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Global positioning system clock and orbit statistics and precise point positioning.

机译：全球定位系统的时钟和轨道统计信息以及精确的点定位。

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摘要

The orbit and clock errors of GPS satellites are examined culminating in error distributions and Gaussian overbounds. The Precise Orbit and Clock (POC) data are then used to produce a Precise Point Position (PPP) solution with a maximum vertical error of +/-1 meter. Flight test data are processed using the Single Difference Residual (SDR) method to detect and correct cycle-slips. The corrected carrier phase measurements are then used in PPP to determine the user's position. The results are compared with truth data to characterize the PPP solution accuracy performance.;POC data from the International GNSS Service (IGS), National Geospatialintelligence Agency (NGA), and the Center for Orbit Determination in Europe (CODE), are used as the truth reference and compared to the broadcast GPS ephemerides obtained from the Scripps Orbit and Permanent Array Center (SOPAC). The error is then analyzed over the three year period from June 2005, through June 2008. Two hundred forty-seven events in which the error in orbit or clock exceed 25 m are identified. These events are classified as outliers. The outliers are compared against data from IGS station receivers to determine if the event is observable. Observable events are reclassified as anomalies. Thirteen anomalies are identified and tabularized to enable future researchers to test anomaly detection mechanisms against historical events. The table of anomalies represents an original contribution to existing research in this field.;The anomalies are removed from the data. The remaining data are analyzed statistically. Seven error metrics are analyzed. Error distribution and a Gaussian overbound are provided by error metric and satellite block type.;The error data are then differenced over time. Three Operational Scenarios (OSs) are analyzed. OS1 is the normal operating procedure in which each ephemeris is used as soon as it is received. OS2 uses only one ephemeris. In OS2 the ephemeris is used from the time it is received until it expires, or until the satellite health is set to unhealthy. OS3 uses each ephemeris as it becomes available but the transitions are made continuous. OS2 and OS3 require that the duration of the anomaly be extended. These data are tabularized separately. Distributions for the error data and Gaussian overbounds are provided. Distributions are provided by error metric, block type, and time interval.;Flight test data are preprocessed using the SDR method to detect and remove cycle-slips before performing a PPP solution. The SDR method requires five satellites and can detect a cycle-slip on one satellite. This is done by comparing the precise average velocity residual for each solution with one satellite removed. Removal of a cycle-slipped satellite removes the clock velocity error from the solution and allows the offending satellite to be identified.
机译：对GPS卫星的轨道和时钟误差进行了检查，最终得出误差分布和高斯越界。然后，将精确轨道和时钟（POC）数据用于产生最大垂直误差为+/- 1米的精确点位置（PPP）解决方案。使用单差残差（SDR）方法处理飞行​​测试数据，以检测和校正周跳。然后在PPP中使用校正后的载波相位测量值来确定用户的位置。将结果与真实数据进行比较，以表征PPP解决方案的准确度性能。将来自国际GNSS服务（IGS），国家地理空间情报局（NGA）和欧洲轨道确定中心（CODE）的POC数据用作真相参考，并与从Scripps轨道和永久阵列中心（SOPAC）获得的GPS广播星历进行比较。然后在从2005年6月到2008年6月的三年中分析该错误。确定了247个事件，其中轨道或时钟误差超过25 m。这些事件被分类为异常值。将异常值与来自IGS站接收器的数据进行比较，以确定事件是否可观察到。可观察的事件被重新分类为异常。识别出13种异常并将其制成表格，以使未来的研究人员能够针对历史事件测试异常检测机制。异常表代表了对该领域现有研究的原始贡献。异常已从数据中删除。其余数据进行统计分析。分析了七个错误指标。误差度量和卫星块类型提供了误差分布和高斯超限。然后，误差数据会随时间变化。分析了三种操作方案（OS）。 OS1是正常的操作过程，在接收到每个星历后便立即使用它。 OS2仅使用一个星历表。在OS2中，从接收到星历开始就使用星历，直到星历过期或将卫星健康设置为不健康为止。 OS3在每个星历可用时使用它，但过渡是连续的。 OS2和OS3要求延长异常持续时间。这些数据分别制成表格。提供了错误数据和高斯越界的分布。通过错误度量，块类型和时间间隔提供分布。;在执行PPP解决方案之前，使用SDR方法对飞行测试数据进行预处理，以检测并消除周期滑移。 SDR方法需要五颗卫星，并且可以检测到一颗卫星的周跳。这是通过比较每个解决方案的精确平均速度残差与一颗人造卫星的相移来完成的。移出周期滑动卫星可以消除解决方案中的时钟速度误差，并可以识别出有问题的卫星。

著录项

  • 作者

    Cohenour, John C.;

  • 作者单位

    Ohio University.;

  • 授予单位 Ohio University.;
  • 学科 Engineering Electronics and Electrical.
  • 学位 Ph.D.
  • 年度 2009
  • 页码 146 p.
  • 总页数 146
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 无线电电子学、电信技术;
  • 关键词

  • 入库时间 2022-08-17 11:38:25

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