Practical precision bound for indoor location determination

摘要

This paper proposes a practical precision bound (PPB) to estimate the achievable localization precision for an indoor location determination system in a given environment. We evaluate the PPB using both database-based and range-based indoor systems in an office building. We further compare PPB with Cramer-Rao bound (CRB), a classic lower bound estimator based on the variance of a deterministic parameter. Experimental results indicate that PPB provides a very close bound to the CRB when CRB uses a normal distribution model for range measurement errors in the considered building. This prior knowledge of a probability distribution could be unknown or inaccurate when deployment environment changes, and therefore PPB, which is independent of this prior knowledge, could serve as a general lower bound estimator for location determination research.