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The effect of relative update rates on tracking performance

In multi-sensor fusion applications, various sources of data are combined to create a coherent situational picture. The ability to track multiple targets using multiple sensors is an important problem. The data provided by these sensors can be of varying quality, such as data from RADAR and AIS. Does this varied quality of data negatively impact the tracking performance when compared to using the best data source alone? From an information-theoretic standpoint, the answer would be no. However, this paper investigates this issue and exposes a few caveats. In particular, this study addresses how the relative update rate of varying quality sensors affects tracking performance and answers the question 'Is more data always better?'