CAJ | 학술논문

蒙特卡罗定位算法在无线传感器网络移动节点定位中具有重要的作用．为了提高定位精度，提出了基于序列相关值的蒙特卡罗优化算法 SCMCL．以接收的 RSSI 信号值对移动节点初定位，并将其作为新的采样中心，SCM-CL 可以优化蒙特卡罗系列算法的采样区域，同时将移动节点收到的锚节点信号值存储为目标序列，通过比较样本序列和目标序列间的相关值来过滤样本点，并将相关值作为加权标准来计算移动节点的坐标．仿真验证，SCMCL 算法在相同的锚节点密度和最大速度下和同类算法相比，定位误差均减少了10％左右．
몽특잡라정위산법재무선전감기망락이동절점정위중구유중요적작용．위료제고정위정도，제출료기우서렬상관치적몽특잡라우화산법 SCMCL．이접수적 RSSI 신호치대이동절점초정위，병장기작위신적채양중심，SCM-CL 가이우화몽특잡라계렬산법적채양구역，동시장이동절점수도적묘절점신호치존저위목표서렬，통과비교양본서렬화목표서렬간적상관치래과려양본점，병장상관치작위가권표준래계산이동절점적좌표．방진험증，SCMCL 산법재상동적묘절점밀도화최대속도하화동류산법상비，정위오차균감소료10％좌우．
Monte Carlo Localization(MCL)has a decisive role for the mobile nodes’localization in Wireless Sensor Net-works(WSN).In order to improve the positioning accuracy,an improved algorithm called Sequence Correlation Optimized Monte Carlo Localization(SCMCL)is proposed.Adopting the mobile node’s location based on the received signal strength indicator (RSSI)as the new sampling center,SCMCL can optimize the sampling area of MCL and etc.The signal values are stored as a target sequence,and by comparing the correlation values between samples’sequences and the target sequence,samples can be filtered out. Also the correlation values are used as the weighted standards to calculate coordinates of the mobile nodes.Extensive simulation re-sults confirm that the new localization approach outperforms MCL and etc.The SCMCL algorithm reduces the localization error by about 10% under the same density of beacon nodes and the maximum speed of mobile nodes.