kong, detected by satellite synthetic aperture radar interferometry

Satellite synthetic aperture radar (SAR) interferometry is used to investigate the slowly accumulating ground settlement at the new Chek Lap Kok Airport in Hong Kong. Most of the land occupied by the airport was reclaimed from the sea and therefore certain ground settlement in the area has been expected. A pair of ERS-2 SAR images spanning nearly a year is used in the study. The high spatial resolution (20 mx20 m) ground settlement map derived indicates that the settlement that occurred in the area over the time period is as large as 50 mm. The SAR measurement results agree with the levelling measurements at some benchmarks in the area to well within 1 cm(rms error), and the overall correlation between the two types of results is 0.89. The paper presents some brief background of interferometric SAR, and outlines the data processing methods and results.

A multi-antenna GPS system for local area deformation monitoring

A new method of using GPS for monitoring local area deformations such as landslides is presented. Unlike the standard method of using GPS for deformation monitoring where a GPS receiver is required for each point to be monitored, the new method allows multiple points to be monitored with one receiver. A system that implements the concept has been developed. It uses a specially designed electronic component that allows a number of GPS antennas to be linked to a single GPS receiver. The receiver takes data sequentially from each of the antennas attached to the receiver. A distinctive advantage of the approach is that one GPS receiver can be used to monitor more than one point. The cost per monitored point is therefore significantly reduced. The design of the system, as well as the data management and processing strategies will be introduced in detail. Results from some preliminary tests will also be given.