發(fā)布時(shí)間：2018-03-19 08:30

  本文選題：無(wú)線傳感器網(wǎng)絡(luò)　切入點(diǎn)：RSSI測(cè)距　出處：《計(jì)算機(jī)工程與設(shè)計(jì)》2017年10期 　論文類型：期刊論文

【摘要】：針對(duì)WSN定位算法在測(cè)距和定位過(guò)程中存在較大誤差的問(wèn)題,提出基于Kalman濾波的加權(quán)補(bǔ)償定位算法。利用Kalman濾波模型對(duì)RSSI信號(hào)值進(jìn)行平滑處理,使接收到的信號(hào)強(qiáng)度值更趨近于真實(shí)值;選取相鄰錨節(jié)點(diǎn)與待測(cè)節(jié)點(diǎn)之間距離倒數(shù)的和作為權(quán)值因子,并用它們之間的距離比對(duì)權(quán)值因子進(jìn)行優(yōu)化,采用二次加權(quán)質(zhì)心算法計(jì)算待測(cè)節(jié)點(diǎn)的位置;再定位周邊的錨節(jié)點(diǎn)得出誤差均值,對(duì)待測(cè)節(jié)點(diǎn)的位置加以補(bǔ)償。仿真結(jié)果表明,所提算法的定位精度比基于RSSI的加權(quán)質(zhì)心算法提高了5%-6%。
[Abstract]:In order to solve the problem of large error in WSN location algorithm, a weighted compensation localization algorithm based on Kalman filter is proposed. The RSSI signal value is smoothed by Kalman filter model. The received signal intensity value is closer to the real value, the reciprocal sum of the distance between adjacent anchor node and the node to be tested is selected as the weight factor, and the weight factor is optimized by the distance ratio between them. The quadratic weighted centroid algorithm is used to calculate the position of the node to be tested, the error mean value is obtained by locating the surrounding anchor node, and the position of the measured node is compensated. The simulation results show that, Compared with the weighted centroid algorithm based on RSSI, the accuracy of the proposed algorithm is improved by 5-6.
【作者單位】： 沈陽(yáng)航空航天大學(xué)計(jì)算機(jī)學(xué)院;
【基金】：航空科學(xué)基金項(xiàng)目(2014ZC54012) 遼寧省自然科學(xué)基金項(xiàng)目(2013024002) 遼寧省教育廳基金項(xiàng)目(L2013063)
【分類號(hào)】：TN929.5;TP212.9
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本文編號(hào)：1633466