【摘要】：為解決室內(nèi)定位系統(tǒng)中建立位置指紋數(shù)據(jù)庫(kù)工作量龐大的問(wèn)題,提出了一種融合信號(hào)衰減因素的普通克里金空間插值建庫(kù)算法。該方法首先采用高斯濾波對(duì)有限預(yù)選參考點(diǎn)的信號(hào)強(qiáng)度采樣數(shù)據(jù)進(jìn)行預(yù)處理,并基于球狀模型由參考點(diǎn)預(yù)處理數(shù)據(jù)擬合出空間變異函數(shù);然后采用普通克里金插值法對(duì)其他位置的信號(hào)強(qiáng)度進(jìn)行估值并生成相應(yīng)的位置指紋;最后由有限實(shí)測(cè)數(shù)據(jù)生成大容量高分辨位置指紋數(shù)據(jù)庫(kù),并通過(guò)KNN_Filter算法和對(duì)數(shù)權(quán)重算法完成定位仿真,驗(yàn)證了該建庫(kù)方法的有效性。仿真實(shí)驗(yàn)結(jié)果表明,該算法在保證定位精度的前提下,相比傳統(tǒng)建庫(kù)方法可降低40%左右的工作量,提高了室內(nèi)位置指紋定位方法的工作效率。
[Abstract]:In order to solve the problem of the huge workload of establishing the location fingerprint database in the indoor positioning system, a common Kriging spatial interpolation database building algorithm is proposed, which combines the attenuation factors of the signal. Firstly, Gao Si filter is used to preprocess the signal intensity sampling data of the limited pre-selected reference points, and the spatial variogram is fitted from the pre-processed data of the reference points based on the spherical model. Then the common Kriging interpolation method is used to estimate the signal intensity of other positions and generate the corresponding location fingerprint. Finally, the large capacity high-resolution location fingerprint database is generated from the limited measured data. KNN_Filter algorithm and logarithmic weight algorithm are used to complete the localization simulation, and the validity of the method is verified. The simulation results show that the algorithm can reduce the workload by about 40% compared with the traditional database building method and improve the efficiency of the indoor location fingerprint location method on the premise of ensuring the location accuracy.
【作者單位】： 遼寧工業(yè)大學(xué)電子與信息工程學(xué)院;
【基金】：遼寧省科技廳博士啟動(dòng)基金資助項(xiàng)目(20131045) 遼寧省教育廳資助項(xiàng)目(L2012218)
【分類(lèi)號(hào)】：TN911.7

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