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首页> 外文期刊>The Journal of Engineering >DOA estimation with extended sparse and parametric approach in multi-carrier MIMO HFSWR
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DOA estimation with extended sparse and parametric approach in multi-carrier MIMO HFSWR

机译:多载体MIMO HFSWR中扩展稀疏和参数方法的DOA估计

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摘要

y To obtain a higher angle resolution of multiple-in multiple-out high-frequency surface wave radar (MIMO HFSWR) for direction of arrival (DOA) estimation with a limited number of antenna sensors, multiple working frequencies are proposed to enlarge the aperture of the virtual array of the MIMO HFSWR. The scenario that all targets have the identical reflection at all working frequencies is studied, which permits the abstraction of a virtual received data vector by using all frequencies. This virtual data vector can be taken as the measurement of a virtual non-uniform linear array (VNLA) with a single reference working frequency. To extend the sparse and parametric approach (SPA) to the VNLA for DOA estimation, the manifold separation technique is utilised to decompose the array steering vector of the VNLA into two different parts, one is a characteristic matrix that is related to the array itself. The other is a Vandermonde vector that contains the DOAs of the targets. Then the authors use the Vandermonde structure to develop a SPA-liked method for the DOA estimation. Simulation results are provided to confirm the validity of the proposed method.
机译:为了获得具有有限数量的天线传感器的到达方向(DOA)估计的更高角度分辨率,以有限的天线传感器,提出了多个工作频率来扩大孔径MIMO HFSWR的虚拟阵列。所有目标在所有工作频率上具有相同反射的场景,这允许通过使用所有频率来抽象虚拟接收的数据矢量。该虚拟数据矢量可以用单个参考工作频率作为测量虚拟非均匀线性阵列(VNLA)。为了将稀疏和参数方法(SPA)扩展到DOA估计的VNLA,利用歧管分离技术将VNLA的阵列转向向量分解为两个不同的部件,是与阵列本身有关的特征矩阵。另一个是包含目标的DOA的Vandermonde载体。然后作者使用Vandermonde结构开发用于DOA估计的SPA喜好的方法。提供了仿真结果以确认所提出的方法的有效性。

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