本文選題：Wi-Fi網(wǎng)絡(luò)　切入點(diǎn)：室內(nèi)定位　出處：《計(jì)算機(jī)應(yīng)用》2017年06期

【摘要】：Wi-Fi網(wǎng)絡(luò)中常規(guī)的基于指紋匹配室內(nèi)定位算法面臨信號時變現(xiàn)象或人為干擾的影響,導(dǎo)致定位精度不高。為此,提出基于動態(tài)時間規(guī)整(DTW)距離相似性指紋匹配的Wi-Fi網(wǎng)絡(luò)室內(nèi)定位算法。首先,該算法將定位區(qū)域的Wi-Fi信號特征按照采樣的先后順序轉(zhuǎn)化為時間序列類型指紋,通過計(jì)算Wi-Fi信號指紋動態(tài)時間規(guī)整距離的大小來獲取定位點(diǎn)與樣本點(diǎn)的相似性;然后,根據(jù)采樣區(qū)域結(jié)構(gòu)特征,將Wi-Fi信號指紋采集問題劃分為三類基本的動態(tài)路徑采樣方式;最后,結(jié)合多種動態(tài)路徑采樣方式增加指紋特征信息的準(zhǔn)確性和完整性,從而提高指紋匹配的準(zhǔn)確性和定位精度。大量實(shí)驗(yàn)結(jié)果表明,較瞬時指紋匹配定位算法,所提算法誤差范圍在3m以內(nèi)定位的累積錯誤率:路徑區(qū)域勻速運(yùn)動提高了10%,變速運(yùn)動提高了13%;開放區(qū)域交叉曲線運(yùn)動提高了9%,S型曲線運(yùn)動提高了3%。所提算法在實(shí)際室內(nèi)定位應(yīng)用中能有效提高指紋匹配的準(zhǔn)確性和定位精度。
[Abstract]:The conventional fingerprint matching indoor location algorithm in Wi-Fi network faces the influence of signal time-varying phenomenon or artificial interference, which leads to the low accuracy of location.Therefore, an indoor location algorithm for Wi-Fi network based on dynamic time warping (DTW) distance similarity fingerprint matching is proposed.Firstly, the Wi-Fi signal feature of the location region is transformed into time series fingerprint according to the sequence of sampling, and the similarity between the location point and the sample point is obtained by calculating the dynamic time warping distance between the Wi-Fi signal fingerprint and the sample point.According to the structure of the sampling region, the fingerprint acquisition problem of Wi-Fi signal is divided into three basic dynamic path sampling methods. Finally, the accuracy and integrity of fingerprint feature information are increased by combining various dynamic path sampling methods.In order to improve the accuracy of fingerprint matching and positioning accuracy.A large number of experimental results show that, compared with the instantaneous fingerprint matching algorithm,The error range of the proposed algorithm is less than 3 m. The cumulative error rate of the proposed algorithm is as follows: the uniform motion of the path region is increased by 10 percent, the movement of the variable speed increases by 13 percent, and the movement of the cross curve in the open area increases by 9 percent and the movement of the S-shaped curve increases by 3 percent.The proposed algorithm can effectively improve the accuracy and accuracy of fingerprint matching in practical indoor localization applications.
【作者單位】： 東北大學(xué)計(jì)算機(jī)科學(xué)與工程學(xué)院;東軟公司軟件架構(gòu)新技術(shù)國家重點(diǎn)實(shí)驗(yàn)室;
【基金】：國家863計(jì)劃項(xiàng)目(2015AA016005) 國家自然科學(xué)基金資助項(xiàng)目(61402096,61173153,61300196)~~
【分類號】：TN92

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本文編號：1710615