However, the speed of the mobile station is assumed to be very low and the relative movement between the base station and the mobile station is not considered. [18] utilizes a constrained nonlinear optimization approach, when range measurements are available from three base stations only. Bounds on the non-line-of-sight (NLOS) error and the relationship kinase inhibitor Tipifarnib between the true ranges are extracted from the geometry of the cell layout and the measured range circles to serve as constraints. [19] introduces two hybrid TOA/AOA techniques, Enhanced Time of Arrivals (E-TOA) and Enhanced Angle of Arrival (E-AOA), in order to optimize the location positioning estimations. [20] proposes a residual test (RT) that can simultaneously determine the number of LOS base stations and identify them such that localization can proceed with only those LOS base stations.
Hybrid location Inhibitors,Modulators,Libraries methods by combining time and angle measurements can reduce the number of receiving base stations Inhibitors,Modulators,Libraries and improve the coverage of location-based service simultaneously. Comprehensive surveys of design challenges and recently proposed hybrid positioning algorithms for wireless networks can be found in [7,21�C24].Due to the error caused by the location estimation algorithm (the estimation error) and the error intrinsic to the problem (noisy distance measurements), location adjustment algorithms are needed in order to improve the estimation accuracy. There are several refinement schemes Inhibitors,Modulators,Libraries that have been proposed in the literature. Since the particle filter looses diversity in the samples, Inhibitors,Modulators,Libraries a sequential Monte Carlo framework [25] can be used to generate new samples and provide improved estimation accuracy (e.
g., random walk Monte Carlo methods, Metropolis-Hastings (M-H) algorithm [26]). The Batimastat basic idea is to simulate an ergodic Markov chain such that the new samples are asymptotically distributed based on the target probability distribution. Thus, applying the Markov chain Monte Carlo (MCMC) method on each estimated sensor right after the location esti
Power grids involve the generation, transmission and distribution of electric power. Figure 1 shows an example of the configuration of a power grid. The electrical distribution system delivers electric power through feeders and pole transformers from distribution substations to end users such as houses, office buildings, and factories.
Power quality is any power problem manifested in voltage, current, or frequency deviations, that results selleck chemicals in failure or malfunctioning of the customer equipment [1]. It is one of the most important issues in electrical distribution systems.Figure 1.An example of a power grid.Korea Electric Power Corporation (KEPCO) [2] in Korea has monitored basic electrical quantities such as voltage and current from major pole transformers using their temperature.