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Improved Spatial Differencing Scheme for 2-D DOA Estimation of Coherent Signals with Uniform Rectangular Arrays

机译:具有均匀矩形阵列的相干信号的二维DOA估计的改进空间差分方案

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摘要

This paper proposes an improved spatial differencing (ISD) scheme for two-dimensional direction of arrival (2-D DOA) estimation of coherent signals with uniform rectangular arrays (URAs). We first divide the URA into a number of row rectangular subarrays. Then, by extracting all the data information of each subarray, we only perform difference-operation on the auto-correlations, while the cross-correlations are kept unchanged. Using the reconstructed submatrices, both the forward only ISD (FO-ISD) and forward backward ISD (FB-ISD) methods are developed under the proposed scheme. Compared with the existing spatial smoothing techniques, the proposed scheme can use more data information of the sample covariance matrix and also suppress the effect of additive noise more effectively. Simulation results show that both FO-ISD and FB-ISD can improve the estimation performance largely as compared to the others, in white or colored noise conditions.
机译:本文提出了一种改进的空间差分(ISD)方案,用于具有均匀矩形阵列(URA)的相干信号的二维到达方向(2-D DOA)估计。我们首先将URA分为许多行矩形子数组。然后,通过提取每个子阵列的所有数据信息,我们仅对自相关执行差分运算,而互相关保持不变。使用重构的子矩阵,在所提出的方案下开发了仅向前ISD(FO-ISD)和向前向后ISD(FB-ISD)方法。与现有的空间平滑技术相比,该方案可以利用样本协方差矩阵的更多数据信息,并且可以更有效地抑制加性噪声的影响。仿真结果表明,在白噪声或彩色噪声条件下,FO-ISD和FB-ISD均可大大提高估计性能。

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