Shi Junpeng, Hu Guoping, Sun Fenggang, Zong Binfeng, Wang Xin
Air and Missile Defense College, Air Force Engineering University, Xi'an 710051, China.
College of Information Science and Engineering, Shandong Agricultural University, Tai'an 271018, China.
Sensors (Basel). 2017 Aug 24;17(9):1956. doi: 10.3390/s17091956.
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.
本文针对采用均匀矩形阵列(URA)的相干信号二维波达方向(2-D DOA)估计问题,提出了一种改进的空间差分(ISD)方案。我们首先将URA划分为多个行矩形子阵列。然后,通过提取每个子阵列的所有数据信息,我们仅对自相关进行差分运算,而互相关保持不变。利用重构的子矩阵,在所提出的方案下开发了前向仅ISD(FO-ISD)和前后向ISD(FB-ISD)方法。与现有的空间平滑技术相比,所提出的方案可以使用样本协方差矩阵的更多数据信息,并且还能更有效地抑制加性噪声的影响。仿真结果表明,在白噪声或有色噪声条件下,与其他方法相比,FO-ISD和FB-ISD都能在很大程度上提高估计性能。