基于GAA模型的分布源直接定位方法
發(fā)布時(shí)間：2018-10-23 10:34
【摘要】：分布源定位是通信等領(lǐng)域的重要問題之一。實(shí)際應(yīng)用中,點(diǎn)目標(biāo)周圍往往密集地分布著散射點(diǎn),導(dǎo)致目標(biāo)信號(hào)在空間上產(chǎn)生一定的角度擴(kuò)展,傳統(tǒng)基于點(diǎn)源假設(shè)的定位方法用于這類場合將導(dǎo)致目標(biāo)定位性能下降。為此,需要針對(duì)具體分布式目標(biāo),建立合理的分布式目標(biāo)參數(shù)化模型及后續(xù)定位方法�，F(xiàn)有的分布源定位方法大都是基于觀測量估計(jì)的兩步定位方法,這類方法忽略了所有觀測量需要對(duì)應(yīng)于同一目標(biāo)的約束條件,使得其在低信噪比時(shí)定位精度不高。針對(duì)這一問題,本文著眼于分布式目標(biāo)的直接位置估計(jì)方法的學(xué)習(xí)和研究。本文主要內(nèi)容如下:(1)分布式目標(biāo)建模針對(duì)點(diǎn)源模型的局限,引入了角度擴(kuò)展參數(shù),建立分布式目標(biāo)的模型;介紹相干和非相干分布源的概念,由此引出空間頻率近似模型和兩點(diǎn)源近似模型這兩個(gè)簡化的非相干分布源模型;針對(duì)實(shí)際通信場景中的非相干分布源,引入GAA(Gaussian Angle of Arrival)模型;假設(shè)目標(biāo)源周圍分布的散射點(diǎn)服從高斯分布,對(duì)其空間模型和時(shí)間模型進(jìn)行了推導(dǎo),得到了該信道模型下的陣列響應(yīng)。(2)直接位置估計(jì)方法研究研究了目標(biāo)源位置直接估計(jì)的基本理論。不同于傳統(tǒng)兩步定位框架中先進(jìn)行中間參數(shù)的估計(jì)、再對(duì)目標(biāo)位置進(jìn)行估計(jì)的思路,直接定位方法直接基于原始接收數(shù)據(jù)對(duì)目標(biāo)位置進(jìn)行估計(jì):通過數(shù)據(jù)的頻域處理并基于最大似然準(zhǔn)則,推導(dǎo)出相應(yīng)的目標(biāo)位置估計(jì)代價(jià)函數(shù)。針對(duì)多目標(biāo)源場景,利用MVDR(Minimum Variance Distortionless Response)理論對(duì)信號(hào)進(jìn)行濾波,提高了定位方法的分辨率。仿真結(jié)果表明:直接定位在低信噪比時(shí)具有較低的誤差,MVDR方法具有良好的分辨率。(3)分布源直接定位方法研究將點(diǎn)源目標(biāo)位置直接估計(jì)方法推廣至分布源模型中,利用GAA模型對(duì)接收信號(hào)進(jìn)行建模,基于最大似然準(zhǔn)則得到分布源位置和散射半徑的估計(jì)。在此基礎(chǔ)上,研究幾種次優(yōu)的估計(jì)——犧牲少量定位精度,獲得更低計(jì)算復(fù)雜度。在基于代價(jià)函數(shù)進(jìn)行最優(yōu)化求解時(shí),利用梯度下降法對(duì)最優(yōu)目標(biāo)位置值進(jìn)行迭代搜索。幾種方法的仿真結(jié)果表明:最大似然估計(jì)具有最優(yōu)精度,最小二乘估計(jì)兼具高定位精度和較低的計(jì)算量。
[Abstract]:Distributed source location is one of the important problems in communication and other fields. In practical applications, scattered points are often distributed around the point targets, which leads to a certain angle expansion of the target signal in space. The traditional localization method based on point source assumption will lead to the degradation of target localization performance. Therefore, it is necessary to establish a reasonable parameterized model of distributed target and its subsequent localization method. Most of the existing distributed source localization methods are two-step localization methods based on the estimation of observations. This method ignores all the constraints corresponding to the same target and makes the localization accuracy low when the SNR is low. To solve this problem, this paper focuses on the study and research of direct position estimation for distributed targets. The main contents of this paper are as follows: (1) aiming at the limitation of point source model, distributed object modeling introduces angle extension parameters to establish distributed target model, and introduces the concepts of coherent and incoherent distributed sources. Two simplified incoherent distributed source models, namely spatial frequency approximation model and two-point source approximation model, are derived, and GAA (Gaussian Angle of Arrival) model is introduced for incoherent distribution sources in actual communication scenarios. Assuming that the scattering points around the target source are distributed from Gao Si, the spatial model and the time model are derived. The array response of the channel model is obtained. (2) the direct position estimation method is used to study the basic theory of direct target source location estimation. Different from the traditional two-step localization framework, the intermediate parameters are estimated first, and then the target position is estimated. The direct location method estimates the target position directly based on the original received data. By processing the data in frequency domain and based on the maximum likelihood criterion, the corresponding target location estimation cost function is derived. The MVDR (Minimum Variance Distortionless Response) theory is used to filter the signal for multi-target source scene, which improves the resolution of the localization method. The simulation results show that direct location has lower error when SNR is low, and MVDR method has good resolution. (3) Direct location method of distributed source is extended to the distributed source model. The GAA model is used to model the