Global Positioning System

About: Global Positioning System is a research topic. Over the lifetime, 53739 publications have been published within this topic receiving 697151 citations. The topic is also known as: GPS & Global Positioning System, GPS.

GPS Meteorology: Remote Sensing of Atmospheric Water Vapor Using the Global Positioning System

Abstract: We present a new approach to remote sensing of water vapor based on the global positioning system (GPS). Geodesists and geophysicists have devised methods for estimating the extent to which signals propagating from GPS satellites to ground-based GPS receivers are delayed by atmospheric water vapor. This delay is parameterized in terms of a time-varying zenith wet delay (ZWD) which is retrieved by stochastic filtering of the GPS data. Given surface temperature and pressure readings at the GPS receiver, the retrieved ZWD can be transformed with very little additional uncertainty into an estimate of the integrated water vapor (IWV) overlying that receiver. Networks of continuously operating GPS receivers are being constructed by geodesists, geophysicists, government and military agencies, and others in order to implement a wide range of positioning capabilities. These emerging GPS networks offer the possibility of observing the horizontal distribution of IWV or, equivalently, precipitable water with unprecedented coverage and a temporal resolution of the order of 10 min. These measurements could be utilized in operational weather forecasting and in fundamental research into atmospheric storm systems, the hydrologic cycle, atmospheric chemistry, and global climate change. Specially designed, dense GPS networks could be used to sense the vertical distribution of water vapor in their immediate vicinity. Data from ground-based GPS networks could be analyzed in concert with observations of GPS satellite occultations by GPS receivers in low Earth orbit to characterize the atmosphere at planetary scale.

Global Positioning System: Theory and Practice

Abstract: 1 Introduction- 11 The origins of surveying- 12 Development of global surveying techniques- 121 Optical global triangulation- 122 Electromagnetic global trilateration- 13 History of the Global Positioning System- 131 Navigating with GPS- 132 Surveying with GPS- 2 Overview of GPS- 21 Basic concept- 22 Space segment- 221 Constellation- 222 Satellites- 223 Operational capabilities- 224 Denial of accuracy and access- 23 Control segment- 231 Master control station- 232 Monitor stations- 233 Ground control stations- 24 User segment- 241 User categories- 242 Receiver types- 243 Information services- 3 Reference systems- 31 Introduction- 32 Coordinate systems- 321 Definitions- 322 Transformations- 33 Time systems- 331 Definitions- 332 Conversions- 333 Calendar- 4 Satellite orbits- 41 Introduction- 42 Orbit description- 421 Keplerian motion- 422 Perturbed motion- 423 Disturbing accelerations- 43 Orbit determination- 431 Keplerian orbit- 432 Perturbed orbit- 44 Orbit dissemination- 441 Tracking networks- 442 Ephemerides- 5 Satellite signal- 51 Signal structure- 511 Physical fundamentals- 512 Components of the signal- 52 Signal processing- 521 Receiver design- 522 Processing techniques- 6 Observables- 61 Data acquisition- 611 Code pseudoranges- 612 Phase pseudoranges- 613 Doppler data- 614 Biases and noise- 62 Data combinations- 621 Linear phase combinations- 622 Code pseudorange smoothing- 63 Atmospheric effects- 631 Phase and group velocity- 632 Ionospheric refraction- 633 Tropospheric refraction- 634 Atmospheric monitoring- 64 Relativistic effects- 641 Special relativity- 642 General relativity- 643 Relevant relativistic effects for GPS- 65 Antenna phase center offset and variation- 66 Multipath- 661 General remarks- 662 Mathematical model- 663 Multipath reduction- 7 Surveying with GPS- 71 Introduction- 711 Terminology definitions- 712 Observation techniques- 713 Field equipment- 72 Planning a GPS survey- 721 General remarks- 722 Presurvey planning- 723 Field reconnaissance- 724 Monumentation- 725 Organizational design- 73 Surveying procedure- 731 Preobservation- 732 Observation- 733 Postobservation- 734 Ties to control monuments- 74 In situ data processing- 741 Data transfer- 742 Data processing- 743 Trouble shooting and quality control- 744 Datum transformations- 745 Computation of plane coordinates- 75 Survey report- 8 Mathematical models for positioning- 81 Point positioning- 811 Point positioning with code ranges- 812 Point positioning with carrier phases- 813 Point positioning with Doppler data- 82 Differential positioning- 821 Basic concept- 822 DGPS with code ranges- 823 DGPS with phase ranges- 83 Relative positioning- 831 Phase differences- 832 Correlations of the phase combinations- 833 Static relative positioning- 834 Kinematic relative positioning- 835 Pseudokinematic relative positioning- 9 Data processing- 91 Data preprocessing- 911 Data handling- 912 Cycle slip detection and repair- 92 Ambiguity resolution- 921 General aspects- 922 Basic approaches- 923 Search techniques- 924 Ambiguity validation- 93 Adjustment, filtering, and smoothing- 931 Least squares adjustment- 932 Kalman filtering- 933 Smoothing- 94 Adjustment of mathematical GPS models- 941 Linearization- 942 Linear model for point positioning with code ranges- 943 Linear model for point positioning with carrier phases- 944 Linear model for relative positioning- 95 Network adjustment- 951 Single baseline solution- 952 Multipoint solution- 953 Single baseline versus multipoint solution- 954 Least squares adjustment of baselines- 96 Dilution of precision- 97 Accuracy measures- 971 Introduction- 972 Chi-square distribution- 973 Specifications- 10 Transformation of GPS results- 101 Introduction- 102 Coordinate transformations- 1021 Cartesian coordinates and ellipsoidal coordinates- 1022 Global coordinates and local level coordinates- 1023 Ellipsoidal coordinates and plane coordinates- 1024 Height transformation- 103 Datum transformations- 1031 Three-dimensional transformation- 1032 Two-dimensional transformation- 1033 One-dimensional transformation- 104 Combining GPS and terrestrial data- 1041 Common coordinate system- 1042 Representation of measurement quantities- 11 Software modules- 111 Introduction- 112 Planning- 113 Data transfer- 114 Data processing- 115 Quality control- 116 Network computations- 117 Data base management- 118 Utilities- 119 Flexibility- 12 Applications of GPS- 121 General uses of GPS- 1211 Global uses- 1212 Regional uses- 1213 Local uses- 122 Attitude determination- 1221 Theoretical considerations- 1222 Practical considerations- 123 Airborne GPS for photo-control- 124 Interoperability of GPS- 1241 GPS and Inertial Navigation Systems- 1242 GPS and GLONASS- 1243 GPS and other sensors- 1244 GPS and the Federal Radionavigation Plan- 125 Installation of control networks- 1251 Passive control networks- 1252 Active control networks- 13 Future of GPS- 131 New application aspects- 132 GPS modernization- 1321 Future GPS satellites- 1322 Augmented signal structure- 133 GPS augmentation- 1331 Ground-based augmentation- 1332 Satellite-based augmentation- 134 GNSS- 1341 GNSS development- 1342 GNSS/Loran-C integration- 135 Hardware and software improvements- 1351 Hardware- 1352 Software- 136 Conclusion- References

