高分辨宽容阵列信号处理研究
文献类型：学位论文
| 作者 | 蒋飚 |
| 学位类别 | 博士 |
| 答辩日期 | 2005 |
| 授予单位 | 中国科学院声学研究所 |
| 授予地点 | 中国科学院声学研究所 |
| 关键词 | 阵列信号处理 波束形成 DOA估计 高分辨 宽容性 |
| 其他题名 | Research on robust high-resolution array signal processing |
| 中文摘要 | 高分辨阵列信号处理方法对信号模型的误差比较敏感，例如当不能确切知道阵列对期望信号的响应矢量时，自适应波束形成的性能会显著下降。本文主要研究如何提高高分辨阵列处理算法对模型误差的宽容性。为提高自适应波束形成对阵列方向矢量误差的宽容性，研究了一种基于方向矢量估计的宽容最小方差无畸变响应（MinimumVarianceDistortionlessResponse，MvDR）算法。利用观测数据对方向矢量作修正，减小其与真实信号响应矢量的误差，用方向矢量的估计量来求自适应权矢量，并由此得到一种自适应对角加载算法。提出一种基于数值优化的二次型约束宽容波束形成方法。限定自适应指向性函数与期望指向性函数在波束指向角附近的加权平方误差，稳定该空间区域内到达信号的增益，消除期望信号的自消，并利用最小方差准则，使阵列输出信号与干扰噪声比最大。为提高对强目标附近弱目标的分辨能力，研究了一种子空间波达方向估计（DireetionofArrival，DOA）估计的改进方法，人为注入一定功率从波束扫描角来的信号，形成增强的协方差阵，利用增强协方差阵与原协方差阵的噪声特征值的差异来估计信号DOA。研究了一种性能优于MUsIC（Mu1tinleSignalClassification）算法的信号空间标度的子空间算法，利用期望信号空间与干扰信号空间之间的斜投影，得到信号加干扰功率估计的误差，若波束扫描方向有信号，则功率误差为零，从而可确定信号方向。为提高空间相关噪声场中的DOA估计性能，研究了一种基于空时相关矩阵联合对角化的DOA估计方法。寻求一酉矩阵，能同时对一组空时相关矩阵作对角化，从而综合利用了信号空域和时域二阶统计信息，提高了估计精度和分辨力。提出一种低复杂性的扩展的Capon参数估计器（SpreadMV，SMV），解决空间扩展源的中心角和扩展角的估计问题，通过定义广义的阵列方向矢量，用Capon谱矩阵的Frobenius范数代替迹函数，提高了低信噪比下的估计性能。研究了几种宽带波束形成方法：基于信号正交分解的宽带MVDR算法，线性内插相干聚焦波束形成、子阵列处理方法、特征空间波束形成等。仿真分析和湖试、海试数据处理结果证明了本文所提各种的算法的有效性。 |
| 英文摘要 | It's well known that high resolution array signal processing algorithms are sensitive to signal model errors. For example, adaptive beamforming may suffer significantly performace degradation when the array response vector for the desired signal is not known exactly. In this paper, we'll mainly discuss how to improve the robustness of array signal processing to the model errors. A robust minimum variance distortionless response (MVDR) beamforming is proposed in order to increase robustness to the array steering vector errors, which is derived based on the estimation of the array steering vector. The steering vector can be regulated to approximate the actual signal response vector using the measurement data, then the adaptive weight vector is obtained by the estimate of the steering vector, and it can be transformed to an adaptive diagonal loading method. A quadratic constraint robust beamforming is proposed base on numerical optimization. The weighted least squared error between the adaptive beam pattern and the desired beam pattern over a small region around the array steering direction is constrained. As a result, the signals coming from the constrained region will suffer the least distortion, and the desired signal cancellation is avoided. The output signal-to-interference-plus-noise-ratio (SINR) is maximized using the criterion of minimum variance. An improved subspace based direction of arrival (DOA) estimation method is studied to improve the resolution capacity between the strong signal and the nearby relatively weak signal. An augumented covariance matrix is formed by artificially injecting a signal coming from the beam scanning angle with certain power. The DOAs can be estimated by the noise eigenvalue difference between the augumented covariance matrix and the original one. A signal subspace scaled DOA estimation method which outperforms the multiple signal classification (MUSIC) is studied. This method utilizes the oblique projection between the desired signal subspace and the interference subspace. By oblique projectons the power estimation error of the signal-plus-interference can be obtained, and the DOAs are estimated by the fact that the power error equals zero when the signal is coming from the array steering direction. To improve the DOA estimation performance in the spatial correlated noise field, a new method based on the joint diagonalization of spatio-temporal correlation matrices is put forward. A set of spatio-temporal correlation matrices can be diagonalized by a common unitary matrix. Both the spatial and temporal second order statistical information are utilized, consequently, the precision and resolution capacity is enhanced. A low-complexity spread Capon's estimator is proposed to estimate the nominal angle and the angle spread of the distributed sources. By defining a generalized array steering vector, and replacing the trace of Capon spectrum matrix with the corresponding Frobenius norm, the proposed estimator outperforms other techniques especially in low SNR scenarios. A few wideband beamforming techniques are studied, such as the signal quadrature decomposition based MVDR method, spatial coherently focusing beamforming by linear interpolation, subarray processing method, and eigenspace beamforming, etc. Simulation, lake and sea trial results demonstrated the effectiveness of all the proposed algorithms in this paper. |
| 语种 | 中文 |
| 公开日期 | 2011-05-07 |
| 页码 | 97 |
| 源URL | [http://159.226.59.140/handle/311008/944]  |
| 专题 | 声学研究所_声学所博硕士学位论文_1981-2009博硕士学位论文 |
| 推荐引用方式 GB/T 7714 | 蒋飚. 高分辨宽容阵列信号处理研究[D]. 中国科学院声学研究所. 中国科学院声学研究所. 2005. |
入库方式： OAI收割
来源：声学研究所
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