received signal, and the location and scattering radius of the distributed source are estimated based on the maximum likelihood criterion. On this basis, several sub-optimal estimators are studied, which sacrifice a small amount of positioning accuracy to obtain lower computational complexity. When solving optimization based on cost function, the gradient descent method is used to iteratively search the optimal target position. The simulation results of several methods show that the maximum likelihood estimation has the best accuracy, and the least square estimation has both high positioning accuracy and low computational complexity.
【學(xué)位授予單位】：電子科技大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：TN92
本文編號(hào)：2288979
[Abstract]:Distributed source location is one of the important problems in communication and other fields. In practical applications, scattered points are often distributed around the point targets, which leads to a certain angle expansion of the target signal in space. The traditional localization method based on point source assumption will lead to the degradation of target localization performance. Therefore, it is necessary to establish a reasonable parameterized model of distributed target and its subsequent localization method. Most of the existing distributed source localization methods are two-step localization methods based on the estimation of observations. This method ignores all the constraints corresponding to the same target and makes the localization accuracy low when the SNR is low. To solve this problem, this paper focuses on the study and research of direct position estimation for distributed targets. The main contents of this paper are as follows: (1) aiming at the limitation of point source model, distributed object modeling introduces angle extension parameters to establish distributed target model, and introduces the concepts of coherent and incoherent distributed sources. Two simplified incoherent distributed source models, namely spatial frequency approximation model and two-point source approximation model, are derived, and GAA (Gaussian Angle of Arrival) model is introduced for incoherent distribution sources in actual communication scenarios. Assuming that the scattering points around the target source are distributed from Gao Si, the spatial model and the time model are derived. The array response of the channel model is obtained. (2) the direct position estimation method is used to study the basic theory of direct target source location estimation. Different from the traditional two-step localization framework, the intermediate parameters are estimated first, and then the target position is estimated. The direct location method estimates the target position directly based on the original received data. By processing the data in frequency domain and based on the maximum likelihood criterion, the corresponding target location estimation cost function is derived. The MVDR (Minimum Variance Distortionless Response) theory is used to filter the signal for multi-target source scene, which improves the resolution of the localization method. The simulation results show that direct location has lower error when SNR is low, and MVDR method has good resolution. (3) Direct location method of distributed source is extended to the distributed source model. The GAA model is used to model the received signal, and the location and scattering radius of the distributed source are estimated based on the maximum likelihood criterion. On this basis, several sub-optimal estimators are studied, which sacrifice a small amount of positioning accuracy to obtain lower computational complexity. When solving optimization based on cost function, the gradient descent method is used to iteratively search the optimal target position. The simulation results of several methods show that the maximum likelihood estimation has the best accuracy, and the least square estimation has both high positioning accuracy and low computational complexity.
【學(xué)位授予單位】：電子科技大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：TN92
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