动态knn:一种基于到达角的无线局域网定位新方法

M. Roshanaei, Mina Maleki
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引用次数: 50

摘要

位置估计由于其广泛的应用而成为近年来研究的热点之一。K近邻(KNN)是一种基本的确定性定位算法,广泛应用于指纹识别中。通过采用合适的选择算法,可以大大提高KNN的性能。本文提出了一种将到达角(AOA)和KNN作为混合方法的动态KNN (D-KNN)算法。该方法与常数K的KNN算法相比,动态选择最近邻的最佳数量。它利用自适应天线系统,通过获取的多个AOA的交集来确定用户的位置区域。可以选择位于确定区域内的K个最佳邻居用于KNN。分析和仿真结果表明,D-KNN在不同条件下的综合性能最佳。
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Dynamic-KNN: A novel locating method in WLAN based on Angle of Arrival
Location estimation as one of the most popular research areas has been recently attended because of wide range of its applications. K Nearest Neighbor (KNN) is a basic deterministic algorithm for locating which is widely used in fingerprinting approach. The performance of the KNN can be improved extensively by employing appropriate selection algorithm. In this paper, a novel algorithm called Dynamic KNN (D-KNN) which uses Angle of Arrival (AOA) and KNN as a hybrid method is proposed. This method comparing with KNN algorithm with constant K, selects the best number of nearest neighbors dynamically. It utilizes the adaptive antenna system to determine the user locative area by intersection of several obtained AOA. The best K neighbors which are located in the determined area can be selected to employ in the KNN. Analysis and simulation results are reported the best overall performance of D-KNN in different conditions.
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