摘要
在非视距传输环境下,粗估计阶段接收信号强度(RSS)的特征维度较低会导致定位性能差。针对该问题,提出一种基于多维标度(MDS)算法改进的时间反转二阶段室内定位方法。对RSS和信道频率响应(CFR)分别进行特定参考点采集,采用线性时域滤波缩小信道状态信息的数据动态范围,利用RSS和MDS算法进行位置粗估计,确定待测点所在范围,构建指纹库。使用预处理过后的CFR与子指纹库中的各参考点处CFR计算组合时间反转共振能量(CTRRS)值,并搜索CTRRS最大值的参考点,实现精确定位。实验结果表明,与时间反转室内定位方法相比,改进方法的定位时间提升了56.5%。
In the non-sight distance transmission environment,the lower characteristic dimension of the Received Signal Strength(RSS) in the coarse estimation phase results in poor positioning performance.To address this problem,an improved time reversal two-stage indoor positioning method based on Multi-Dimensional Scale(MDS) algorithm is proposed.Specific reference point of the RSS and the Channel Frequency Response(CFR) are collected.Linear time domain filtering is adopted to narrow the dynamic data range of the Channel State Information(CSI).RSS and MDS algorithms are used for coarse location estimation to determine the location range of to-be-measured points,and the fingerprint database is constructed.The Combined Time Reversed Resonating Strength(CTRRS) value is calculated by using the pre-processed CFR and the CFR at each reference point in the fingerprint sub-library,and the reference point of the CTRRS maximum value is searched for precise positioning.Experimental results show that compared with the time reversal indoor positioning method,the positioning time of the improved method can be increased by 56.5%.
引文
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