Reconstructing diffusion fields sampled with a network of arbitrarily distributed sensors

Sensor networks are becoming increasingly prevalent for monitoring physical phenomena of interest. For such wireless sensor network applications, knowledge of node location is important. Although a uniform sensor distribution is common in the literature, it is normally difficult to achieve in reality. Thus we propose a robust algorithm for reconstructing two-dimensional diffusion fields, sampled with a network of arbitrarily placed sensors. The two-step method proposed here is based on source parameter estimation: in the first step, by properly combining the field sensed through well-chosen test functions, we show how Prony's method can reveal locations and intensities of the sources inducing the field. The second step then uses a modification of the Cauchy-Schwarz inequality to estimate the activation time in the single source field. We combine these steps to give a multi-source field estimation algorithm and carry out extensive numerical simulations to evaluate its performance.