發(fā)布時(shí)間：2018-04-20 07:21

  本文選題：到達(dá)時(shí)間差 + 小波變換��； 參考：《西安郵電大學(xué)》2014年碩士論文

【摘要】：無(wú)線通信技術(shù)高速發(fā)展的今天,無(wú)線定位技術(shù)得到了人們更多的關(guān)注,能夠快速準(zhǔn)確的提供移動(dòng)終端的位置信息、對(duì)移動(dòng)終端進(jìn)行實(shí)時(shí)跟蹤成為了我們的迫切要求。因此,在不同的無(wú)線通信環(huán)境下,如何能夠快速、有效的獲得移動(dòng)終端的位置信息成為了無(wú)線通信技術(shù)領(lǐng)域的研究熱點(diǎn)問(wèn)題。 在定位算法的實(shí)際應(yīng)用時(shí),由于受非視距傳播環(huán)境的影響,系統(tǒng)測(cè)量得到的定位數(shù)據(jù)往往存在很大的誤差量,會(huì)影響無(wú)線定位算法的準(zhǔn)確性,如何有效的消除非視距傳播引起的誤差量成為了定位算法中的研究重點(diǎn)問(wèn)題。本文對(duì)此,提出了一種解決辦法,利用小波降噪理論抑制非視距傳播引起的誤差量。 首先詳細(xì)介紹了小波分析理論,著重介紹小波降噪的方法及步驟,并通過(guò)分析非視距傳播引起的誤差量的模型從理論上驗(yàn)證了小波降噪消除測(cè)量誤差的理論依據(jù)。接下來(lái)給出小波降噪對(duì)測(cè)量定位數(shù)據(jù)修正的具體步驟,并給出了兩種定位算法。一種是基于TDOA測(cè)量值的定位算法,一種是基于TDOA/AOA的混合定位算法,兩種算法均是依據(jù)修正后的測(cè)量值實(shí)現(xiàn)的定位算法。最后,在非視距環(huán)境中,對(duì)兩種定位算法進(jìn)行仿真評(píng)估。仿真結(jié)果表明,算法能夠有效的實(shí)現(xiàn)移動(dòng)臺(tái)的位置估計(jì),并且定位性能明顯優(yōu)于其它經(jīng)典算法,說(shuō)明本文提出的方法可以有效抑制非視距誤差對(duì)定位算法性能的影響,提高了算法的定位精度。 隨著移動(dòng)臺(tái)定位技術(shù)的廣泛應(yīng)用,人們已不局限于要求對(duì)移動(dòng)臺(tái)的靜態(tài)定位,對(duì)移動(dòng)臺(tái)的動(dòng)態(tài)跟蹤成為了迫切的要求。本文在提出上述定位算法的基礎(chǔ)上,給出了兩種跟蹤辦法,一種是利用相關(guān)距離檢測(cè)門(mén)限提出的跟蹤算法,一種是基于卡爾曼濾波的跟蹤算法。在詳細(xì)講述兩種算法的實(shí)現(xiàn)步驟之后對(duì)算法的性能進(jìn)行仿真驗(yàn)證,從仿真結(jié)果上看,兩種算法均能實(shí)現(xiàn)對(duì)移動(dòng)臺(tái)的跟蹤,性能良好。 在4G商用化的今天,OFDM技術(shù)得到了更多的關(guān)注。本文在OFDM系統(tǒng)中提出了一種基于小波變換的定位算法。首先利用多重信號(hào)分類(lèi)(MUSIC)算法獲取OFDM信號(hào)的到達(dá)時(shí)延,以此作為信號(hào)的TOA值,進(jìn)而計(jì)算得到TDOA值,用小波降噪的方法對(duì)TDOA測(cè)量值進(jìn)行修正,利用修正后的測(cè)量值實(shí)現(xiàn)對(duì)移動(dòng)臺(tái)的位置估計(jì),最后根據(jù)相關(guān)算法實(shí)現(xiàn)動(dòng)態(tài)跟蹤。對(duì)算法進(jìn)行仿真實(shí)驗(yàn),結(jié)果表明算法性能良好。 最后,對(duì)全文內(nèi)中做了詳細(xì)的總結(jié),并對(duì)無(wú)線定位技術(shù)的發(fā)展做了展望。
[Abstract]:With the rapid development of wireless communication technology, more and more attention has been paid to wireless positioning technology, which can provide the location information of mobile terminal quickly and accurately. It is urgent for us to track the mobile terminal in real time. Therefore, in different wireless communication environments, how to obtain the location information of mobile terminals quickly and effectively has become a hot issue in the field of wireless communication technology. In the practical application of the localization algorithm, due to the influence of the non-line-of-sight propagation environment, there is often a large error in the location data measured by the system, which will affect the accuracy of the wireless location algorithm. How to effectively eliminate the error caused by non-line-of-sight propagation has become a key problem in the localization algorithm. In this paper, a solution is proposed to suppress the error caused by non-line-of-sight propagation using wavelet denoising theory. Firstly, the theory of wavelet analysis is introduced in detail, and the methods and steps of wavelet noise reduction are emphasized, and the theoretical basis of eliminating measurement error by wavelet denoising is verified theoretically by analyzing the model of error caused by non-line-of-sight propagation. Then the detailed steps of wavelet denoising to modify the measurement location data are given, and two localization algorithms are given. One is a localization algorithm based on TDOA measurement value, the other is a hybrid localization algorithm based on TDOA/AOA. Finally, two localization algorithms are simulated and evaluated in the non-line-of-sight environment. The simulation results show that the algorithm can effectively realize the location estimation of mobile station, and the location performance is obviously superior to other classical algorithms, which shows that the proposed method can effectively suppress the influence of the non-line-of-sight error on the performance of the location algorithm. The accuracy of the algorithm is improved. With the wide application of mobile station positioning technology, people are not limited to the static positioning of mobile station, and the dynamic tracking of mobile station has become an urgent requirement. Based on the above algorithms, two tracking methods are presented in this paper, one is based on the threshold of correlation distance detection, the other is based on Kalman filter. After describing the implementation steps of the two algorithms in detail, the performance of the algorithm is verified by simulation. From the simulation results, the two algorithms can track the mobile station, and the performance is good. In the 4G commercialization of today's OFDM technology has received more attention. In this paper, a localization algorithm based on wavelet transform is proposed in OFDM system. First, the arrival delay of OFDM signal is obtained by using the multiplex signal classification algorithm, which is used as the TOA value of the signal, and then the TDOA value is calculated, and the TDOA measurement value is corrected by wavelet denoising method. The position estimation of the mobile station is realized by using the revised measurement value, and the dynamic tracking is realized according to the correlation algorithm. The simulation results show that the performance of the algorithm is good. Finally, a detailed summary is made and the development of wireless positioning technology is prospected.
【學(xué)位授予單位】：西安郵電大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2014
【分類(lèi)號(hào)】：TN929.5

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本文編號(hào)：1776802