2018/10/18 by Luca Carlino, Di Jin, Carlino, Luca +5
Computer Science · Engineering · #Energy Efficient Wireless Sensor Networks #FOS: Electrical engineering #Indoor and Outdoor Localization Technologies #Signal Processing (eess.SP) #Underwater Vehicles and Communication Systems #eess.SP #electronic engineering #information engineering
paper · pdf · doi:10.48550/arxiv.1810.08098
16 pages, 12 figures
openalex publication_date 2018/10/18 · arxiv created 2018/12/11 · arxiv updated 2018/12/12 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
The accurate and low-cost localization of sensors using a wireless sensor network is critically required in a wide range of today's applications. We propose a novel, robust maximum likelihood-type method for distributed cooperative received signal strength-based localization in wireless sensor networks. To cope with mixed LoS/NLoS conditions, we model the measurements using a two-component Gaussian mixture model. The relevant channel parameters, including the reference path loss, the path loss exponent and the variance of the measurement error, for both LoS and NLoS conditions, are assumed to be unknown deterministic parameters and are adaptively estimated. Unlike existing algorithms, the proposed method naturally takes into account the (possible) asymmetry of links between nodes. The proposed approach has a communication overhead upper-bounded by a quadratic function of the number of nodes and computational complexity scaling linearly with it. The convergence of the proposed method is guaranteed for compatible network graphs and compatibility can be tested a priori by restating the problem as a graph coloring problem. Simulation results, carried out in comparison to a centralized benchmark algorithm, demonstrate the good overall performance and high robustness in mixed LoS/NLoS environments.