一种局部模式的RGB差值序列交叉区域取样节点定位算法

A Local Cross Region of RGB Difference Sequence Sampling WSN Localization Algorithm

摘要:

鉴于当前无线传感器网络(WSN)移动节点定位技术中存在的实时性差和定位不准确的问题,设计了一种交叠区域采样模式的WSN移动节点定位算法OASM_MNL(overlapping area sampling mode of mobile node localization);该算法通过获取的信号在能够直接和移动节点通信的信标节点的信号交叠区域里面进行局部采样；通过距离比例因子对平均跳距进行权值化,优化了CDL中跳距的计算公式；通过RGB差值序列对样本点滤波,在此基础上把差值序列绝对值作为加权标准,计算出移动节点的坐标;仿真结果表明,与E-CDL、MCL等常见的移动节点定位算法相比,新算法定位误差降低幅度超过33%,定位效果良好。

Abstract:

Aiming at the problem that the real time difference and location of the mobile node localization technology in wireless sensor networks (WSN), this paper proposes a new method of WSN mobile node localization algorithm based on overlapping area sampling mode of mobile node localization. In this algorithm, the signal is obtained by using the signal in the signal intersection area of the beacon node, and the average hop distance is calculated by using the distance scale factor. The calculation formula of the jump distance in CDL is optimized; The RGB difference sequence is used to filter the sample point, and the absolute value of the difference sequence is used as the weighted standard to calculate the coordinates of the mobile node. Simulation results show that compared with common mobile node localization algorithm such as E-CDL and MCL, the positioning error of the new algorithm is reduced by more than 33%, its positioning performance is good.