Direct Position Determination of Noncircular Sources with Multiple Nested Arrays: Reduced Dimension Subspace Data Fusion

Yang Qian, Dalin Zhao, Haowei Zeng
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引用次数: 8

Abstract

Direct position determination (DPD) of noncircular (NC) sources with multiple nested arrays (NA) is investigated in this paper. Noncircular sources are used to expand the dimension of the received signal matrix, so the number of identifiable information sources and the accuracy of direct position determination are improved. Furthermore, nested array increases spatial degree of freedom. In this paper, the high-dimensional search problem of noncircular sources is investigated. Therefore, we propose algorithm dimension reduction subspace data fusion (RD-SDF) to reduce complexity and increase positioning accuracy. Simulation results show that the proposed RD-SDF algorithm for multiple nested arrays with noncircular sources has improved positioning accuracy with higher spatial degree of freedom than SDF, Capon, and two-step algorithms with uniform linear array and circular sources (CS).
多嵌套阵列非圆源的直接位置确定:降维子空间数据融合
研究了具有多个嵌套阵列的非圆源的直接定位问题。采用非圆源扩展接收信号矩阵的维数,提高了可识别信息源的数量和直接定位的精度。此外,嵌套数组增加了空间自由度。本文研究了非圆源的高维搜索问题。为此,我们提出了降维子空间数据融合算法(RD-SDF)来降低复杂性和提高定位精度。仿真结果表明,针对非圆源多嵌套阵列,本文提出的RD-SDF算法比均匀线阵和圆源的SDF、Capon和两步算法具有更高的空间自由度,提高了定位精度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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