提出了一种基于稀疏近似最小方差的宽带波达方向(DOA)估计算法,有效解决当前宽带波达方向估计方法分辨率较低、相干干扰条件下DOA估计误差大等问题。该算法在空域稀疏模型的基础上利用宽带相干信号子空间算法,将宽带信号聚焦到固定频点处,再以近似最小方差准则进行迭代,实现高分辨DOA估计。该算法得到的空间谱具有稀疏度高和副瓣低的特点,且与CSM算法相比无需任何先验信息。通过仿真计算表明,该算法的方位分辨能力较宽带传统DOA估计算法提升30% ,并具有分辨相干信号能力。通过某海试实测数据处理得到的时间历程图有效验证该算法性能。

A wideband signals direction-of-arrival (DOA) algorithm based on sparse asymptotic minimum variance(SAMV)is presented in this paper, which can effectively improve spatial resolution and anti-coherent-interference performance. Based on spatial sparse signal model, the algorithm transforms wideband signal to narrowband, using coherent signal subspace method (CSM), and then iterates with asymptotic minimum variance (AMV) approach to carry out high-resolution DOA estimation. The spatial spectrums implemented by this algorithm have the specialty of high sparse and extremely low side lobe. What忆s more, the prior information isn’t required in this algorithm. Computer simulations show that, this method improves 30￡￥ spatial resolution compared to traditional DOA algorithm, and coherent interference resistance. Bearing鄄time recording (BTR) results of a sea trial also demonstrate the efficiency of the algorithm.

TN957.52

国家自然科学基金资助项目(00000000);国家高技术研究发展计划( 863 计划) 资助项目(2008AA000000)