在无线传感器网络(WSN ) 的活动终端地点的主导的错误来源是 non-line-of-sight (NLOS ) 繁殖错误。在建议减轻 NLOS 繁殖错误的影响的算法之中,剩余测试(RT ) 是有效的,然而与高计算的复杂性(CC ) 。LOS 范围大小识别了的记住识别的范围大小(RM ) 记住的视觉(LOS ) 的光的一个改进算法剩余测试(MLSI-RT ) 在这份报纸被介绍给地址这个问题。MLSI-RT 基于假设当所有 RM 从 LOS 繁殖时,当为 NLOS 盒子它是非中央的时,规范的剩余跟随中央 Chi 平方分发。这研究能在超过 90% 减少 CC。
The dominant error source of mobile terminal location in wireless sensor networks (WSNs) is the non-line-of-sight (NLOS) propagation error. Among the algorithms proposed to mitigate the influence of NLOS propagation error, residual test (RT) is an efficient one, however with high computational complexity (CC). An improved algorithm that memorizes the light of sight (LOS) range measurements (RMs) identified memorize LOS range measurements identified residual test (MLSI-RT) is presented in this paper to address this problem. The MLSI-RT is based on the assumption that when all RMs are from LOS propagations, the normalized residual follows the central Chi-Square distribution while for NLOS cases it is non-central. This study can reduce the CC by more than 90%.