Localization of Objects Using Cross-Correlation of Shadow Fading Noise and Copulas

While fading, in general, is detrimental to accurately localizing a target, fading correlation between adjacent receivers may be exploited to improve localization accuracy. Therefore, this paper presents a novel wireless localization scheme that employs a combination of cross-correlation between shadow fading noise and copula technique to recursively estimate the location of a transmitter. A stochastic filter that models multipath fading as an Ornstein-Uhlenbeck process followed by a Generalized Auto Regressive Conditional Heteroskedasticity (GARCH) filtering is proposed to extract shadow fading residuals from measured RSSI values. Subsequently, Student-t Copula function is used to create the log likelihood function, which acts as the cost function for localization, by combining spatial shadow fading correlation arising among adjacent receivers due to pedestrian traffic in the area. Maximum Likelihood Estimate (MLE) is used for position estimation as it inherits the statistical consistency and asymptotic normality. The performance of our proposed localization method is validated over simulations and hardware experiments.