Distributed least-squares estimation applied to GNSS networks

In view of the recent proliferation of low-cost mass-market receivers, the number of network receivers and GNSS users will be growing rapidly, demanding an efficient way of data processing in terms of computational power and capacity. One way of improving the computational capacity is to decentralize the underlying data processing and distribute the task of the computer center across individual network receivers. In this invited contribution we review the problem of distributed estimation and present an algorithm for distributed least-squares estimation using the alternating direction method of multipliers. Applying the algorithm to a network of GNSS receivers, we show how the distributed data processing of individual receivers can deliver parameter solutions comparable to their centralized network-derived counterparts. With distributed estimation techniques, GNSS single-receiver users can therefore obtain high-precision solutions without the need of having a centralized computing center.