基于證據(jù)理論的群指紋融合室內(nèi)定位方法
發(fā)布時(shí)間:2019-07-15 16:21
【摘要】:室內(nèi)定位的主要挑戰(zhàn)是室內(nèi)的多徑傳播及非平穩(wěn)信道環(huán)境,傳統(tǒng)基于信號強(qiáng)度指紋的單指紋室內(nèi)定位方法由于受環(huán)境變化影響較大,穩(wěn)健性較差且精度較低。針對此問題,提出一種基于D-S證據(jù)理論的群指紋融合高精度室內(nèi)定位方法。在建庫階段,利用室內(nèi)陣列信號接收模型,首先通過計(jì)算陣列接收信號的不同統(tǒng)計(jì)特性構(gòu)建包括信號強(qiáng)度、協(xié)方差矩陣、信號子空間及四階累積量組成的群指紋庫,再對群指紋進(jìn)行神經(jīng)網(wǎng)絡(luò)訓(xùn)練獲取針對每種指紋的神經(jīng)網(wǎng)絡(luò)分類器;在實(shí)測階段,把實(shí)測數(shù)據(jù)的上述4種變換輸入到訓(xùn)練好的神經(jīng)網(wǎng)絡(luò)分類器中,最后利用D-S證據(jù)理論對神經(jīng)網(wǎng)絡(luò)分類器的分類結(jié)果進(jìn)行融合,給出最終的定位結(jié)果。仿真結(jié)果證明了算法的有效性及可行性。該算法可充分發(fā)揮指紋信息的集群效應(yīng),對噪聲、多徑傳播等具有較好的穩(wěn)健性,是一種高精度的室內(nèi)定位新方法。
[Abstract]:The main challenge of indoor positioning is indoor multi-path propagation and non-stationary channel environment. The traditional single fingerprint indoor location method based on signal strength fingerprint is greatly affected by environmental changes, poor robustness and low accuracy. In order to solve this problem, a group fingerprint fusion high precision indoor location method based on D 鈮,
本文編號:2514761
[Abstract]:The main challenge of indoor positioning is indoor multi-path propagation and non-stationary channel environment. The traditional single fingerprint indoor location method based on signal strength fingerprint is greatly affected by environmental changes, poor robustness and low accuracy. In order to solve this problem, a group fingerprint fusion high precision indoor location method based on D 鈮,
本文編號:2514761
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