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Introduction to Random Signals and Applied Kalman Filtering with Matlab Exercises, 4th Edition by Patrick Y. C. Hwang, Robert Grover Brown

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9

Kalman Filter Applications To The GPS And Other Navigation Systems

The Global Positioning System (GPS) has established itself over more than two decades of operation as a reliable and accurate source of positioning and timing information for navigation applications (1). Perhaps the clearest mark of its resounding success is found in the widespread use of low-cost GPS modules embedded in many modern-day utilities such as smartphones and car navigators. “GPS” is now a well-recognized acronym in our cultural lexicon. Ironically, a testament to its technological maturity actually lies in a growing emphasis of advanced research work into navigation areas beyond GPS, i.e., into so-called “GPS denied” situations. Without a doubt, the usefulness of GPS has far surpassed what had originally been envisioned by its early designers, thanks in large part to a creative and competitive community of navigation users, practitioners and developers (2). As we venture nearer a new dawn of multiple global navigation satellite systems (GNSS), that will have largely drawn from the GPS experience, we may yet see even more new and exciting concepts that take advantage of what will be a bountiful abundance of satellite navigation signals in space.

9.1 POSITION DETERMINATION WITH GPS

An observer equipped to receive and decode GPS signals must then solve the problem of position determination. In free space, there are three dimensions of position that need to be solved. Also, an autonomous user is not expected ...

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