scholarly journals A generalised background correction algorithm for a Halo Doppler lidar and its application to data from Finland

2015 ◽  
Vol 8 (10) ◽  
pp. 11139-11170
Author(s):  
A. J. Manninen ◽  
E. J. O'Connor ◽  
V. Vakkari ◽  
T. Petäjä

Abstract. Current commercially available Doppler lidars provide an economical and robust solution for measuring vertical and horizontal wind velocities, together with the ability to provide co- and cross-polarised backscatter profiles. The high temporal resolution of these instruments allow turbulent properties to be obtained from studying the variation in velocities. However, the instrument specifications mean that certain characteristics, especially the background noise behaviour, become a limiting factor for the instrument sensitivity in regions where the aerosol load is low. Turbulent calculations require an accurate estimate of the contribution from velocity uncertainty estimates, which are directly related to the signal-to-noise ratio. Any bias in the signal-to-noise ratio will propagate through as a bias in turbulent properties. In this paper we present a method to correct for artefacts in the background noise behaviour of commercially available Doppler lidars and reduce the signal-to-noise ratio threshold used to discriminate between noise, and cloud or aerosol signals. We show that, for Doppler lidars operating continuously at a number of locations in Finland, the data availability can be increased by as much as 50 % after performing this background correction and subsequent reduction in the threshold. The reduction in bias also greatly improves subsequent calculations of turbulent properties in weak signal regimes.

2016 ◽  
Vol 9 (2) ◽  
pp. 817-827 ◽  
Author(s):  
Antti J. Manninen ◽  
Ewan J. O'Connor ◽  
Ville Vakkari ◽  
Tuukka Petäjä

Abstract. Current commercially available Doppler lidars provide an economical and robust solution for measuring vertical and horizontal wind velocities, together with the ability to provide co- and cross-polarised backscatter profiles. The high temporal resolution of these instruments allows turbulent properties to be obtained from studying the variation in radial velocities. However, the instrument specifications mean that certain characteristics, especially the background noise behaviour, become a limiting factor for the instrument sensitivity in regions where the aerosol load is low. Turbulent calculations require an accurate estimate of the contribution from velocity uncertainty estimates, which are directly related to the signal-to-noise ratio. Any bias in the signal-to-noise ratio will propagate through as a bias in turbulent properties. In this paper we present a method to correct for artefacts in the background noise behaviour of commercially available Doppler lidars and reduce the signal-to-noise ratio threshold used to discriminate between noise, and cloud or aerosol signals. We show that, for Doppler lidars operating continuously at a number of locations in Finland, the data availability can be increased by as much as 50 % after performing this background correction and subsequent reduction in the threshold. The reduction in bias also greatly improves subsequent calculations of turbulent properties in weak signal regimes.


2012 ◽  
Vol 29 (12) ◽  
pp. 1769-1775 ◽  
Author(s):  
Koji Nishimura ◽  
Takuji Nakamura ◽  
Toru Sato ◽  
Kaoru Sato

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.


2019 ◽  
Vol 12 (2) ◽  
pp. 839-852 ◽  
Author(s):  
Ville Vakkari ◽  
Antti J. Manninen ◽  
Ewan J. O'Connor ◽  
Jan H. Schween ◽  
Pieter G. van Zyl ◽  
...  

Abstract. Commercially available Doppler lidars have now been proven to be efficient tools for studying winds and turbulence in the planetary boundary layer. However, in many cases low signal-to-noise ratio is still a limiting factor for utilising measurements by these devices. Here, we present a novel post-processing algorithm for Halo Stream Line Doppler lidars, which enables an improvement in sensitivity of a factor of 5 or more. This algorithm is based on improving the accuracy of the instrumental noise floor and it enables longer integration times or averaging of high temporal resolution data to be used to obtain signals down to −32 dB. While this algorithm does not affect the measured radial velocity, it improves the accuracy of radial velocity uncertainty estimates and consequently the accuracy of retrieved turbulent properties. Field measurements using three different Halo Doppler lidars deployed in Finland, Greece and South Africa demonstrate how the new post-processing algorithm increases data availability for turbulent retrievals in the planetary boundary layer, improves detection of high-altitude cirrus clouds and enables the observation of elevated aerosol layers.


2012 ◽  
Vol 126 (10) ◽  
pp. 1010-1015 ◽  
Author(s):  
V Possamai ◽  
G Kirk ◽  
A Scott ◽  
D Skinner

AbstractObjectives:To assess the feasibility of designing and implementing a speech in noise test in children before and after grommet insertion, and to analyse the results of such a test in a small group of children.Methods:Twelve children aged six to nine years who were scheduled to undergo grommet insertion were identified. They underwent speech in noise testing before and after grommet insertion. This testing used Arthur Boothroyd word lists read at 60 dB in four listening conditions presented in a sound field: firstly in quiet conditions, then in signal to noise ratios of +10 (50 dB background noise), 0 (60 dB) and −10 (70 dB).Results:Mean phoneme scores were: in quiet conditions, 28.1 pre- and 30 post-operatively (p = 0.04); in 50 dB background noise (signal to noise ratio +10), 24.2 pre- and 29 post-operatively (p < 0.01); in 60 dB background noise (signal to noise ratio 0), 22.6 pre- and 27.5 post-operatively (p = 0.06); and in 70 dB background noise (signal to noise ratio −10), 13.9 pre- and 21 post-operatively (p = 0.05).Conclusion:This small study suggests that speech in noise testing is feasible in this scenario. Our small group of children demonstrated a significant improvement in speech in noise scores following grommet insertion. This is likely to translate into a significant advantage in the educational environment.


