Adaptive beamforming technique based on compressed sensing in multi-carrier frequency MIMO HFSWR

2015 ◽  
Author(s):  
Aihua Liu Aihua Liu ◽  
Qiang Yang Qiang Yang ◽  
Weibo Deng Weibo Deng
Keyword(s):  
Compressed Sensing ◽  
Carrier Frequency ◽  
Adaptive Beamforming ◽  
Beamforming Technique

scholarly journals Adaptive Beamforming Technique for Accurate Vertical Wind Measurements with Multichannel MST Radar

2012 ◽  
Vol 29 (12) ◽  
pp. 1769-1775 ◽  
Author(s):  
Koji Nishimura ◽  
Takuji Nakamura ◽  
Toru Sato ◽  
Kaoru Sato
Keyword(s):  
Signal To Noise Ratio ◽  
Adaptive Beamforming ◽  
Vertical Wind ◽  
Constrained Minimization ◽  
Horizontal Wind ◽  
Signal To Noise ◽  
Mst Radar ◽  
Vertical Beam ◽  
Noise Ratio ◽  
Beamforming Technique

Abstract Aspect-sensitive backscattering of the atmosphere causes a small error in an effective line-of-sight direction in vertical beam observations leading to a serious degradation of vertical wind estimates due to contamination by horizontal wind components. An adaptive beamforming technique for a multichannel mesosphere–stratosphere–troposphere (MST) radar is presented, which makes it possible to measure the vertical wind velocity with higher accuracy by adaptively generating a countersteered reception beam against an off-vertically shifted echo pattern. The technique employs the norm-constrained direction-constrained minimization of power (NC-DCMP) algorithm, which provides not only robustness but also higher accuracy than the basic direction-constrained minimization of power algorithm in realistic conditions. Although the technique decreases the signal-to-noise ratio, the ratio is controlled and bound at a specified level by the norm constraint. In the case that a decrease of −3 dB is acceptable in a vertical beam observation, for which usually a much higher signal-to-noise ratio is obtained than for oblique beams, the maximum contamination is suppressed to even for the most imbalanced aspect sensitivity.

Compressed Sensing Based Blind Carrier Frequency Offset Estimation for OFDM System

2013 ◽  
Vol 756-759 ◽  
pp. 1894-1897 ◽  
Author(s):  
Gang Yang ◽  
Hua Xin Yu ◽  
Xiao Fei Zhang
Keyword(s):  
Compressed Sensing ◽  
Carrier Frequency ◽  
Orthogonal Frequency Division Multiplexing ◽  
Carrier Frequency Offset ◽  
Signal To Noise Ratio ◽  
Estimation Algorithm ◽  
Frequency Offset ◽  
Ofdm Systems ◽  
Carrier Frequency Offset Estimation ◽  
Sensing Model

In this paper, we address the problem of carrier frequency offset (CFO) estimation for Orthogonal Frequency Division Multiplexing (OFDM) systems. This paper links CFO estimation problem in OFDM systems to the compressed sensing model. Exploiting this link, it derives a compressed sensing-based CFO estimation algorithm. The proposed algorithm has better CFO estimation performance than ESPRIT method with lower signal-to-noise ratio (SNR). Simulation results illustrate performance of this algorithm.

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