多阵列中非圆信号借助于降维搜索和子空间数据融合的直接定位算法
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南京航空航天大学电子信息工程学院,南京,211106

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国家自然科学基金(61971217,61971218,61631020)资助项目;江苏省博士后科学基金(2020Z013)资助项目;声纳技术重点实验室基金资助项目。


Direct Position Determination of Non-circular Signals with Multiple Arrays by Exploiting Reduced-Dimension Finding and Subspace Data Fusion
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College of Electronic and Information Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing, 211106, China

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    摘要:

    为了解决多阵列中子空间数据融合(Subspace data fusion, SDF)算法自由度受限于实际阵元数与定位精度低的问题,本文利用非圆(Non-circular, NC)信号特性并结合降维(Reduced-dimension, RD)搜索思想提出了一种基于降维搜索的子空间数据融合的非圆信号直接定位算法(Reduced-dimension subspace data fusion, RD-SDF)。该算法首先利用辐射源信号的NC特性扩展空间信息,以获得增大的虚拟阵列孔径,与更多的可识别信源数。但是由于NC相位导致的高维搜索大大增加了算法求解时的复杂度,本文引入RD搜索思想,通过数据重构消除NC相位导致的高维搜索复杂度问题,并结合SDF构造RD融合搜索谱函数。仿真结果表明,相比于传统SDF算法,本文RD-SDF算法具有更高的空间自由度和定位精度。此外,RD-SDF算法在保证估计性能的同时显著降低了算法复杂度。

    Abstract:

    To improve the traditional subspace data fusion (SDF) algorithm with multiple arrays in terms of degree of freedom (DOF) and accuracy, a direct position determination algorithm for non-circular (NC) signals with multiple arrays is proposed by exploiting the NC characteristics and the concept of reduced-dimension (RD). Specifically, the NC characteristics are used to obtain the extended spatial information, which contributes to the extended array aperture and enhanced DOFs. However, this leads to the expensive high-dimension search. As a result, the concept of RD is introduced to discard the NC phase and then construct the RD spectrum search function based on SDF. Compared with the traditional SDF algorithm, the superiorities of the proposed algorithm in DOF and position performance are corroborated by numerical results. Besides, without losing the estimation performance, it significantly reduces the complexity.

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张小飞,曾浩威,郑旺,李建峰.多阵列中非圆信号借助于降维搜索和子空间数据融合的直接定位算法[J].数据采集与处理,2020,35(6):1022-1032

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  • 收稿日期:2020-08-03
  • 最后修改日期:2020-10-09
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  • 在线发布日期: 2020-11-25