Google+ GPS Phone Tracker data processing can be automated | StoryMaker™

GPS Phone Tracker data processing can be automated

In this chapter we use the lessons of Personal GPS receiver design to suggest desirable features of future GNSS infrastructure. We investigated A-GPS, with an emphasis on practical implementation. In particular, we focused on practical receiver design for commercial applications, such as mobile phones and personal navigation devices. We have concentrated on what is actually done in A-GPS design, based on the available constellations, and real price and size constraints, based on the available semiconductor technology as of the time of this writing. In this chapter, we take a more expansive view, by looking at the coming GNSS constellations and applying what we have learned in the previous chapters to discuss desirable design features in the GNSS infrastructure itself. Now that we are looking to the future, we can imagine a different practical world from that of 2008/2009. There will be far more navigation satellites available, and semiconductor technology will probably continue to improve at the rate predicted by Moore’s law. GNSS are partitioned into three segments: space, control, and user segments. When we talk about the GNSS infrastructure, we mean the space and control segments. One of the key ideas of this chapter is that future GNSS infrastructure could include features that benefit A-GNSS, not just in the design of the spacecraft and signals, but in the control segment on the ground.

GIS data has long been captured from paper records such as digitizing and scanning paper maps. Photogrammetry, remote sensing, and conventional surveying has also been data sources for GIS. More recently, data collected in the field with DGPS has become significant in Magnetic GPS . GIS data collection with DGPS requires the integration of the position of features of interest and relevant attribute information about those features. Whether a handheld data logger, an electronic notebook, or a pen computer are used, the attributes to be collected are defined by the data dictionary designed for the particular GIS. In GIS it is frequently important to return to a particular site or feature to perform inspections or maintenance. DGPS with real-time correction makes it convenient to load the position or positions of features into a data logger, and navigate back to the vicinity. But to make such applications feasible, a GIS must be kept current. It must be maintained.

DGPS allows the immediate attribution and validation in the field with accurate and efficient recording of position. In the past, many GIS mapping efforts have often relied on ties to street centerlines, curb-lines, railroads, and so forth. Such dependencies can be destroyed by demolition or new construction. But, meter level positional accuracy even in obstructed environments such as urban areas, amid high-rise buildings, is possible with DGPS. In other words, with GPS Mini Tracker the control points are the satellites themselves. Therefore it can provide reliable positioning even if the landscape has changed. And its data can be integrated with other technologies, such as laser range-finders, and so forth, in environments where DGPS is not ideally suited to the situation. Finally, loading GPS data into a GIS platform does not require manual intervention. GPS data processing can be automated; the results are digital and can pass into a GIS format without redundant effort, reducing the chance for errors.

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