  Ultrawideband (UWB) technology has attracted a lot of attention for indoor
and outdoor positioning systems due to its high accuracy and robustness in
non-line-of-sight (NLOS) environments. However, UWB signals are affected by
multipath propagation which causes errors in localization. To overcome this
problem, researchers have proposed various techniques for NLOS identification
and mitigation. One of the approaches is statistical LOS/NLOS classification,
which uses statistical parameters of the received signal to distinguish between
LOS and NLOS channels. In this paper, we formulated several techniques which
can be used for effectively classifying a Line of Sight (LOS) channel from a
Non-Line of Sight (NLOS) channel. Various parameters obtained from Channel
Impulse Response (CIR) like Skewness, Kurtosis, Root Mean Squared Delay Spread
(RDS), Mean Excess Delay (MED), Energy, Energy Ratio, and Mean of Covariance
Matrix are used for channel classification. In addition to this, the Joint
Probability Density Functions (PDFs) of various parameters are used to improve
the accuracy of UWB LOS/NLOS channel classification. Two different
criteria-Likelihood Ratio and Hypothesis Tests are used for the identification
of the channel.
