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NLOS環(huán)境下基于WSN的救援人員定位系統(tǒng)研究
2020年電子技術(shù)應(yīng)用第12期
王欽銳1,黃越洋1,石元博2,張吉祥1,左梓邑1
1.遼寧石油化工大學(xué) 信息與控制工程學(xué)院,遼寧 撫順113001; 2.遼寧石油化工大學(xué) 計(jì)算機(jī)與通信工程學(xué)院,遼寧 撫順113001
摘要: 在大型建筑災(zāi)難發(fā)生過程中,由于受到有毒煙霧、噪聲、大火、漏電、光線等不利因素影響,加上大型建筑內(nèi)部結(jié)構(gòu)復(fù)雜,很多救援人員難以獲得可靠的信息。針對(duì)上述情況,無線傳感器網(wǎng)絡(luò)在室內(nèi)復(fù)雜環(huán)境定位方面可以發(fā)揮其優(yōu)勢(shì)作用,但目前面臨的挑戰(zhàn)就是在LOS環(huán)境下其定位精度非常高,然而在NLOS環(huán)境下其測(cè)量可能會(huì)受到非視距傳播的污染,從而導(dǎo)致定位精度下降。針對(duì)這一現(xiàn)象,提出一種改進(jìn)的無跡卡爾曼濾波(MKF)定位方法。首先,采用檢驗(yàn)統(tǒng)計(jì)方法識(shí)別移動(dòng)節(jié)點(diǎn)和信標(biāo)節(jié)點(diǎn)之間的傳播狀態(tài)。然后,利用線性卡爾曼濾波器(LKF)平滑測(cè)量距離,在此基礎(chǔ)上利用MKF削弱NLOS對(duì)于測(cè)量產(chǎn)生的影響。之后,采用無跡卡爾曼濾波(UKF)方法來確定未知移動(dòng)節(jié)點(diǎn)的位置信息。最后通過數(shù)值仿真實(shí)驗(yàn)驗(yàn)證了所提算法的有效性。
中圖分類號(hào): TN911.23
文獻(xiàn)標(biāo)識(shí)碼: A
DOI:10.16157/j.issn.0258-7998.200409
中文引用格式: 王欽銳,黃越洋,石元博,等. NLOS環(huán)境下基于WSN的救援人員定位系統(tǒng)研究[J].電子技術(shù)應(yīng)用,2020,46(12):78-82,88.
英文引用格式: Wang Qinrui,Huang Yueyang,Shi Yuanbo,et al. Research on the location system of rescuers based on WSN in NLOS environment[J]. Application of Electronic Technique,2020,46(12):78-82,88.
Research on the location system of rescuers based on WSN in NLOS environment
Wang Qinrui1,Huang Yueyang1,Shi Yuanbo2,Zhang Jixiang1,Zuo Ziyi1
1.The School of Information and Control Engineering,Liaoning Shihua University,F(xiàn)ushun 113001,China; 2.The School of Computer and Communication Engineering, Liaoning Shihua University,F(xiàn)ushun 113001,China
Abstract: During the process of large building disaster, due to the adverse effects of toxic smoke, noise, fire, electricity leakage, light and other factors, as well as the complex internal structure of large buildings, it is difficult for many rescuers to obtain reliable information. Considering the above situation, wireless sensor networks can play their advantages in positioning indoor complex environments. But there is a challenge. Although their positioning accuracy is very high in the LOS environment, their measurement may be polluted by non-line-of-sight propagation in the NLOS environment, which results in a decrease in positioning accuracy. To solve this problem, we propose an improved location method based on unscented Kalman filter(UKF). Firstly, the propagation state between mobile node and beacon node is identified by means of test statistics. Secondly, the linear Kalman filter(LKF) is used to measure the distance smoothly. On this basis, a modified Kalman filter(MKF) is used to weaken the influence of NLOS on the measurement. Then, the UKF method is used to determine the location information of the unknown mobile node. Finally, the effectiveness of the proposed algorithm is verified by numerical simulation.
Key words : wireless sensor network;nonline-of-sight;unscented Kalman filter;location;rescue

