基于典型相关回归的多跳非测距定位方法

Multihop Range-Free Localization Algorithm Based on Canonical Correlation Regression

多跳非测距定位方法是一种有效的、简单的节点定位方法,然而其一般仅适用于各向同性,节点密集网络。针对在各向异性网络中,多跳非测距定位方法定位性能低的问题,提出了基于典型相关回归非测距定位方法。该方法通过典型相关回归获得节点间跳数与欧氏距离精确的映射模型,并利用该映射获得未知节点到已知节点估计距离。仿真实验表明,该方法与现有算法相比具有更高的定位精度和定位稳定性。

Multihop range-free localization method is an effective and simple method to determine node location.However,it is generally suitable for isotropic and the node intensive network.Since the low performance of multihop range-free localization method in anisotropic networks,an improved scheme is proposed based on canonical correlation.This method obtains a high precision mapping model by canonical correlation regression between nodes hops and Euclidean distance,then obtains the estimated distance between unknown node and known node using the measurement of hop-count.It also solves the problem of multi-hop range free localization method,which the performance is low in anisotropic network.Experimental simulation results show that this method achieves higher accuracy and stability than other location algorithms.