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Pulse-Compression Signal Propagation and Parameter Estimation in the Troposphere With Parabolic Equation

Authors :
Dongmin Zhang
Cheng Liao
Ju Feng
Xiaochuan Deng
Source :
IEEE Access, Vol 7, Pp 99917-99927 (2019)
Publication Year :
2019
Publisher :
IEEE, 2019.

Abstract

Wireless channel analysis is essential in the design, performance evaluation, and error correction of radar system. In this paper, an efficient parabolic equation (PE) method, which employs the split-step Fourier transform (SSFT) solution and Fourier synthesis technique, is developed for the propagation and parameter estimation of pulse-compression signals in the troposphere considering anomalous propagation conditions. A sliding window method is applied to reduce computational loads for long-distance propagation in time-domain PE. The signal delay is obtained via searching the peak of the correlation function of the received signal and a known reference signal according to the autocorrelation of the signals. The numerical examples indicate that the presented method is well suited for pulse-compression signals. Beyond that, a multiple signal classification (MUSIC) algorithm with spatial smoothing technique is introduced to obtain the signal direction of arrival (DOA) in PE model, where the covariance matrix is constructed via the array fields obtained from PE and the curvature of wavefronts due to the atmospheric refraction is considered in the array steering vector. The numerical examples verify the accuracy of the presented method. The simulation experiments in a typical sea-to-land scenario are presented to analyze the sensitivity of pulse-compression signals to evaporation ducts, including pulse waveform, time delay, and DOA, utilizing the presented methods.

Details

Language :
English
ISSN :
21693536
Volume :
7
Database :
Directory of Open Access Journals
Journal :
IEEE Access
Publication Type :
Academic Journal
Accession number :
edsdoj.74d557bd6dcf4cc8bde4eba3705342d0
Document Type :
article
Full Text :
https://doi.org/10.1109/ACCESS.2019.2929003