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利用信號(hào)非圓特性的陣列測(cè)向技術(shù)研究

發(fā)布時(shí)間:2018-07-20 20:15
【摘要】:現(xiàn)代雷達(dá)、通信系統(tǒng)中,經(jīng)常使用具有非圓特性的調(diào)制信號(hào),在陣列測(cè)向技術(shù)領(lǐng)域中,信號(hào)具有非圓特性會(huì)使得其偽協(xié)方差矩陣中也含有信息。因此如果合理地利用信號(hào)非圓特性將可以增加信息利用效率,提高陣列測(cè)向算法各項(xiàng)估計(jì)性能,因此,利用信號(hào)非圓特性的陣列測(cè)向方法已經(jīng)成為近年來的一個(gè)研究熱點(diǎn)。目前已有的適用于非圓信號(hào)的陣列測(cè)向方法多用于估計(jì)只有最大非圓率信號(hào)的情況,而當(dāng)入射信號(hào)中同時(shí)存在圓信號(hào)、非圓信號(hào)時(shí),會(huì)存在對(duì)信源數(shù)目估計(jì)準(zhǔn)確性不高、估計(jì)精度不足、分辨能力較差等現(xiàn)象。本文針對(duì)利用信號(hào)非圓特性的陣列測(cè)向方法做出了較為深入的研究,主要內(nèi)容如下:1.分析了現(xiàn)有信源數(shù)目估計(jì)方法的不足和局限性,提出了可以在色噪聲背景下對(duì)信源數(shù)目進(jìn)行估計(jì)的基于特征空間投影的CEP算法,并將其應(yīng)用于虛擬擴(kuò)展陣列,提出了可以在圓信號(hào)和非圓信號(hào)同時(shí)入射的情形下對(duì)等效信源數(shù)目進(jìn)行估計(jì)的基于均值聚類的MCEP算法。與目前已有方法相比,MCEP算法無論在信噪比和快拍數(shù)較低還是較高情況下均有較良好的估計(jì)性能,且在色噪聲背景下仍然能夠保持有效估計(jì)。2.針對(duì)DOA參數(shù)估計(jì)問題,分析了現(xiàn)有方法在入射信號(hào)中同時(shí)存在圓信號(hào)、一般非圓率信號(hào)和最大非圓率信號(hào)時(shí)會(huì)面臨存在偽峰和分辨力不足等問題的原因。提出了可以提高分辨力的HRNC-MUSIC算法,該方法可以對(duì)不同類別的信號(hào)依次做出估計(jì),減少了各類信號(hào)間相互影響,提高分辨能力。仿真結(jié)果表明,當(dāng)混合入射信號(hào)中各類信號(hào)之間的空間角距離相距較小時(shí),HRNC-MUSIC算法可以明顯提高對(duì)入射信號(hào)的分辨能力和估計(jì)精度。3.針對(duì)應(yīng)用于極化敏感陣列的DOA估計(jì)算法運(yùn)算量高、陣列擴(kuò)展能力不強(qiáng)等現(xiàn)象,提出了基于平面雙極化敏感陣列的DRL-MUSIC算法,并研究了同時(shí)利用信號(hào)非圓特性和極化信息的測(cè)向方法,提出了基于四元數(shù)的QNC-MUSIC算法和基于降維長矢量的DRLNC-MUSIC算法,填補(bǔ)了極化敏感陣列下適用于非圓信號(hào)測(cè)向方法的空白。仿真結(jié)果表明,當(dāng)入射信號(hào)只含最大非圓率信號(hào)時(shí),QNC-MUSIC算法的估計(jì)性能優(yōu)于DRLNC-MUSIC算法;而當(dāng)入射信號(hào)中既存在非圓信號(hào)又存在圓信號(hào)時(shí),DRLNC-MUSIC算法的估計(jì)性能要優(yōu)于QNC-MUSIC算法,且DRLNC-MUSIC算法可以同時(shí)對(duì)極化參數(shù)做出聯(lián)合估計(jì),不耗費(fèi)額外的計(jì)算量。
[Abstract]:In modern radar and communication systems, modulation signals with non-circular characteristics are often used. In the field of array direction finding technology, the non-circular characteristics of signals make the pseudo-covariance matrix contain information. Therefore, if the signal non-circular characteristics are used reasonably, the efficiency of information utilization can be increased and the estimation performance of the array direction finding algorithm can be improved. Therefore, the array direction finding method based on the non-circular characteristics of signals has become a hot research topic in recent years. Most of the current array direction finding methods for non-circular signals are used to estimate only the maximum non-circular rate signals, but when there are circular signals and non-circular signals in the incident signals, the estimation of the number of sources is not accurate. The estimation accuracy is insufficient, the resolution ability is poor and so on. In this paper, the array direction-finding method based on the non-circular characteristics of signals is studied in depth, the main contents are as follows: 1. In this paper, the shortcomings and limitations of the existing methods for estimating the number of sources are analyzed. A CEP algorithm based on feature space projection is proposed to estimate the number of sources under the background of color noise, and it is applied to the virtual extended array. An MCEP algorithm based on mean value clustering is proposed to estimate the number of equivalent sources when both circular and non-circular signals are incident at the same time. Compared with the existing methods, the MCEP algorithm has better estimation performance in the case of low SNR and high shot number, and can still maintain an effective estimation of .2. under the background of color noise. Aiming at the problem of DOA parameter estimation, this paper analyzes the reasons why the existing methods have circular signals in incident signals simultaneously, and the problems such as false peaks and insufficient resolution will be encountered in general non-circular rate signals and maximum non-circular rate signals. The HRNC-MUSIC algorithm which can improve the resolution is proposed. This method can estimate the different kinds of signals in order to reduce the interaction between different signals and improve the resolution ability. The simulation results show that the HRNC-music algorithm can obviously improve the resolution and estimation accuracy of the incident signals when the distance between the different signals is small. A novel DRL-MUSIC algorithm based on planar dual polarimetric sensing array is proposed to solve the problem of high computational complexity and low expansion ability of DOA estimation algorithm applied to polarization-sensitive arrays. At the same time, the method of direction finding based on the non-circular characteristic and polarization information is studied. The QNC-MUSIC algorithm based on quaternion and the DRLNC-MUSIC algorithm based on reduced dimension vector are proposed, which fills the blank of the direction finding method for non-circular signals under polarization sensitive array. Simulation results show that the estimation performance of QNC-MUSIC algorithm is better than that of DRLNC-MUSIC algorithm when the incident signal contains only the maximum non-circular rate signal, and the estimation performance of DRLNC-MUSIC algorithm is better than that of QNC-MUSIC algorithm when there are both non-circular and circular signals in the incident signal. Moreover, the DRLNC-MUSIC algorithm can simultaneously estimate the polarization parameters without additional computation.
【學(xué)位授予單位】:哈爾濱工程大學(xué)
【學(xué)位級(jí)別】:博士
【學(xué)位授予年份】:2014
【分類號(hào)】:TN911.7

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