High-resolution DOA estimation with Meridian prior
High-resolution DOA estimation with Meridian prior
复制标题
使用子午线先验进行高分辨率 DOA 估计
DOI：
10.1186/1687-6180-2013-91
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发表时间：
2013-04
影响因子：
1.9
通讯作者：
Zicheng Liu
中科院分区：
文献类型：
--
作者：
Guanghui Zhao;Jie Lin;Fangfang Shen;Guangming Shi;Qingyu Hou;Zicheng Liu
基于空间谱中只有少量点源的假设，波达方向（DOA）估计问题可以转化为信号关于字典的稀疏表示问题。通过选择合适的字典，阵列测量可以很好地近似为字典中几个条目的线性组合，其中稀疏系数向量的非零元素对应于目标的到达方向。传统的方法是通过对信号分布施加拉普拉斯先验约束来保证信号的稀疏性。但在数据量不足或噪声环境下，会出现大量的假目标，从而影响其性能。考虑到子午线分布具有高能量集中的特点，我们提出采用子午线先验作为系数向量的先验分布。此外，我们提出了一个新的最小化问题与子午线先验假设（MMP）的DOA估计。由于Meridian先验对能量定位的约束比拉普拉斯先验更严格，因此该方法可以获得更好的DOA估计，体现在更高的分辨率和更少的假目标。仿真实验和地面真实数据处理实验均表明了该算法的上级性能。
Based on the assumption that only a few point sources exist in the spatial spectrum, the direction-of-arrival (DOA) estimation problem can be formulated as a problem of sparse representation of signal with respect to a dictionary. By choosing a proper dictionary, the array measurements can be well approximated by a linear combination of a few entries of the dictionary, in which the non-zero elements of the sparse coefficient vector correspond to the targets’ arrival direction. Conventionally, the desired sparsity of signal is guaranteed by imposing a constraint ofLaplaceprior on the distribution of signal. However, its performance is not satisfied under the condition of insufficient data or noisy environment since a lot of false targets will appear. Considering that theMeridiandistribution has the characteristic of high energy concentration, we propose to adopt the Meridian prior as the prior distribution of the coefficient vector. Further, we present a new minimization problem with the Meridian prior assumption (MMP) for DOA estimation. Because the Meridian prior imposes a more stringent constraint on the energy localization than the Laplace prior, the proposed MMP method can achieve a better DOA estimation, which is embodied in higher resolution and less false targets. The experiments of both simulation and ground truth data process exhibit the superior performance of our proposed algorithm.
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DOI：
10.1017/cbo9780511794308
发表时间：
2012
期刊：
--
影响因子：
--
作者：
Gitta Kutyniok
通讯作者：
Gitta Kutyniok
DOI：
10.1109/tsp.2002.808076
发表时间：
2003-03
期刊：
IEEE Trans. Signal Process.
影响因子：
--
作者：
B. Rao;K. Engan;S. Cotter;J. Palmer;K. Kreutz-Delgado
通讯作者：
B. Rao;K. Engan;S. Cotter;J. Palmer;K. Kreutz-Delgado
影响因子：
3.9
作者：
Chartrand, Rick
通讯作者：
Chartrand, Rick
影响因子：
5.4
作者：
Malioutov, D;Çetin, M;Willsky, AS
通讯作者：
Willsky, AS
DOI：
10.1109/jstsp.2009.2039177
发表时间：
2010-04-01
影响因子：
7.5
作者：
Carrillo, Rafael E.;Barner, Kenneth E.;Aysal, Tuncer C.
通讯作者：
Aysal, Tuncer C.