Self Localization of Acoustic Sensor Networks

We present algorithms for self-localization of a network of sensors. We consider the case when no “anchor” nodes with known locations are present. We use source signals in the scene, also at unknown locations, to estimate time-of-arrival and direction-of-arrival between sources and sensors. These measurements are used to compute maximum likelihood relative calibration solutions, in which sensor nodes are localized and oriented with respect to one another. Prior location information, in the form of uncertain aimpoints for a subset of the sensors, are then be used to obtain maximum a posteriori estimates of absolute locations and orientations. We derive analytical statistical performance bounds for the two estimators, and present examples that illustrate the performance of the algorithms.