Indoor positioning in peer-to-peer networks

We present two algorithms for indoor positioning in peer-to-peer networks. The setup is a network of two types of devices: reference devices with a known location, and user devices that can determine distances to reference devices and each other. We present two algorithms for positioning estimation in such a peer-to-peer network. The first one is purely geometric and reduces determining the best estimate for the position of a device to a least squares problem. The second approach can be considered as a probabilistic version of the geometric approach. We estimate the probability density function that a device is located at a position, given a probability density function for the positions of the other devices in the network, and a probability density function of the measured distances.