  In this paper we present an approach to geometry calibration in wireless
acoustic sensor networks, whose nodes are assumed to be equipped with a compact
microphone array. The proposed approach solely works with estimates of the
distances between acoustic sources and the nodes that record these sources. It
consists of an iterative weighted least squares localization procedure, which
is initialized by multidimensional scaling. Alongside the sensor node
locations, also the positions of the acoustic sources are estimated.
Furthermore, we derive the Cramer-Rao lower bound (CRLB) for source and sensor
position estimation, and show by simulation that the estimator is efficient.
