Use of the LMS adaptive signal processing technique to improve signal data rates from practical oil well logging equipment

1998 ◽  
Author(s):  
R.S. Sherratt
Keyword(s):  
Signal Processing ◽  
Well Logging ◽  
Adaptive Signal Processing ◽  
Processing Technique ◽  
Oil Well ◽  
Signal Processing Technique ◽  
Data Rates ◽  
Adaptive Signal

scholarly journals Meteor Trail Echo Rejection in Atmospheric Phased Array Radars Using Adaptive Sidelobe Cancellation

2014 ◽  
Vol 31 (12) ◽  
pp. 2749-2757 ◽  
Author(s):  
Taishi Hashimoto ◽  
Koji Nishimura ◽  
Masaki Tsutsumi ◽  
Toru Sato
Keyword(s):  
Wind Velocity ◽  
Signal To Noise Ratio ◽  
Adaptive Signal Processing ◽  
Processing Technique ◽  
Signal Processing Technique ◽  
Actual Observation ◽  
Severe Reduction ◽  
Meteor Trail ◽  
The Cost ◽  
Adaptive Signal

Abstract Strong meteor trail echoes are interferences in the wind velocity estimates made from mesosphere radar observations. Contaminated spectra are detected by their discontinuity and are removed at the risk of greater fluctuations of spectra, leading to a severe reduction of the signal-to-noise ratio (SNR) and inaccurate wind estimates for weak atmospheric echoes. This paper presents an adaptive signal processing technique for the suppression of spectral contaminations by meteor trail echoes. The method is based on the norm-constrained and directionally constrained minimization of power (NC-DCMP), which balances the capability of canceling the clutter and the robustness of beam shaping, at the cost of a slight decrease in the SNR, which can be determined in advance. Simulation results show that with a 3-dB decrease of the SNR being allowed, the method improves the signal-to-interference ratio (SIR) by 15 dB, giving wind estimates that are about 8 m s−1 better in terms of root-mean-square error and providing 4 times as wide an observable range when compared with the results of the ordinary nonadaptive beamforming method. The results for an actual observation show that the improvement of both the SIR and the observable range are achieved as in the simulations, which implies that the method should provide the simulated accuracy for the estimation of wind velocity from actual observations.

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