Maximum likelihood bearing estimation by quasi-Newton method using a uniform linear array
Maximum likelihood bearing estimation by quasi-Newton method using a uniform linear array
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使用均匀线性阵列的拟牛顿法的最大似然方位估计
DOI：
10.1109/icassp.1991.150165
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发表时间：
1991
期刊：
影响因子：
--
通讯作者：
N. Miki
中科院分区：
文献类型：
--
作者：
Hideyuki Watanabe;Masakiyo Suzuki;N. Nagai;N. Miki
提出了一种利用均匀线阵进行窄带信号源最大似然（ML）方位估计的有效算法。该算法采用了最有效的梯度法之一的拟牛顿法。通过计算多项式的零点得到估计，多项式的系数可以通过求解ML准则所产生的非线性优化问题来给出。仿真结果表明：该方法具有比MUSIC更好的估计精度，与传统的ML交替投影（AP）方法几乎相同的精度，且计算量比AP低。<<ETX>>
An efficient algorithm for maximum likelihood (ML) bearing estimation of narrowband signal sources using a uniform linear array of sensors is proposed. This algorithm adopts the quasi-Newton method which is one of the most efficient gradient methods. The estimates are obtained by computing zeros of a polynomial whose coefficients can be given by solving the nonlinear optimization problem arising from the ML criterion. Simulations have indicated the following properties: the proposed method gives better estimation accuracy than MUSIC, gives almost the same accuracy as the conventional ML procedure alternating projection (AP), and requires lower computational cost than AP.<<ETX>>