CAJ | 학술논문

为了提高在一个移动信标节点下的无线传感器网络节点定位的精度，提出了一种稀疏化的无线传感器网络节点定位算法。该算法通过网格化感知区域把节点定位问题转化为稀疏信号重构问题，并提出了Schmidt正交单位化的预处理方法，对观测矩阵进行预处理，使其有效地满足了约束等距性条件。并针对稀疏定位模型中得到的稀疏信号是近似稀疏信号的问题，采用质心算法来优化算法的定位精度。实验结果表明，相比于MAP类算法，稀疏化的无线传感器网络节点定位算法的定位精度更优，同时所需要的信标节点的广播次数也更少。
위료제고재일개이동신표절점하적무선전감기망락절점정위적정도，제출료일충희소화적무선전감기망락절점정위산법。해산법통과망격화감지구역파절점정위문제전화위희소신호중구문제，병제출료Schmidt정교단위화적예처리방법，대관측구진진행예처리，사기유효지만족료약속등거성조건。병침대희소정위모형중득도적희소신호시근사희소신호적문제，채용질심산법래우화산법적정위정도。실험결과표명，상비우MAP류산법，희소화적무선전감기망락절점정위산법적정위정도경우，동시소수요적신표절점적엄파차수야경소。
To improve the localization accuracy of a node in the wireless sensor network with a mobile beacon node, a sparse localization algorithm using Schmidt orthonormalization ( SLSO) was proposed. With the SLSO, the node localization problem was converted to a reconstruction problem of the sparse signal by gridding the sensing area, and a new observation matrix which is able to effectively satisfy the restricted isometry property ( RIP ) was obtained by Schmidt orthonormalization. To solve the problem of the sparse signal being approximately sparse in the model, a centroid algorithm was adopted to improve the localization accuracy. The experiment results show that, compared with MAP algorithms, SLSO has better localization accuracy, and requires less broadcasting times.