Particle filters for positioning, navigation, and tracking

Abstract: A framework for positioning, navigation, and tracking problems using particle filters (sequential Monte Carlo methods) is developed. It consists of a class of motion models and a general nonlinear measurement equation in position. A general algorithm is presented, which is parsimonious with the particle dimension. It is based on marginalization, enabling a Kalman filter to estimate all position derivatives, and the particle filter becomes low dimensional. This is of utmost importance for high-performance real-time applications. Automotive and airborne applications illustrate numerically the advantage over classical Kalman filter-based algorithms. Here, the use of nonlinear models and non-Gaussian noise is the main explanation for the improvement in accuracy. More specifically, we describe how the technique of map matching is used to match an aircraft's elevation profile to a digital elevation map and a car's horizontal driven path to a street map. In both cases, real-time implementations are available, and tests have shown that the accuracy in both cases is comparable with satellite navigation (as GPS) but with higher integrity. Based on simulations, we also argue how the particle filter can be used for positioning based on cellular phone measurements, for integrated navigation in aircraft, and for target tracking in aircraft and cars. Finally, the particle filter enables a promising solution to the combined task of navigation and tracking, with possible application to airborne hunting and collision avoidance systems in cars.

Global Positioning Systems, Inertial Navigation, and Integration

Abstract: An updated guide to GNSS and INS, and solutions to real-world GPS/INS problems with Kalman filtering Written by recognized authorities in the field, this second edition of a landmark work provides engineers, computer scientists, and others with a working familiarity with the theory and contemporary applications of Global Navigation Satellite Systems (GNSS), Inertial Navigational Systems (INS), and Kalman filters. Throughout, the focus is on solving real-world problems, with an emphasis on the effective use of state-of-the-art integration techniques for those systems, especially the application of Kalman filtering. To that end, the authors explore the various subtleties, common failures, and inherent limitations of the theory as it applies to real-world situations, and provide numerous detailed application examples and practice problems, including GNSS-aided INS, modeling of gyros and accelerometers, and SBAS and GBAS. Drawing upon their many years of experience with GNSS, INS, and the Kalman filter, the authors present numerous design and implementation techniques not found in other professional references. This Second Edition has been updated to include: GNSS signal integrity with SBAS Mitigation of multipath, including results Ionospheric delay estimation with Kalman filters New MATLAB programs for satellite position determination using almanac and ephemeris data and ionospheric delay calculations from single and dual frequency data New algorithms for GEO with L1 /L5 frequencies and clock steering Implementation of mechanization equations in numerically stable algorithms To enhance comprehension of the subjects covered, the authors have included software in MATLAB, demonstrating the working of the GNSS, INS, and filter algorithms. In addition to showing the Kalman filter in action, the software also demonstrates various practical aspects of finite word length arithmetic and the need for alternative algorithms to preserve result accuracy.

GPS satellite surveying

Abstract: Elements of Satellite Surveying The Global Positioning System Adjustment Computations Least-Squares Adjustment Examples Links to Physical Observations The Three-Dimensional Geodetic Model GPS Observables Propagation Media, Multipath, and Phase Center Processing GPS Carrier Phases Network Adjustments Ellipsoidal and Conformal Mapping Models Useful Transformations Datums, Standards, and Specifications Appendices References Abbreviations for Frequently Used References Indexes.