【作者】 武思军；

【导师】 张曙；

【作者基本信息】 哈尔滨工程大学 ， 通信与信息系统， 2005， 博士

【摘要】 阵列信号处理作为信号处理领域中的一个重要分支,其应用涉及到雷达、声纳、通信以及医疗诊断等多种领域。通过对信号在时间和空间上进行采样和处理,可更加充分地开发信号中蕴含的信息,有效地抑制干扰、提高系统的效率。虽然自适应阵列信号处理在理想的情况下可以达到很好的性能,但由于实际系统中存在的误差,会严重影响到阵列信号处理最后的输出性能,所以,寻求稳健的阵列信号处理算法一直是广大研究者追求的目标。本文通过对阵列信号处理中现有算法的研究,提出和改进了一些现有的算法,使之更加具有稳健性,适应更加复杂和恶劣的环境。 首先针对MVDR算法对指向误差敏感的缺点,通过方向矢量旋转的方法,提出一种在指向误差存在情况下的稳健自适应波束形成算法,并给出角度旋转的选择准则。并基于干扰方向矢量旋转的方法,提出一种零陷加宽的算法,使MVDR算法可以在干扰快速移动时稳健工作。 通过数值分析的方法,对前后向空间平滑的协方差矩阵进行了分析,得出后向平滑矩阵是前向平滑矩阵中元素的重新排列的结论,并通过分析均匀线阵的导向矩阵,指出协方差矩阵本身就包含了平滑子矩阵的全部信息,不仅有效降低了空间平滑算法的运算量,同时使空间平滑处理更加灵活方便。 由于高阶累积量计算的相对复杂性,关于高阶累积量的算法主要还停留在理论研究阶段,本文分析了MUSIC-LIKE算法对均匀线阵的阵列扩展作用,将累积量矩阵压缩到最小,为(2M-1)×(2M-1)的累积量矩阵,较为显著的减少了运算量。另外,分析了相干信号情况下广义导向矢量的估计问题,将盲自适应波束形成算法和特征分析法相结合,提高了盲算法在小信号情况下的性能。 通信中的绝大部分信号均存在循环平稳的性质,利用信号的循环平稳性已经在阵列信号处理中形成了很多算法,如SCORE、CAB算法等,但当系统中存在循环频率误差时,由于存在sinc函数的零点效应,算法性能随着快拍数的增加而出现周期性的性能恶化。本文通过将循环频率均匀分布在选择的区间上,将该区间的所有循环自相关矩阵进行累加,然后用累加后的自相更多还原

【Abstract】 The array signal processing as an important branch of the signal processing domain is applied for many areas such as radar, sonar, communication and biomedical testing. It can exploit sufficiently the information of the signal by sampling the signal in time-spatial domain to suppress the interference and increase the SINR of the system. The adaptive array signal processing can obtain good performance in the ideal cases. But the errors in the system always severely affect the performance of the array signal processing. So many researchers are trying to research robust array signal processing algorithms. This paper introduced several algorithms to improve the robusness, which makes the system more robust for the complicated scenario.Firstly, a robust adaptive beamforming algorithm in the presence of the pointing error is proposed by the steering vector rotation method aiming at the shortcoming of the MVDR sensitive to the pointing error, and proposed the choice criterion of the angle rotation quantity. Secondly, a NULL-broadening method is proposed by the interference steering vector rotation, which increases the MVDR algorithm’s robustness when the interference moves quickly.Analyzing the forward-backward covariance by the numerical analysis, we reached a conclusion that the backward smoothing matrix is the rearrange of the forward smoothing matrix, and the covariance matrix includes itself the all information of the smoothing submatrix by analyzing the steering vector of the uniform linear array. As a result, the computation effort of the spatial smoothing algorithm can be reduced. The algorithm also makes the spatial smoothing processing more flexible.Due to the computation complexity of the higher order cumulant(HOC), the algorithms of HOC exists in the theoretical analysis stage. This paper analyzies the extension of the MUSIC-LIKE method for uniform linear array, and reduces the size of cumulant matrix to (2M-Y)×(2M-1) which leads the reduction ofthe computation effort. On the other hand, this paper analyses the problem of the generalized steering vector in the presence of the coherent signals, and combines the blind adaptive beamforming with eigen-analysis algorithm to improve the performance of the blind algorithm for the weak signal cases.The most signals in the communication system have the cyclostationary property. Many algorithms based on the cyclostationary of the signal in the array signal processing have been exploited, such as SCORE, CAB and so on. But the performance of the algorithms have periodic zero point as the number of snapshot increasing when there is the error of the cycle frequency in the system due to the effect of the sine function. This paper assumes that the distribute of the cycle frequency is uniform in the specific interval and cumulant the all cycle autocorrelation matrix, then perform the CAB operation utilizing the cumulant cycle autocorrelation matrix, which can improve the robustness of the algorithm when the correct cycle frequency exists in this interval. At the end, this paper studies the problem of the DOA in the presence of the coherent signal utilizing the cyclostationary property of the signal, and obtains some significant conclusions.更多还原