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Error Modeling for Differential GPS.
| 题名： | Error Modeling for Differential GPS. |
| 作者： | Bierman, Gregory S.; |
| 关键词： | MATHEMATICAL MODELS, ERROR ANALYSIS, GLOBAL POSITIONING SYSTEM, TIME INTERVALS, POSITION(LOCATION), OPTIMIZATION, DATA MANAGEMENT, SIGNAL TO NOISE RATIO, AUTOCORRELATION, ANALYSIS OF VARIANCE, ACCURACY, THESES, BASE LINES, NAVIGATION SATELLITES, FAST FOURIER TRANSFORMS, NONLINEAR ANALYSIS, RANGE(DISTANCE), BIAS, MARKOV PROCESSES, ERROR CORRECTION CODES, CROSS CORRELATION, EPHEMERIDES, TRIANGULATION, CURVE FITTING. |
| 摘要： | Differential GPS (DGPS) positioning is used to accurately locate a GPS receiver based upon the well-known position of a reference site. In utilizing this technique, several errors sources contribute to position inaccuracy. This thesis investigates the error in DGPS operation and attempts to develop a statistical model for the behavior of this error. The model for DGPS error is developed using GPS data collected by Draper Laboratory. The Marquardt method for non-linear curve-fitting is used to find the parameters of a first order Markov process that models the average errors from the collected data. The results show that a first order Markov process can be used to model the DGPS error as a function of baseline distance and time delay. The model's time correlation constant is 3847.1 seconds (1.07 hours) for the mean square error. The distance correlation constant is 122.8 kilometers. The total process variance for the DGPS model is 3.73 meters square. |
| 总页数： | 100 |
| 报告类型： | 科技报告 |
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