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.

scholarly journals DOA Estimation for UCAs Based on Virtual Subarray Beamforming Technique

2018 ◽  
Vol 232 ◽  
pp. 01012
Author(s):  
Bo Xu ◽  
Zhigang Huang
Keyword(s):  
Signal To Noise Ratio ◽  
Estimation Method ◽  
Direction Of Arrival ◽  
Doa Estimation ◽  
Signal To Noise ◽  
Circular Arrays ◽  
Noise Ratio ◽  
Subarray Beamforming ◽  
Beamforming Technique

Direction-of-arrival (DOA) estimation is always a hotspot research in the fields of radar, sonar, communication and so on. And uniform circular arrays (UCAs) are more attractive in the context of DOA estimation since their symmetrical structures have potential to provide two directions coverage. This paper proposed a new DOA estimation method for UCAs via virtual subarray beamforming technique. The method would provide an acceptable DOA estimate even if the number of sources is great than the number of array elements. Also, the performance of the proposed method would hold good when the snapshot length or the signal-to-noise ratio (SNR) is small. Simulations show that the proposed technique offers significantly improved estimation resolution, capacity, and accuracy relative to the existing techniques.

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
Keyword(s):  
Background Noise ◽  
Signal To Noise Ratio ◽  
Background Correction ◽  
Data Availability ◽  
Horizontal Wind ◽  
Limiting Factor ◽  
High Temporal Resolution ◽  
Signal To Noise ◽  
Uncertainty Estimates ◽  
Noise Ratio

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.

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

2016 ◽  
Vol 9 (2) ◽  
pp. 817-827 ◽  
Author(s):  
Antti J. Manninen ◽  
Ewan J. O'Connor ◽  
Ville Vakkari ◽  
Tuukka Petäjä
Keyword(s):  
Background Noise ◽  
Signal To Noise Ratio ◽  
Background Correction ◽  
Data Availability ◽  
Horizontal Wind ◽  
Limiting Factor ◽  
High Temporal Resolution ◽  
Signal To Noise ◽  
Uncertainty Estimates ◽  
Noise Ratio

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.

scholarly journals ANALYSIS OF METHODS USING FOR SUPERRESOLUTION OF THE SIGNALS IN THE TASKS OF SPACE-TIME ACCESS

2016 ◽  
Vol 5 ◽  
pp. 16-24
Author(s):  
Mykola Moskalets ◽  
Svitlana Teplytska
Keyword(s):  
Signal To Noise Ratio ◽  
Adaptive Beamforming ◽  
Space Time ◽  
Signal Interference ◽  
Maximal Entropy ◽  
Comparative Characteristic ◽  
Signal To Noise ◽  
Multiple Signal Classification ◽  
Noise Ratio ◽  
Statistical Consistency

Six methods are considered in the analysis of the methods of angular superresolution of the signals: non-adaptive beamforming, Kapon, thermal noise, Bordzhotti-Lagunas, maximal entropy and multiple signal classification (MUSIC). The comparative characteristic of the methods with assessing their advantages disadvantages and limitations is given. Theoretical resolution of these methods is assessed in the article. Numerical evaluation of resolution ability of the methods of angular superresolution of the signal are obtained based on the simulation of various scenarios of signal-to-noise ratio, taking into account the use of correlated and uncorrelated signals, a different number of antenna elements and the values of the signal / interference + noise ratio. These estimations show the ultimate theoretical accuracy of the methods and the potential for their use in problems of space-time access with set limits. The simulation results confirmed the statistical consistency of these methods of estimation of arrival direction angles of correlated and uncorrelated signals from subscriber stations for the space-time sampling in the output of the linear equidistant antenna array. The present analysis and research results make it possible to select the most effective method for determining the arrival of signals in accordance with the given parameters of signal-to-noise ratio under restrictions.

