LOS/NLOS channel identification for improved localization in wireless ultra-wideband networks

Abstract

The paper presents techniques for line-of-sight (LOS) and non-line-of-sight (NLOS) link identification in ultra-wideband wireless networks for the purpose of improving mobile positioning reliability in indoor and outdoor environments. Statistical hypothesis testing is applied by using specific parameters of the channel impulse response (CIR) related to skewness, kurtosis, root mean square delay and mean excess delay. Analytical multi-variate lognormal statistical models are developed for the joint probability densities of the CIR parameters which are found to have distinct features under LOS and NLOS conditions, and this is exploited in determining the nature of the propagation channels. Simulation results demonstrate that link identification with accuracy rates exceeding 95% are achievable for most types of environments, particularly when using combined amplitude and delay parameters. Reliable link identification is then integrated with time-of-arrival positioning, first using a low-complexity iterative maximum likelihood algorithm for localizing mobile nodes with LOS/NLOS links to a network of fixed access nodes. Numerical results show that reliable identification can greatly enhance mobile positioning accuracy, bringing the localization error to within 2 m with 90% probability. In the case of NLOS-dominated dynamically changing environments, another approach is developed based on the use of the unscented Kalman filter with integrated least-squares bias estimation and mitigation, and it is shown that accurate mobile tracking can be achieved, with performance approaching that of NLOS-free operating conditions.