波束域变换将阵元域数据投影到一个低维的波束域空间,不仅能够减小信号处理算法的运算时间,提高算法性能,还能够抑制干扰.本文针对常规自适应波束域变换方法需要在线调整波束变换矩阵、更新波束域导向矢量由此导致实时实现困难的问题,提出一种高效的自适应波束域变换方法.该方法将波束域协方差矩阵与导向矢量均表示成不依赖自适应波束变换矩阵的闭合形式,省去在线调整与更新过程,使运算效率得到了显著提高.最后将该方法应用到波达方向(DOA)的估计之中,仿真研究表明,本文方法获得了比常规自适应方法更好的DOA估计性能.此外,本文方法还具有另一个非常突出的优点,即它可以有效抑制运动强干扰.这是因为本文方法无需训练波束变换矩阵,其当前运算结果与历史快拍数据无关,这样可以有效避免常规自适应方法中因目标运动所导致的训练数据与应用数据失配的问题.
Beam-space transformation projects the array data into a lower space, which is not only effective in reducing computation time, improving performance, but also being capable to suppress interference. In contrast to conventional adaptive beam-space transformation method, which often requires adjusting the beam-space matrix and steering vectors online, an efficient adaptive beam-space transformation method is proposed. In the proposed method, the beam-space covariance matrix and the steering vector both have closed-forms, and do not depend on the adaptive beam-space matrix. This eliminates the 0aline adjustment process, and, thus, improves the computational efficiency. Finally, the proposed method can also be applied to the direction of arrival (DOA) estimation. Simulation results demonstrate that it has a better DOA estimation performance than the conventional adaptive method. Furthermore, the proposed method also has another significant advantage, i.e., it is able to suppress moving interference. This can be ascribed to the proposed beam-space matrix which is independent of the historical data, and, thus, effective to avoid the mismatch between the training and application data, since this mismatch often occurs in conventional adaptive methods.