CAJ | 학술논문

移动无线传感器网络的节点定位算法中，基于RSSI（Received Signal Strength Indication ）的蒙特卡罗定位算法结合了RSSI定位算法和蒙特卡罗定位算法的优点，定位精度较好，但计算量较大，节点能量消耗严重。针对上述不足，提出一种基于RSSI的改进蒙特卡罗定位算法，采用插值法对节点运动状态进行预测，同时采用交叉操作加快有效粒子的选择，提高预测和滤波的准确性。仿真实验结果表明，该算法与传统算法相比加快了收敛速度，减少了计算开销，同时提高了定位精度。
이동무선전감기망락적절점정위산법중，기우RSSI（Received Signal Strength Indication ）적몽특잡라정위산법결합료RSSI정위산법화몽특잡라정위산법적우점，정위정도교호，단계산량교대，절점능량소모엄중。침대상술불족，제출일충기우RSSI적개진몽특잡라정위산법，채용삽치법대절점운동상태진행예측，동시채용교차조작가쾌유효입자적선택，제고예측화려파적준학성。방진실험결과표명，해산법여전통산법상비가쾌료수렴속도，감소료계산개소，동시제고료정위정도。
Among the localisation algorithms for wireless sensor networks nodes , the received signal strength indication ( RSSI )-based Monte Carlo localisation ( MCL) algorithm combines the advantages of RSSI localisation algorithm and classical MCL algorithm , though having good localisation accuracy , its computational cost is big , and its energy consume is serious .To overcome these shortages , an improved Monte Carlo localisation algorithm based on RSSI is proposed .The algorithm uses interpolation to estimate the state of node motion and uses cross operation to accelerate the validated particle's selection and increase the accuracy of prediction and filtration .Simulation experimental results show that the algorithm outperforms the traditional algorithm in convergence speed , computational cost and localisation accuracy .