Abstract
This paper presents the results from a study on the use of Graph Signal Processing (GSP) techniques for satellite-based navigation systems. Graph Signal Processing, an emerging and innovative way of processing signal and information on a graph, had established some unique advantages in analyzing very large datasets, or big data that usually pose a significant challenge for conventional signal processing techniques. This paper described the theoretical background of and commonly-used tools in Graph Signal Processing; and presented the results from multiple recent studies where Graph Signal Processing had been used for analyzing large datasets in various applications. As the trend of navigation system design moves from single, standalone systems to networked, collaborative systems, Graph Signal Processing has a great potential to be used in the design of networked, collaborative navigation systems with upgraded capacity and enhanced reliability since the formation of satellite-based navigation systems can be naturally represented in the form of a graph with nodes (satellites and receivers) correlating to each other. For such reasons, the feasibility of using Graph Signal Processing for applications in satellite-based navigation systems was investigated and discussed in this paper. Ways of constructing graphs based on different types of measurements obtained from satellites at the receiver side were discussed in this paper. An example was then given in the paper using simulated GPS data to show the possible use of Graph Signal Processing in the detection of anomalies in GPS measurements for integrity monitoring.
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