Using Code Loop Tracking Observations to Characterize GNSS Receivers

Benjamin H. Downing

Peer Reviewed

Abstract: The landscape of Global Navigation Satellite Systems (GNSS) signals is undergoing significant change. The parallel development of new, more robust and versatile signals along with two new GNSS systems with global reach is having a dramatic impact on the development of GNSS receivers. Receiver manufacturers are continually developing and implementing unique signal acquisition and tracking algorithms, advanced integrity monitoring algorithms, advanced multipath mitigation algorithms and a host of other enhancements in an effort to improve the performance of GNSS receivers and make their products stand out in a crowded field. The objective of this research is to develop a methodology for comparing the pseudorandom noise (PRN) code tracking performance of various receivers. While the overall performance of a receiver depends on many more factors, effective PRN code tracking is fundamental to the operation of a GNSS receiver. The methodology developed in this research requires three fundamental measurements from the receiver under test – code pseudorange, carrier pseudorange and carrier-to-noise-density ratio (C/No). These measurements are generated by all GNSS receivers but may not always be available to the user. Therefore, this methodology can only be performed on receivers that output these values. This methodology might be useful as a tool to evaluate the suitability of various receivers in certain environments or applications (e.g., weak signal environments, high dynamic environments, unfriendly radio frequency (RF) interference environments, etc.) and also as a means of comparing the relative performance of receivers in those environments or applications. Expectations for the research were that the data collection and analysis techniques would generate code loop tracking jitter plots that closely tracked with theoretical curves. In addition, it was expected that different receivers would yield slightly different jitter plots giving them a unique “signature.” Finally, it was expected that some receivers might incorporate scalar code tracking loops and others might incorporate vector tracking loops. The methodology was developed and refined using three receivers from three popular manufacturers, each with a unique set of capabilities. Raw data was collected from each receiver and processed using purpose built algorithms to estimate the code loop tracking jitter for each signal for each receiver. The code loop tracking observations for each of the three receivers tested were compared with theoretical curves generated using closed form equations published in previous papers. In most cases, the data compared favorably. However, there were some significant outliers that are worthy of additional research and analysis. In addition, the jitter plots for one receiver tested indicated that it used scalar code tracking loops and the jitter plots for the other two receivers indicated that they use vector tracking loops. It appears to be possible to determine if a receiver uses scalar tracking loops or vector tracking loops based on the jitter estimates generated in this research. This research indicated that the methodology might be a useful tool for 2 characterizing GNSS receivers and, eventually evaluating their performance in various environments. However, more data collection and analysis is required to further validate and refine the methodology. Also, more analysis of the signals that yielded “non-conforming” jitter plots should be examined in more detail.
Published in: Proceedings of the 30th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS+ 2017)
September 25 - 29, 2017
Oregon Convention Center
Portland, Oregon
Pages: 3615 - 3638
Cite this article: Downing, Benjamin H., "Using Code Loop Tracking Observations to Characterize GNSS Receivers," Proceedings of the 30th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS+ 2017), Portland, Oregon, September 2017, pp. 3615-3638.
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