Lang Zhou , Kun Ye , Jie Qi , Shaohua Hong , Zihao Feng
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引用次数: 0
摘要
在有限的快照和低信噪比(SNR)条件下,二维(2-D)到达方向(DOA)估计能获得更好的估计性能,这一点最近越来越受到关注。为此,我们提出了一种基于离散分数傅里叶变换和泰勒扩展近似(DFRFT-TEA)的 L 形嵌套阵列(LsNA)二维 DOA 估计算法。具体来说,首先引入离散分数傅里叶变换(DFRFT)方法生成初始估计角度,然后利用泰勒展开近似(TEA)方法补偿角度偏移以获得精细估计角度,最后通过置换矩阵实现精细估计角度的成对匹配。数值仿真结果表明,DFRFT-TEA 算法不仅在有限快照和低信噪比条件下具有良好的 DOA 估计性能,而且可适用于未确定场景下的 DOA 估计。此外,与现有算法相比,所提出的 DFRFT-TEA 算法具有更优越的估计性能。
2-D DOA estimation based on discrete fractional Fourier transform for L-shaped nested array
Yielding better estimation performance for two-dimensional (2-D) direction-of-arrival (DOA) estimation at limited snapshots and low signal-to-noise ratios (SNRs) has recently attracted increasing attention. Aiming at this, a 2-D DOA estimation algorithm based on discrete fractional Fourier transform and Taylor expansion approximation (DFRFT-TEA) for the L-shaped nested array (LsNA) is proposed. Specifically, the discrete fractional Fourier transform (DFRFT) method is first introduced to generate the initial estimated angles, then the Taylor expansion approximation (TEA) method is utilized to compensate the angular offsets to obtain the fine estimated angles, and finally the pair-matching of the fine estimated angles is achieved by the permutation matrix. The findings of the numerical simulation show that the DFRFT-TEA algorithm not only has favorable DOA estimation performance under finite snapshots and low SNRs but also can be adapted to DOA estimation for the underdetermined scenario. Furthermore, the proposed DFRFT-TEA algorithm provides superior estimation performance in comparison to the existing algorithms.
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