本文選題：室內(nèi)定位 + 超寬帶��； 參考：《廣東工業(yè)大學(xué)》2017年碩士論文

【摘要】：隨著科學(xué)技術(shù)的迅猛發(fā)展,人們對(duì)位置服務(wù)的需求變得越來(lái)越多,對(duì)位置定位精度的要求越來(lái)越高。位置服務(wù)產(chǎn)業(yè)在智慧城市、救災(zāi)減災(zāi)、物聯(lián)網(wǎng)等諸多領(lǐng)域都存在廣闊的市場(chǎng)�，F(xiàn)如今,全球定位系統(tǒng)GPS已經(jīng)有效解決了室外的定位問題,同時(shí)隨著生活水平的提高,人們對(duì)部分特殊病人(如:老年癡呆癥患者、高危傳染病患者以及精神狀態(tài)異�；颊叩�)的安全監(jiān)護(hù)問題也變得越來(lái)越重視,對(duì)位置服務(wù)的關(guān)注重心也開始從室外逐漸轉(zhuǎn)移到室內(nèi)。由于室內(nèi)環(huán)境復(fù)雜,存在大量非視距因素,傳統(tǒng)的室內(nèi)無(wú)線定位技術(shù)如:射頻識(shí)別、藍(lán)牙、超聲波等,在定位精度上已經(jīng)很難滿足人們的需求。而超寬帶技術(shù)以其具有的抗干擾能力強(qiáng)、穿透能力強(qiáng)和定位精度高等適合于室內(nèi)定位環(huán)境的優(yōu)點(diǎn),在室內(nèi)人員精確定位上得到人們更多的青睞。本文也將在基于超寬帶技術(shù)的定位算法上展開研究。首先,本文研究了超寬帶信號(hào)與室內(nèi)傳輸信號(hào)模型的特性,并選用IEEE802.15.4a模型作為本文的超寬帶信道模型。接著介紹了幾種超寬帶定位中常用的測(cè)距方法和經(jīng)典定位算法,并對(duì)誤差的主要來(lái)源和對(duì)非視距誤差的鑒別與抑制方法展開討論。詳細(xì)介紹了三種非視距鑒別與抑制算法,分別為:N-Taylor算法、基于幾何面積的鑒別算法和基于Chan的殘差加權(quán)算法。然后,結(jié)合雙向測(cè)距TWR與到達(dá)時(shí)間差測(cè)距TDOA的測(cè)距原理,提出一種TWR/TDOA混合測(cè)距的方法,該測(cè)距方法不需要考慮參考節(jié)點(diǎn)與目標(biāo)節(jié)點(diǎn)時(shí)鐘同步,同時(shí)有效減小了TWR測(cè)距階段由節(jié)點(diǎn)對(duì)信號(hào)響應(yīng)時(shí)造成的時(shí)延誤差問題。在非視距誤差問題的處理上,本文在基于幾何面積的鑒別算法和基于Chan的殘差加權(quán)算法的基礎(chǔ)上進(jìn)行適當(dāng)修改,并通過(guò)迭代加權(quán)的方式對(duì)測(cè)距估計(jì)值進(jìn)行修正,直到其結(jié)果到達(dá)規(guī)定的門限值為止,從而降低系統(tǒng)的定位誤差。最后,本論文采用MATLAB軟件,在室內(nèi)環(huán)境下和視距與非視距環(huán)境下分別對(duì)經(jīng)典Chan算法、經(jīng)典Taylor算法、幾何面積鑒別法與本文提出的TWR/TDOA混合定位算法進(jìn)行了仿真實(shí)驗(yàn)與分析,結(jié)果表明,無(wú)論在視距還是非視距仿真環(huán)境下,本論文提出的基于TWR/TDOA的混合定位算法的定位精度更高,定位位置的穩(wěn)定性更好。
[Abstract]:With the rapid development of science and technology, the demand for location service becomes more and more. Location service industry in intelligent cities, disaster relief, Internet of things and many other fields have a broad market. Nowadays, GPS GPS has effectively solved the problem of outdoor positioning, and with the improvement of living standards, some special patients (such as Alzheimer's disease) have been treated. The safety monitoring of high risk infectious disease patients and patients with abnormal mental state has become more and more important, and the focus of attention on location services has gradually shifted from outdoor to indoor. Because of the complex indoor environment and a large number of non-line-of-sight factors, the traditional indoor wireless positioning technology, such as radio frequency identification, Bluetooth, ultrasonic and so on, has been difficult to meet the needs of people in positioning accuracy. Ultra-wideband (UWB) technology is suitable for indoor positioning environment because of its strong anti-interference ability, strong penetration ability and high positioning accuracy, so it has been more and more popular in precise positioning of indoor personnel. In this paper, the location algorithm based on UWB technology will also be studied. Firstly, the characteristics of UWB signal and indoor transmission signal model are studied, and the IEEE802.15.4a model is chosen as the UWB channel model in this paper. Then, several common ranging methods and classical localization algorithms in UWB location are introduced, and the main sources of errors and the identification and suppression methods of non-line-of-sight errors are discussed. Three kinds of non-line-of-sight discriminant and suppression algorithms are introduced in detail, namely: N-Taylor algorithm, geometric area discriminant algorithm and residual weighting algorithm based on Chan. Then, combining the principle of bidirectional ranging TWR and time-of-arrival ranging (TDOA), a hybrid ranging method of TWR/TDOA is proposed, which does not need to consider the synchronization of reference node and target node clock. At the same time, the delay error caused by the response of the node to the signal in the TWR ranging phase is reduced effectively. Based on the geometric area discriminant algorithm and the residual weighting algorithm based on Chan, the non-line-of-sight error problem is properly modified, and the range estimation is modified by iterative weighting method. The positioning error of the system is reduced until the result reaches the prescribed threshold. Finally, MATLAB software is used to simulate and analyze the classical Chan algorithm, classical Taylor algorithm, geometric area identification algorithm and the TWR/TDOA hybrid localization algorithm proposed in this paper. The results show that the proposed hybrid localization algorithm based on TWR/TDOA is more accurate and more stable in the visual range or non-line-of-sight simulation environment.
【學(xué)位授予單位】：廣東工業(yè)大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：TN925

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