Cooperative Localization in NLOS Environments Using Semidefinite Programming

Abstract

In this letter, cooperative source localization using range-based measurements in severe non-line-of-sight (NLOS) environments is studied. The accuracy of localization can significantly degrade in indoor and dense environments, where the majority of connections are NLOS. Cooperative localization is highly beneficial in such environments by improving localization performance considerably. However, NLOS connections still must be handled properly. In this work, a novel cooperative localization algorithm with the ability to mitigate NLOS propagation based on semidefinite programming (SDP) is derived. It is assumed that the algorithm knows neither which connections are NLOS nor the distribution of NLOS propagation. The performance of the proposed SDP method is compared with that of the optimal maximum-likelihood estimator and several previously considered methods through computer simulations. It will be shown that the proposed SDP method substantially outperforms other methods in NLOS environments.