能量分簇傳感器網(wǎng)絡(luò)距離誤差校正MDS-MAP定位算法
doi: 10.11999/JEIT161237
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2.
(吉林大學(xué)通信工程學(xué)院 長春 130012) ②(東北電力大學(xué)信息工程學(xué)院 吉林 132012) ③(長春理工大學(xué)電子信息工程學(xué)院 長春 130022)
基金項(xiàng)目:
國家自然科學(xué)基金(61371092, 61540022)
Modified MDS-MAP Localization Algorithm with Distance Error Correction in Energy Clustering Wireless Sensor Networks
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2.
(School of Communication Engineering, Jilin University, Changchun 130012, China)
Funds:
The National Natural Science Foundation of China (61371092, 61540022)
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摘要: 經(jīng)典MDS-MAP算法在無線傳感器網(wǎng)絡(luò)定位中存在誤差較大及計(jì)算量隨網(wǎng)絡(luò)規(guī)模增大而急劇增加的缺點(diǎn)。該文設(shè)計(jì)了基于自身和鄰居節(jié)點(diǎn)剩余能量大小的成簇方法，形成的簇具有適當(dāng)節(jié)點(diǎn)連接度和簇大小，降低了下一步定位算法的計(jì)算量和誤差。然后對于僅有連通信息的簇內(nèi)節(jié)點(diǎn)，利用時(shí)間差測距方法獲得簇首與其他單跳節(jié)點(diǎn)間距離。提出多跳節(jié)點(diǎn)間距離誤差校正算法，利用相鄰節(jié)點(diǎn)的幾何關(guān)系及節(jié)點(diǎn)連接度信息，獲得簇內(nèi)多跳間隔節(jié)點(diǎn)距離。采用多維標(biāo)度技術(shù)計(jì)算各簇內(nèi)節(jié)點(diǎn)相對坐標(biāo)，融合簇間坐標(biāo)并通過錨節(jié)點(diǎn)轉(zhuǎn)換為絕對坐標(biāo)，最終實(shí)現(xiàn)節(jié)點(diǎn)的定位。所提方法通過能量分簇及多跳間隔節(jié)點(diǎn)加權(quán)幾何距離校正算法，相對于經(jīng)典多維標(biāo)度算法定位提供更準(zhǔn)確的節(jié)點(diǎn)間距離信息，能夠在進(jìn)一步提高定位精度的基礎(chǔ)上降低無線傳感器網(wǎng)絡(luò)定位功耗。
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關(guān)鍵詞:
- 無線傳感器網(wǎng)絡(luò) /
- 定位 /
- 多維標(biāo)度 /
- 分簇 /
- 距離誤差校正
Abstract: The classical MDS-MAP algorithm has the disadvantage of large error and the computational complexity increases sharply with the increase of network size in the localization of wireless sensor networks. The clustering method based on the residual energy of the neighbor nodes is designed. The cluster has the proper node degree and cluster size, which reduces the calculation amount and error of the next-step localization algorithm. Then, for the intra-cluster nodes with only connectivity information, the distance between the sink and other single-hop nodes is obtained using the time difference ranging method. A multi-hop distance error correction algorithm is proposed. The distance between nodes in a cluster is obtained using the geometrical relationship of neighboring nodes and the node connectivity. Multi-Dimensional Scaling (MDS) is used to calculate the relative coordinates of nodes in each cluster, and the inter-cluster coordinates are merged and converted into absolute coordinates by the anchor nodes. Finally, the localization of the nodes is realized. The proposed method provides more accurate information of inter-node distance based on energy clustering and multi-hop interval weighted geometric distance correction algorithm. Compared with classical MDS algorithm, this method can further improve the positioning accuracy and reduce the power consumption of wireless sensor network localization. -
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