0 引言

    隨著中國城市化進(jìn)程速度的加快,高建筑物密度區(qū)域也在不斷增加。因此,這些城市化區(qū)域在面臨大型災(zāi)難應(yīng)對(duì)方面遭受著巨大壓力[1-2]。GPS在空曠的環(huán)境下定位能夠發(fā)揮巨大優(yōu)勢(shì),可對(duì)于復(fù)雜的室內(nèi)環(huán)境則顯得力不從心,而無線傳感器因其網(wǎng)絡(luò)自組織能力強(qiáng)、易部署、低能耗等特點(diǎn)在室內(nèi)定位中有著較為良好的應(yīng)用前景[3]。目前最為普遍的基于距離的定位方法有到達(dá)時(shí)間(TOA)定位方法、到達(dá)時(shí)間差(TDOA)定位方法、接收信號(hào)強(qiáng)度(RSS)定位方法和到達(dá)角(AOA)[4-5]定位方法等。

    由于NLOS定位方法傳播誤差被認(rèn)為是定位系統(tǒng)的主要誤差來源之一,因此在無線傳感器網(wǎng)絡(luò)定位中,識(shí)別NLOS傳播和削弱NLOS的影響非常重要。在過去的十幾年中,關(guān)于NLOS識(shí)別和削弱的研究方法層出不窮。在文獻(xiàn)[6]中,作者采用二元假設(shè)檢驗(yàn)來識(shí)別測(cè)量的LOS狀態(tài);在文獻(xiàn)[7]中,提出了似然比檢驗(yàn)的方法;在文獻(xiàn)[8-9]中,作者提出了統(tǒng)計(jì)分析方法。這些方法被廣泛應(yīng)用于NLOS的鑒定。對(duì)于運(yùn)動(dòng)目標(biāo)跟蹤問題,文獻(xiàn)[10]采用卡爾曼濾波算法的線性回歸模型生成測(cè)量值的殘差,然后對(duì)殘差進(jìn)行篩選;文獻(xiàn)[11]采用多項(xiàng)式擬合和基于KF統(tǒng)計(jì)分析的方法進(jìn)行NLOS識(shí)別,然后采用極大似然法進(jìn)行定位;文獻(xiàn)[12]提出了采用偽測(cè)量位置來檢測(cè)LOS或NLOS的測(cè)量信息,然后利用KF對(duì)所選的LOS偽測(cè)量位置求平均的方法進(jìn)行運(yùn)動(dòng)目標(biāo)定位;文獻(xiàn)[13]采用兩個(gè)平行的卡爾曼濾波器對(duì)測(cè)量進(jìn)行濾波,之后用擴(kuò)展卡爾曼的方法進(jìn)行定位;文獻(xiàn)[14]提出了基于UKF的IMM方法來估計(jì)移動(dòng)目標(biāo)的位置。

    然而,這些算法需要大量的計(jì)算、高錨節(jié)點(diǎn)(ANs)密度和大量的信息等?;谝陨戏治觯疚牟捎没诰嚯x的測(cè)量方法TOA進(jìn)行測(cè)距,并對(duì)此進(jìn)行平滑,之后利用假設(shè)檢驗(yàn)的方法辨識(shí)傳播狀態(tài),并采用MKF來削弱NLOS帶來的偏置誤差。最后采用UKF來確定移動(dòng)節(jié)點(diǎn)的位置。




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作者信息:

王欽銳1,黃越洋1,石元博2,張吉祥1,左梓邑1

(1.遼寧石油化工大學(xué) 信息與控制工程學(xué)院,遼寧 撫順113001;

2.遼寧石油化工大學(xué) 計(jì)算機(jī)與通信工程學(xué)院,遼寧 撫順113001)

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