Asynchronous particle filter for tracking using non-synchronous sensor networks

This paper deals with the problem of tracking using a sensor network when the sensors are not synchronised. We propose a new algorithm called the asynchronous particle filter that, with much less computational burden than the traditional particle filter, has a slightly poorer performance. Thus, it is a good solution to real-time applications with non-synchronised sensors when high performance is required. The low computational burden of the method lies in the fact that we do not predict and update the state every time a measurement is collected. Its high performance is due to the fact that we account for the time instant at which each measurement was taken.

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