Sensor Localization from WLS Optimization with Closed-form Gradient and Hessian

— A non-parametric, low-complexity algorithm for accurate and simultaneous localization of multiple sensors from scarce and imperfect ranging information is proposed. The technique is based on multidimensional scaling (MDS) and weighted least-squares (WLS) optimization. Closed-form expressions of the gradient and Hessian of the weighted quadratic objective used to solve the WLS problem are also provided. The performance of the proposed technique is studied through extensive computer simulations, with the intra-node distances randomly generated in accordance to a statistical model constructed from the results of a measurement campaign conducted with a pair of impulsive ultrawideband (UWB) radios in an indoor scenario. The simulation results reveal that the proposed algorithm, despite its low complexity, is nearly as accurate as the known alternative of best performance, which is based on semi-definite programming and demands significantly more computational power.

• Type: Conference
• Year: 2006
• Where: GLOBECOM
• Authors: Giuseppe Destino, Giuseppe Thadeu Freitas de Abreu
• Keywords: GLOBECOM 2006, Imperfect Ranging Information, Low-complexity Algorithm, Telecommunications , Weighted Quadratic Objective