基于小波变换的TDOA无线定位算法的研究

发布时间：2018-04-20 07:21

本文选题：到达时间差 + 小波变换　；参考：《西安邮电大学》2014年硕士论文

【摘要】：无线通信技术高速发展的今天,无线定位技术得到了人们更多的关注,能够快速准确的提供移动终端的位置信息、对移动终端进行实时跟踪成为了我们的迫切要求。因此,在不同的无线通信环境下,如何能够快速、有效的获得移动终端的位置信息成为了无线通信技术领域的研究热点问题。在定位算法的实际应用时,由于受非视距传播环境的影响,系统测量得到的定位数据往往存在很大的误差量,会影响无线定位算法的准确性,如何有效的消除非视距传播引起的误差量成为了定位算法中的研究重点问题。本文对此,提出了一种解决办法,利用小波降噪理论抑制非视距传播引起的误差量。首先详细介绍了小波分析理论,着重介绍小波降噪的方法及步骤,并通过分析非视距传播引起的误差量的模型从理论上验证了小波降噪消除测量误差的理论依据。接下来给出小波降噪对测量定位数据修正的具体步骤,并给出了两种定位算法。一种是基于TDOA测量值的定位算法,一种是基于TDOA/AOA的混合定位算法,两种算法均是依据修正后的测量值实现的定位算法。最后,在非视距环境中,对两种定位算法进行仿真评估。仿真结果表明,算法能够有效的实现移动台的位置估计,并且定位性能明显优于其它经典算法,说明本文提出的方法可以有效抑制非视距误差对定位算法性能的影响,提高了算法的定位精度。随着移动台定位技术的广泛应用,人们已不局限于要求对移动台的静态定位,对移动台的动态跟踪成为了迫切的要求。本文在提出上述定位算法的基础上,给出了两种跟踪办法,一种是利用相关距离检测门限提出的跟踪算法,一种是基于卡尔曼滤波的跟踪算法。在详细讲述两种算法的实现步骤之后对算法的性能进行仿真验证,从仿真结果上看,两种算法均能实现对移动台的跟踪,性能良好。在4G商用化的今天,OFDM技术得到了更多的关注。本文在OFDM系统中提出了一种基于小波变换的定位算法。首先利用多重信号分类(MUSIC)算法获取OFDM信号的到达时延,以此作为信号的TOA值,进而计算得到TDOA值,用小波降噪的方法对TDOA测量值进行修正,利用修正后的测量值实现对移动台的位置估计,最后根据相关算法实现动态跟踪。对算法进行仿真实验,结果表明算法性能良好。最后,对全文内中做了详细的总结,并对无线定位技术的发展做了展望。
[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.
【学位授予单位】：西安邮电大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：TN929.5

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