一种基于压缩感知的离格阵列测向方法
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南瑞集团有限公司/国网电力科学研究院有限公司,南京,211000

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A Compressed Sensing Based Off-Grid Direction-of-Arrival Estimation Method
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Nari Group Corporation/State Grid Electric Power Research Institute, Nanjing, 211000, China

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    摘要:

    基于稀疏表示的阵列测向技术中的一系列高精度鲁棒性方法都基于网格假设,即假设入射信号来向无误差地落在网格上,这一假设与现实中信号来向落在连续角度域内相违背,所造成的网格偏差效应会带来模型失配,从而导致估计性能的恶化。针对这一问题,本文提出了一种基于泰勒展开的离格类信号模型,该模型允许信号来向偏离网格,从而消除了网格误差效应,减小了估计误差。同时采用一种交替迭代优化的方法对模型进行求解,并利用奇异值分解等方法降低计算量。该方法能够有效减小网格误差,提高估计精度。仿真结果验证了所提方法的有效性。

    Abstract:

    Benefiting from the development of compressed sensing (CS) theory, sparse representation based off-grid direction-of-arrival (DOA) estimation technique has been extensively exploited, resulting in several high accuracy methods. However, most of these methods are based on the grid assumption, i.e., the DOAs of the incident signals are accurately located on the grid points, which violates the fact that the true DOAs belong to the continuous angle space. This grid bias effect may bring in model mismatch, leading to performance deterioration. In this paper, we propose an off-grid signal model based on Taylor expansion, which allows the DOAs to deviate from the grid points, so the grid bias effect can be eliminated, and the estimation accuracy can be improved. We employ an alternating iterative method to solve the problem and use the singular value decomposition to reduce the computational cost. The proposed method is able to reduce the grid bias, resulting in high estimation accuracy. Simulation results are provided to verify the effectiveness of the proposed method.

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陈俣.一种基于压缩感知的离格阵列测向方法[J].数据采集与处理,2019,34(6):1118-1124

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  • 收稿日期:2018-08-23
  • 最后修改日期:2019-01-28
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  • 在线发布日期: 2019-12-13