Typically, a Kalman filter is only as accurate as your mathematical model of the underlying phenomena (for example, your flight dynamics on an airplane), and the filter is mainly useful to mitigate the noise from your real-world sensor observations. Is there more public information available about the mathematical model being used within their state transition matrix? Depending on that information, this could be really clever or a glorified low-pass filter.
All you kalman filter fans out there will be happy to hear that you can grab a ride from SideCar and some Giants tickets from SeatGeek[1] for a truly algorithmic afternoon.<p>1. <a href="http://chairnerd.seatgeek.com/using-a-kalman-filter-to-predict-ticket-prices/" rel="nofollow">http://chairnerd.seatgeek.com/using-a-kalman-filter-to-predi...</a>
Not an expert in this field, but amusing to me in that the only other place i've had the fortune of encountering kalman filters were groups trying to analyze neuro data from Blackrock Utah micro electrode arrays.<p>Brain signals, brunch, they all look the same...