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A convenient technique for mitigating the impact of non-line of sight (NLOS) ranging errors on the positioning accuracy within indoor ultra wideband (UWB) ad-hoc networks is proposed in this paper. At first, classical ranging error models are adapted to the specific indoor UWB context by considering real channel measurements, which were performed in the band [2:6] GHz. Then, it is demonstrated that a prior knowledge of the ranging statistics coupled with a cooperative maximization of the global likelihood among the network, make it possible to reduce significantly the uncertainty on the estimated positions. This algorithm preserves a reasonable level of complexity in each node by adopting a distributed and asynchronous approach for the maximization process. Some simulations have been carried out to illustrate the relevance of such an approach, and predict the achievable performances of the proposed algorithm in typical 3D indoor environments. Results seem to show that the NLOS error mitigation is all the more efficient relative to traditional least-squares techniques since the connectivity is high.