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室內(nèi)環(huán)境中基于天牛須尋優(yōu)的普適定位方法

劉影,  錢志鴻,  賈迪

劉影, 錢志鴻, 賈迪. 室內(nèi)環(huán)境中基于天牛須尋優(yōu)的普適定位方法[J]. 電子與信息學(xué)報, 2019, 41(7): 1565-1571. doi: 10.11999/JEIT181021
引用本文: 劉影, 錢志鴻, 賈迪. 室內(nèi)環(huán)境中基于天牛須尋優(yōu)的普適定位方法[J]. 電子與信息學(xué)報, 2019, 41(7): 1565-1571. doi: 10.11999/JEIT181021
Ying LIU, Zhihong QIAN, Di JIA. Universal Localization Algorithm Based on Beetle Antennae Search in Indoor Environment[J]. Journal of Electronics & Information Technology, 2019, 41(7): 1565-1571. doi: 10.11999/JEIT181021
Citation: Ying LIU, Zhihong QIAN, Di JIA. Universal Localization Algorithm Based on Beetle Antennae Search in Indoor Environment[J]. Journal of Electronics & Information Technology, 2019, 41(7): 1565-1571. doi: 10.11999/JEIT181021

室內(nèi)環(huán)境中基于天牛須尋優(yōu)的普適定位方法

doi: 10.11999/JEIT181021
  • 1.

    遼寧工程技術(shù)大學(xué)電子與信息工程學(xué)院 葫蘆島 125105

  • 2.

    吉林大學(xué)通信工程學(xué)院 ??長春 ??130022

基金項目: 國家自然科學(xué)基金青年基金(61601213)，遼寧省教育廳一般項目資金(LJ2017QL013)，遼寧省博士啟動基金(20170520098)，中國博士后面上基金(2017M611252)，遼寧省創(chuàng)新人才支持計劃項目(LR2016045)
詳細(xì)信息
    作者簡介:

    劉影：女，1983年生，講師，研究方向為無線定位、非接觸式物體識別

    錢志鴻：男，1957年生，教授、博士生導(dǎo)師，研究方向為基于物聯(lián)網(wǎng)，D2D，Wi-Fi，RFID等無線網(wǎng)絡(luò)與通信技術(shù)

    賈迪：男，1982年生，副教授，研究方向為圖像處理、計算機(jī)視覺及模式識別

    通訊作者:

    劉影　lycommunication@126.com

  • 中圖分類號: TN92

Universal Localization Algorithm Based on Beetle Antennae Search in Indoor Environment

  • 1.

    School of Electronic and Information Engineering, Liaoning Technical University, Huludao 125105, China

  • 2.

    College of Communication Engineering, Jilin University, Changchun 130022, China

Funds: The National Natural Foundation of China(61601213), The Project of Educational Commission of Liaoning Province of China (LJ2017QL013), Liaoning Province Doctor Startup Fund(20170520098), China Postdoctoral Science Foundation (2017M611252), The Project of Innovative Talents Support of Liaoning Province of China (LR2016045)
  • 摘要: 在復(fù)雜的室內(nèi)環(huán)境中，測得的接收信號強(qiáng)度(RSS)值會出現(xiàn)不同程度的波動，導(dǎo)致無法準(zhǔn)確地刻畫出無線信號傳播模型。為了解決這個問題，在基于Wi-Fi測距定位模型下，該文提出一種普適的粗粒度定位方法。該方法通過對測量到的RSS值進(jìn)行擬合，以此獲取信號的傳播模型；在此基礎(chǔ)上計算出未知節(jié)點與接入點(AP)的距離，再利用天牛須算法實現(xiàn)未知節(jié)點定位，通過仿真驗證此傳播模型的性能以及該優(yōu)化算法的有效性。
    Abstract: In complex indoor environment, the measured Received Signal Strength (RSS) values will fluctuate in different degrees, which lead to inaccurate characterization of wireless signal propagation model. To solve this problem, a universal coarse grained localization method is proposed based on the Wi-Fi ranging location model. This method gets the signal propagation model by fitting the measured RSS value. On this basis, the distance between the unknown node and the Access Point (AP) is calculated, then the location of the unknown node is realized by the beetle antennae search algorithm. The performance of the propagation model and the effectiveness of the optimization algorithm are verified by simulation.
    • HTML全文

  • 圖  1  RSS測量值

    圖  2  測試場景

    圖  3  DSPM測距結(jié)果值

    圖  4  式(1)測量結(jié)果值

    圖  5  改變DSPM參數(shù)后得到的測量結(jié)果

    圖  6  不同${\rm{step}}$取值定位誤差隨隨機(jī)步長$l$的變化

    圖  7  收斂速度

    圖  8  不同AP數(shù)目的定位誤差對比

    表  1  本文算法與經(jīng)典算法對比

    真實位置測量位置誤差(m)收斂速度
    BAS-DSPM(0, 0)(0.7123, 1.4437)1.6098迭代27次趨于平穩(wěn)
    PSO-DSPM(0, 0)(1.3654, –1.8031)2.2617迭代108次趨于平穩(wěn)
    PSO-經(jīng)典測距模型(0, 0)(–2.0462, 3.4623)4.0217迭代98次趨于平穩(wěn)
    下載: 導(dǎo)出CSV
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出版歷程
  • 收稿日期:  2018-11-06
  • 修回日期:  2019-02-24
  • 網(wǎng)絡(luò)出版日期:  2019-04-02
  • 刊出日期:  2019-07-01

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