基于粒子群与DBSCAN的SSOA定位算法

SSOA Location Algorithm Based on Particle Swarm Optimization and DBSCAN

定位技术应用广泛,利用到达信号强度(SSOA)定位有着成本低,能量消耗少的特点,为此提出一种SSOA定位算法。该方法的目的是利用电波到达信号强度数据和GPS数据,计算出较精准的信号源位置。假设目标位置,通过分析电波传播过程,构建代价函数,使用粒子群算法进行迭代,求出代价最小的最优解。为了解决增根与不收敛等问题,使用基于密度的聚类算法(DBSCAN)进行聚类。实测表明,该算法有较高的定位精度并且收敛。

Localization technology is widely used,and the using of Signal Strength of Arrival (SSOA) localization has the characteristics of low cost and low energy consumption.To solve this problem,proposes a SSOA localization algorithm.The aim of this method is to use the arrival signal strength data and GPS data to calculate the accurate signal source position.Assumes a target position,and the cost function is constructed by analyzing the propagation process of the radio wave.The particle swarm optimization algorithm is used to iterate and find the optimal solution with the least cost.In order to solve the problem of extraneous root and not converge,uses Density-Based Spatial Clustering of Applications with Noise (DBSCAN) algorithm to cluster.The experimental show that the algorithm has high accuracy and convergence.