Qi Song;Feng-Gang Yan;Xiang-Tian Meng;Bing-Xia Cao;Ming Jin
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引用次数: 0
摘要
在本文中,我们利用原始噪声子空间及其共轭重构了一种新的估计器,用于快速联合估计部分校准阵列(PCA)中的 DOA 和子阵间误差,即快速rank-reduce(F-RARE)。基于新的估计器,只需搜索总视场角的一半,就能获得真实 DOA 估计及其虚拟镜像的集合。然后,就可以利用传统波束成形(CBF)技术选择真正的 DOA 估计值。此外,子阵列间误差也可以通过有限数量的子空间分解来计算。数值模拟表明,与传统的 RARE 算法相比,新方法不仅能减少一半的计算负担,还能提供类似的估计精度。
Fast joint DOA and inter-subarray errors estimation in partly calibrated arrays
In this paper, we utilize the original noise subspace and its conjugate to reconstruct a new estimator for the fast joint estimation of DOA and inter-subarray errors in the partly calibrated arrays (PCA), namely fast-rank-reduce (F-RARE). Based on the new estimator, the collection of true DOA estimation and its virtual mirror can be obtained by searching over only half of the total angular field-of-view. Then, the true DOA estimation can be selected by using the conventional beamforming (CBF) technique. Additionally, the inter-subarray errors can also be computed by a finite number of subspace decompositions. Numerical simulation illustrates that compared with the conventional RARE algorithm, the new method can not only reduce the computational burden by a half but also provide a similar estimation accuracy.
期刊介绍:
Radio Science (RDS) publishes original scientific contributions on radio-frequency electromagnetic-propagation and its applications. Contributions covering measurement, modelling, prediction and forecasting techniques pertinent to fields and waves - including antennas, signals and systems, the terrestrial and space environment and radio propagation problems in radio astronomy - are welcome. Contributions may address propagation through, interaction with, and remote sensing of structures, geophysical media, plasmas, and materials, as well as the application of radio frequency electromagnetic techniques to remote sensing of the Earth and other bodies in the solar system.