The positioning technology based on receive signal strength (RSS) fingerprints has become one of the hottest research spots with its advantages of simple deployment, low cost, and single parameter. However, in the limited space, the multipath and shadowing, result in poor separability of the fingerprint data, and low accuracy of target localization. In this paper, a novel RSS fingerprints positioning algorithm that is based on fuzzy kernel clustering SVM is proposed to combat the multipath and shadowing effects. The first step of the proposed positioning algorithm is to use kernel function to map the traditional fingerprints sample data to high-dimensional feature space to generate fuzzy classes. The second step is to generate binary-class SVM of fuzzy class based on the relationship between classes and internal discrete information of each class. After that, we can use the binary fuzzy class SVM to dichotomize the classified fingerprints in the first step, and combine these dichotomous SVMs into a handstand classification binary tree. And thus, the proposed positioning algorithm achieves quick and accurate positioning. Experimental results show that the positioning accuracy and locating stability of proposed positioning algorithm are improved by 38.73% and 59.26%, respectively, compared with the traditional RSS fingerprints algorithm.
Telecommunication Systems - In a wireless sensor network (WSN) where positioning information is not assumed or is partially available, efficient data access is a very challenging issue especially... 相似文献
Thermoelectric (TE) materials, which can directly convert heat to electrical energy, possess wide application potential for power generation from waste heat. As TE devices in vehicle exhaust power generation systems work in the long term in a service environment with coupled thermal–mechanical–electrical conditions, the reliability of their mechanical strength and conversion efficiency is an important issue for their commercial application. Based on semiconductor TE devices wih multiple p–n couples and the working environment of a vehicle exhaust power generation system, the service conditions of the TE devices are simulated by using the finite-element method. The working temperature on the hot side is set according to experimental measurements, and two cooling methods, i.e., an independent and shared water tank, are adopted on the cold side. The conversion efficiency and thermal stresses of the TE devices are calculated and discussed. Numerical results are obtained, and the mechanism of the influence on the conversion efficiency and mechanical properties of the TE materials is revealed, aiming to provide theoretical guidance for optimization of the design and commercial application of vehicle TE devices. 相似文献