Open AccessDirection of Arrival Estimation in Low-Grazing Angle: A Partial Spatial-Differencing Approach
Author(s) -
Junpeng Shi,
Guoping Hu,
Xiaofei Zhang
Publication year - 2017
Publication title -
ieee access
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.587
H-Index - 127
ISSN - 2169-3536
DOI - 10.1109/access.2017.2706193
Subject(s) - aerospace , bioengineering , communication, networking and broadcast technologies , components, circuits, devices and systems , computing and processing , engineered materials, dielectrics and plasmas , engineering profession , fields, waves and electromagnetics , general topics for engineers , geoscience , nuclear engineering , photonics and electrooptics , power, energy and industry applications , robotics and control systems , signal processing and analysis , transportation
This paper addresses a partial spatial-differencing (PSD) approach for the direction of arrival estimation in a low-grazing angle (LGA) condition. By dividing the sample covariance matrix into several column subvectors, we first form the corresponding reconstructed subarray covariance matrices (RSCMs). We then calculate the spatial differencing matrix for the noise parts of RSCMs, while the non-noise parts are kept completely. That is, we build a PSD matrix. Compared with the existing spatial smoothing and full spatial-differencing methods, the PSD approach can use all the data information of the sample covariance matrix and also suppress the effect of additive white or colored noise more effectively. Simulation results show that our method provides a higher estimation accuracy and resolution than the state-of-the-art methods.
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