摘要
根据水下目标在其到达方位(DOA)搜索空间的稀疏性,采用稀疏分解理论实现了小样本、低信噪比条件下的声矢量阵DOA估计。通过分析,构造出基于声矢量阵阵列流型形式的过完备原子库,并采用正交匹配追踪算法得到目标的DOA估计。通过仿真,基于稀疏分解的声矢量阵DOA估计算法对单快拍数据进行处理,即可得到比较准确的DOA估计结果。对湖试数据进行了处理,验证了算法的有效性和优越性。
According to sparsity of direction of arrival （ DOA ） of underwater target in its search space, DOA estimation based on acoustic vector array is realized using sparse decomposition theory in small samples and low SNR case. Over-complete atomic library based on acoustic vector array array flow pattern form is constructed, and DOA estimation of target is obtained using orthogonal matching pursuit（OMP） algorithm. The simulation results show that through processing single snapshot data based on sparse decomposition DOA estimation algorithm based on acoustic vector array, more precise DOA estimation results can be obtained. Through data processing on lake experiment, the validity and superiority of algorithm is verified.
出处
《传感器与微系统》
CSCD
北大核心
2013年第3期33-36,共4页
Transducer and Microsystem Technologies
基金
中央高校基本科研业务费资助项目(HEUCF110502)
关键词
到达方位
声矢量阵
正交匹配追踪
小样本
direction of arrival（DOA）
acoustic vector array
orthogonal matching pursuit（OMP）
small sam-ple
