摘要
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 presen- ted 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 iter- ates with asymptotic minimum variance (AMV) approach to carry out high-resoluition DOA estimation. The spatial spectrums imple- mented by this algorithm have the specialty of high sparse and extremely low side lobe. What's more, the prior information isn't re- quired in this algorithm. Computer simulations show that, this method improves 30% spatial resolution compared to traditional DOA algorithm, and coherent interference resistance. Bearing-time recording (BTR) results of a sea trial also demonstrate the efficiency of the algorithm.
出处
《现代雷达》
CSCD
北大核心
2018年第1期30-35,42,共7页
Modern Radar
基金
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)
关键词
波达方向估计
稀疏谱
宽带聚焦
相干干扰
direction of arrival estimation
sparse spectrum
wideband focusing
coherent interference