Determination of the Best Emulsion for the Microscopy of Crystals

1981 ◽  
Vol 39 ◽  
pp. 32-33
Author(s):  
David A. Grano ◽  
Kenneth H. Downing
Keyword(s):  
Spatial Frequency ◽  
Information Transfer ◽  
Signal To Noise Ratio ◽  
Experimental Situation ◽  
Photographic Emulsion ◽  
Modulation Transfer ◽  
Signal To Noise ◽  
Frequency Space ◽  
Noise Ratio

The retrieval of high-resolution information from images of biological crystals depends, in part, on the use of the correct photographic emulsion. We have been investigating the information transfer properties of twelve emulsions with a view toward 1) characterizing the emulsions by a few, measurable quantities, and 2) identifying the “best” emulsion of those we have studied for use in any given experimental situation. Because our interests lie in the examination of crystalline specimens, we've chosen to evaluate an emulsion's signal-to-noise ratio (SNR) as a function of spatial frequency and use this as our critereon for determining the best emulsion.The signal-to-noise ratio in frequency space depends on several factors. First, the signal depends on the speed of the emulsion and its modulation transfer function (MTF). By procedures outlined in, MTF's have been found for all the emulsions tested and can be fit by an analytic expression 1/(1+(S/S0)2). Figure 1 shows the experimental data and fitted curve for an emulsion with a better than average MTF. A single parameter, the spatial frequency at which the transfer falls to 50% (S0), characterizes this curve.

Experiments in Bright-Field Imaging with Hollow-Cone Illumination

1981 ◽  
Vol 39 ◽  
pp. 226-227
Author(s):  
W. Kunath ◽  
K. Weiss ◽  
E. Zeitler
Keyword(s):  
Signal To Noise Ratio ◽  
Carbon Support ◽  
Electronic System ◽  
Optic Axis ◽  
Hollow Cone ◽  
Signal To Noise ◽  
Bright Field ◽  
Noise Ratio ◽  
Single Field ◽  
Field Imaging

Bright-field images taken with axial illumination show spurious high contrast patterns which obscure details smaller than 15 ° Hollow-cone illumination (HCI), however, reduces this disturbing granulation by statistical superposition and thus improves the signal-to-noise ratio. In this presentation we report on experiments aimed at selecting the proper amount of tilt and defocus for improvement of the signal-to-noise ratio by means of direct observation of the electron images on a TV monitor.Hollow-cone illumination is implemented in our microscope (single field condenser objective, Cs = .5 mm) by an electronic system which rotates the tilted beam about the optic axis. At low rates of revolution (one turn per second or so) a circular motion of the usual granulation in the image of a carbon support film can be observed on the TV monitor. The size of the granular structures and the radius of their orbits depend on both the conical tilt and defocus.

Information capacity and bandwidth limitations in the SEM

1989 ◽  
Vol 47 ◽  
pp. 84-85
Author(s):  
D. C. Joy ◽  
R. D. Bunn
Keyword(s):  
Signal To Noise Ratio ◽  
Critical Dimension ◽  
Information Capacity ◽  
Acquisition Time ◽  
Signal To Noise ◽  
Sem Image ◽  
Probe Size ◽  
Minimum Number ◽  
Noise Ratio ◽  
Signal Channel

The information available from an SEM image is limited both by the inherent signal to noise ratio that characterizes the image and as a result of the transformations that it may undergo as it is passed through the amplifying circuits of the instrument. In applications such as Critical Dimension Metrology it is necessary to be able to quantify these limitations in order to be able to assess the likely precision of any measurement made with the microscope.The information capacity of an SEM signal, defined as the minimum number of bits needed to encode the output signal, depends on the signal to noise ratio of the image - which in turn depends on the probe size and source brightness and acquisition time per pixel - and on the efficiency of the specimen in producing the signal that is being observed. A detailed analysis of the secondary electron case shows that the information capacity C (bits/pixel) of the SEM signal channel could be written as :

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