2019 ◽  
Vol 64 (4) ◽  
pp. 471-480 ◽  
Author(s):  
Jan Osmers ◽  
Michael Sorg ◽  
Andreas Fischer

Abstract Motivation Glaucoma is currently the most common irreversible cause of blindness worldwide. A significant risk factor is an individually increased intraocular pressure (IOP). A precise measurement method is needed to determine the IOP in order to support the diagnosis of the disease and to monitor the outcome of the IOP reduction as a medical intervention. A handheld device is under development with which the patient can perform self-measurements outside the clinical environment. Method For the measurement principle of the self-tonometer the eye is acoustically excited to oscillate, which is analyzed and attributed to the present IOP. In order to detect the corneal oscillation, an optical sensor is required which meets the demands of a compact, battery driven self-tonometer. A combination of an infrared diode and a phototransistor provides a high-resolution measurement of the corneal oscillation in the range of 10 μm–150 μm, which is compared to a reference sensor in the context of this study. By means of an angular arrangement of the emitter and the detector, the degree of reflected radiation of the cornea can be increased, allowing a measurement with a high signal-to-noise ratio. Results By adjusting the angle of incidence between the detector and the emitter, the signal-to-noise ratio was improved by 40 dB which now allows reasonable measurements of the corneal oscillation. For low amplitudes (10 μm) the signal-to-noise ratio is 10% higher than that of the commercial reference sensor. On the basis of amplitude variations at different IOP levels, the estimated standard uncertainty amounts to <0.5 mm Hg in the physiological pressure range with the proposed measuring approach. Conclusion With a compact and cost-effective approach, that suits the requirements for a handheld self-tonometer, the corneal oscillation can be detected with high temporal resolution. The cross-sensitivity of the sensor concept concerning a distance variation can be reduced by adding a distance sensor. Existing systematic influences of corneal biomechanics will be integrated in the sensor concept as a consecutive step.


Sensors ◽  
2019 ◽  
Vol 19 (19) ◽  
pp. 4076
Author(s):  
Yang ◽  
Zhu ◽  
Wang ◽  
Yang ◽  
Wu ◽  
...  

Raman spectroscopy visualization is a challenging task due to the interference of complex background noise and the number of selected measurement points. In this paper, a super-resolution image reconstruction algorithm for Raman spectroscopy is studied to convert raw Raman data into pseudo-color super-resolution imaging. Firstly, the Raman spectrum data of a single measurement point is measured multiple times to calculate the mean value to remove the random background noise, and innovatively introduce the Retinex algorithm and the median filtering algorithm which improve the signal-to-noise ratio. The novel method of using deep neural network performs a super-resolution reconstruction operation on the gray image. An adaptive guided filter that automatically adjusts the filter radius and penalty factor is proposed to highlight the contour of the cell, and the super-resolution reconstruction of the pseudo-color image of the Raman spectrum is realized. The average signal-to-noise ratio of the reconstructed pseudo-color image sub-band reaches 14.29 db, and the average value of information entropy reaches 4.30 db. The results show that the Raman-based cell pseudo-color image super-resolution reconstruction algorithm is an effective tool to effectively remove noise and high-resolution visualization. The contrast experiments show that the pseudo-color image Kullback–Leiber (KL) entropy of the color image obtained by the method is small, the boundary is obvious, and the noise is small, which provide technical support for the development of sophisticated single-cell imaging Raman spectroscopy instruments.


1994 ◽  
Vol 38 ◽  
pp. 691-698
Author(s):  
K. Kansai ◽  
K. Toda ◽  
H. Kohno ◽  
T. Arai ◽  
R. Wilson

Advancements in trace clement analysis require improvements in both the signal-to-noise ratio and accurate background correction. With a sequential spectrometer, one can obtain detection limits of around 0.1 ppm for medium to heavy Z elements. Conditions can be individually optimized for each element, for example, selection of filters, collimators, crystals and background subtraction. The disadvantage is that the analysis time may become “long” if many elements are to be analyzed. This long exposure time can lead to the deterioration of some samples.


2018 ◽  
Vol 66 (2) ◽  
pp. 131-141 ◽  
Author(s):  
Wongyu Choi ◽  
Michael B. Pate ◽  
James F. Sweeney

2009 ◽  
Vol 20 (01) ◽  
pp. 028-039 ◽  
Author(s):  
Elizabeth M. Adams ◽  
Robert E. Moore

Purpose: To study the effect of noise on speech rate judgment and signal-to-noise ratio threshold (SNR50) at different speech rates (slow, preferred, and fast). Research Design: Speech rate judgment and SNR50 tasks were completed in a normal-hearing condition and a simulated hearing-loss condition. Study Sample: Twenty-four female and six male young, normal-hearing participants. Results: Speech rate judgment was not affected by background noise regardless of hearing condition. Results of the SNR50 task indicated that, as speech rate increased, performance decreased for both hearing conditions. There was a moderate correlation between speech rate judgment and SNR50 with the various speech rates, such that as judgment of speech rate increased from too slow to too fast, performance deteriorated. Conclusions: These findings can be used to support the need for counseling patients and their families about the potential advantages to using average speech rates or rates that are slightly slowed while conversing in the presence of background noise.


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