  Estimation of a deterministic quantity observed in non-Gaussian additive
noise is explored via order statistics approach. More specifically, we study
the estimation problem when measurement noises either have positive supports or
follow a mixture of normal and uniform distribution. This is a problem of great
interest specially in cellular positioning systems where the wireless signal is
prone to multiple sources of noises which generally have a positive support.
Multiple noise distributions are investigated and, if possible, minimum
variance unbiased (MVU) estimators are derived. In case of uniform, exponential
and Rayleigh noise distributions, unbiased estimators without any knowledge of
the hyper parameters of the noise distributions are also given. For each noise
distribution, the proposed order statistic-based estimator's performance, in
terms of mean squared error, is compared to the best linear unbiased estimator
(BLUE), as a function of sample size, in a simulation study.
