Data Processing for the Calibration of an Acoustic Local Positioning System

In local positioning systems (LPS) that use active beacons placed in the environment, the knowledge of the precise position of these beacons is supposed by the positioning algorithms. Previously the positions of the beacons have been directly measured or indirectly deduced and entered to the positioning system. In this work, a self-calibration method for LPS is presented that allows the deduction of the position of a number of N beacons from measurements of distances between these beacons and different test points in the area of measurements. Only the positions of three test points (in 3D positioning) have to be previously known, the rest (the number depending on the number of beacons) could be at any unknown position. The method has been developed for both spherical and hyperbolic positioning systems. In both cases simulated and real results have been presented.