基于DBSCAN-GRNN-LSSVR算法的WLAN异构终端定位方法

Subjects: Computer Science >> Integration Theory of Computer Science submitted time 2018-05-02 Cooperative journals: 《计算机应用研究》

张勇 范恒 王昱洁

Abstract： Aiming at the excessive location error caused by heterogeneous terminal (fingerprint database terminal and test terminal) in WLAN indoor localization system, a solution based on DBSCAN-GRNN-LSSVR algorithm is proposed. In this paper, the least square support vector regression (LSSVR) algorithm is employed to build the mapping relationship model between the received signal strength (RSS) of fingerprint database terminal and physical coordinate locations. The scatter plot is obtained through listing the RSS values collected by the fingerprint database terminal and the test terminal at the calibration point. The boundary points and noise points are eliminated by density-based spatial clustering. Generalized regression neural network (GRNN) is used to construct the heterogeneous terminal mapping function of the RSS. The LSSVR model is used to determine the location of the test point. Proved by experiment, compared with LSSVR algorithm, using the proposed DBSCAN-GRNN-LSSVR algorithm to calibrate the heterogeneous terminal, test terminal positioning accuracy increased by 18-40%, which effectively solves the problem of excessive localization deviation caused by heterogeneous terminals.

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