【作者】 谢菊兰；

【导师】 何子述；

【作者基本信息】 电子科技大学 ， 信号与信息处理， 2012， 博士

【摘要】 阵列信号处理是信号处理领域的一个重要分支，其最主要研究内容包括自适应波束形成（Adaptive Beamforming,ABF）和波达方向（Direction OfArrive，DOA）估计。ABF和DOA估计可提高阵列天线的性能，在军用与民用方面具有广泛的应用前景。阵列信号处理的基础是阵列结构。由于考虑了空气动力学或水力学，共形阵能进一步提高系统性能。均匀圆阵（Uniform Circular Array,UCA）和球阵（SphericalArray）是共形阵中比较典型的阵列结构，可提供360的方位角覆盖，并且在各个方向上可具有相同的测向性能。此外，它们还能提供俯仰角信息。因此，与均匀线阵和其他的一些平面阵相比，均匀圆阵更适于被应用在雷达、声纳和无线通信等领域，而由于球阵能提供180的俯仰角覆盖范围，其更适于应用在卫星通信领域。本文主要研究了基于均匀圆阵和球形阵列的自适应波束形成和DOA估计算法。主要工作和贡献有：（1）均匀圆阵常规去相干波束形成算法中模式变换引起噪声功率发生改变，从而导致算法性能下降。针对该问题，提出了一种给同心双圈阵列加权的方法来消除模式变换给噪声功率带来的变化。仿真结果表明该方法大大改善了输出SINR。（2）提出了一种高效的实值权去相干波束形成算法。该算法可以通过只使用实值权来抑制相干干扰，并且不需进行空间平滑去相干，因此大大减小了计算量。此外，它在低信噪比和小快拍下能快速收敛，并性能稳定。（3）提出了一种均匀圆阵的相干信源DOA估计的差分算法。该方法具有很强的信源过载能力，且兼顾了相干及非相关信源的分辨。（4）提出了一种未知互耦条件下的快速DOA估计算法，并给出了一种新的除伪方法。相对于互耦效应存在时常规的盲DOA估计算法，所提算法的计算量显著降低。（5）提出了一种互耦效应存在时的基于稀疏均匀圆阵的混合算法。与互耦效应存在时已有的计算量较小的二维DOA估计算法不同的是，该算法不需要足够多的阵元来支撑其采用传统的波束空间变换。以阵列流形分解技术为基础，我们提出了一种改进的UCA-RARE来估计方位角，并使用Root-MUSIC算法来估计俯仰角。对于稀疏均匀圆阵来说，与UCA-RARE相比，改进的UCA-RARE能够消除一些由阵列稀疏带来的伪解。阵列流形分解引入的截断误差影响DOA估计精度，因此，我们分析了该误差对DOA估计的影响。（6）研究了三种球形阵列的阵元分布方式，并讨论了它们的球形模式变换。同时还研究了一种球形ESPRIT算法，完善了该算法并对这三种不同分布方式下的该算法的性能进行了研究。此外还提出了另外两种球形ESPRIT算法，并研究了他们的性能。更多还原

【Abstract】 The array signal processing，an important branch of signal processing, mainlyincludes adaptive beamforming and DOA estimation techniques. Adaptivebeamforming and DOA estimation techniques, which can improve the performance ofthe array antenna, have broad application prospects in military and civilian applications.The foundation of the array signal processing is the array configuration. Due to theconsideration of aerodynamics or hydraulics, the comformal array is able to furtherimprove the performance of the system. The uniform circular array (UCA) and thespherical array, two typical configurations of the confomal array, are able to provide360o of coverage in the azimuth plane and have uniform performance regardless ofangle of arrival. Moreover, they can provide the elevation angle information. Therefore,compared with the uniform linear array and other planar arrays, the UCA is moresuitable for applications such as radar, sonar, and wireless communications. On theotherhand, due to the180coverage in elevation plane, the spherical array is moresuitable for satellite commulication. In this dissertation, we mainly study thealgorithms of adaptive beamforming and DOA estimation for UCAs and sphericalarrays. Works and contributiones in the dissertation mainly include:(1) The mode transformation applied to the beamforming of coherent signals willcause the noise power altering. This leads to a degraded performance of theconventional beamforming algorithms. In order to solve this problem, we propose amethod of weighing virtual array of two concentric ring arrays, which significantlyimproves the output SINR.(2) The conventional beamforming algorithms of coherent signals usually havehigh computation complexity. An effective algorithm that uses real weights withoutphase shift is proposed. The interference is suppressed by using real weightgs and thedecorrelation of the signal sources is realized without spatial smoothing technique.Terefore the computation complexity is reduced. Moreover, this algorithm has rapidconvergency and stable performance in case of low SNR and finite snapshots.(3) A difference algorithm of DOA estimation for coherent sources with the UCA is proposed. Compared with the conventional DOA estimation algorithms, theproposed algorithm occupies stronger overload ability of signal sources and takes boththe resolution of the coherent and noncoherent signal sources into account.(4) A fast DOA estimation algorithm in the presence of an unknown mutualcoupling is proposed for UCAs. Meanwhile, a new method to remove the spuriousestimates is presented. Compared with the conventional DOA algorithms in thepresence of the unknown mutual coupling, the computation burden of the proposedalgorithm is greatly reduced.(5) A novel hybrid approach for2D DOA estimation in the presence of mutualcoupling based on sparse UCA is proposed. Different from the existing2D DOAalgorithms in the presence of mutual coupling, whose computation burdern is low, theproposed algorithm does not require the number of antenna elements to be sufficient toapply the traditional beamspace transoforamtion. Based on the manifold decompositiontechnique, a modified UCA-RARE algorithm is proposed to estimate the azimuth angleand the Root-MUSIC algorithm is employed to estimate the elevation angle. For sparseUCAs, compared with the original UCA-RARE, the modified UCA-RARE is able toavoid spurious estimates which only arise from the sparseness of the array elements.It’s shown that the estimate accuracy usually depends on the truncation errorintroduced by manifold decomposition techniques. Hence, we analyze the truncationerrors for sparse UCAs and derive expressions describing the truncation errors in theDOA estimates.(6) Three different distributions of a spherical array antenna are introduced andtheir spherical mode transformations are discussed. A modified spherical ESPRITalgorithm is also presented. The performances of this algorithm applied to the threedifferent distributions are evaluated. Moerover, other two kinds of spherical ESPRITalgorithms are proposed. The performances of the proposed spherical ESPRITalgorithms are also studied.更多还原