Vertical Localization by Multipath Analysis in Artificial Human Ears for Robots

Author(s):  
Piyanat Sirisawat ◽  
Saiyan Saiyod ◽  
Woottichai Nonsakhoo
2015 ◽  
Vol 45 (10) ◽  
pp. 2660-2678 ◽  
Author(s):  
Victor I. Shrira ◽  
Philippe Forget

AbstractInertial band response of the upper ocean to changing wind is studied both theoretically and by analysis of observations in the northwestern Mediterranean. On the nontraditional f plane, because of the horizontal component of the earth’s rotation for waves of inertial band with frequencies slightly below the local inertial frequency f, there is a waveguide in the mixed layer confined from below by the pycnocline. It is argued that when the stratification is shallow these waves are most easily and strongly excited by varying winds as near-inertial oscillations (NIOs). These motions have been overlooked in previous studies because they are absent under the traditional approximation. The observations that employed buoys with thermistors, ADCPs, and two 16.3-MHz Wellen Radar (WERA) HF radars were carried out in the Gulf of Lion in April–June 2006. The observations support the theoretical picture: a pronounced inertial band response occurs only in the presence of shallow stratification and is confined to the mixed layer, and the NIO penetration below the stratified layer is weak. NIO surface magnitude and vertical localization are strongly affected by the presence of even weak density stratification in the upper 10 m. The NIO surface signatures are easily captured by HF radars. Continuous 1.8-yr HF observations near the Porquerolles Island confirm that shallow stratification is indeed the precondition for a strong NIO response. The response sensitivity to stratification provides a foundation for developing HF radar probing of stratification and, indirectly, vertical mixing, including spotting dramatic mixing events and spikes of vertical heat, mass, and momentum exchange.


2006 ◽  
Vol 77 (10) ◽  
pp. 10E918 ◽  
Author(s):  
L. Lin ◽  
E. M. Edlund ◽  
M. Porkolab ◽  
Y. Lin ◽  
S. J. Wukitch

2014 ◽  
Vol 142 (12) ◽  
pp. 4477-4483 ◽  
Author(s):  
Lili Lei ◽  
Jeffrey L. Anderson

Abstract To investigate the impacts of frequently assimilating only surface pressure (PS) observations, the Data Assimilation Research Testbed and the Community Atmosphere Model (DART/CAM) are used for observing system simulation experiments with the ensemble Kalman filter. An empirical localization function (ELF) is used to effectively spread the information from PS in the vertical. The ELF minimizes the root-mean-square difference between the truth and the posterior ensemble mean for state variables. The temporal frequency of the observations is increased from 6 to 3 h, and then 1 h. By observing only PS, the uncertainty throughout the entire depth of the troposphere can be constrained. The analysis error over the entire depth of the troposphere, especially the middle troposphere, is reduced with increased assimilation frequency. The ELF is similar to the vertical localization function used in the Twentieth-Century Reanalysis (20CR); thus, it demonstrates that the current vertical localization in the 20CR is close to the optimal localization function.


2010 ◽  
Vol 138 (10) ◽  
pp. 3946-3966 ◽  
Author(s):  
Jean-François Caron ◽  
Luc Fillion

Abstract This study examines the modification to the balance properties of the analysis increments in a global three-dimensional variational data assimilation scheme when using flow-dependent background-error covariances derived from an operational ensemble Kalman filter instead of static homogenous and isotropic background-error covariances based on lagged forecast differences. It is shown that the degree of balance in the analysis increments is degraded when the former method is used. This change can be attributed in part to the reduced degree of rotational balance found in short-term ensemble Kalman filter perturbations as compared to lagged forecast differences based on longer-range forecasts. However, the use of a horizontal and vertical localization technique to increase the rank of the ensemble-based covariances are found to have a significant deleterious effect on the rotational balance with the largest detrimental impact coming from the vertical localization and affecting particularly the upper levels. The examination of the vertical motion part of the analysis increments revealed that the spatial covariance localization technique also produces unrealistic vertical structure of vertical motion increments with abnormally large increments near the surface. A comparison between the analysis increments from the ensemble Kalman filter and from the ensemble-based three-dimensional variational data assimilation (3D-Var) scheme showed that the balance characteristics of the analysis increments resulting from the two systems are very similar.


1989 ◽  
Vol 67 (8) ◽  
pp. 1955-1959 ◽  
Author(s):  
B. J. Frost ◽  
P. J. Baldwin ◽  
M. Csizy

Although there are several anecdotal reports in the literature that northern saw-whet owls (Aegolius acadicus) have extremely accurate auditory localization abilities, there have been no attempts to quantify these observations. In this study we used the search coil technique to obtain precise measurements of the northern saw-whet owl's head orientation toward either cricket chirps or mouse squeaks presented through speakers at various azimuthal positions. The results indicate owls of this species can orient their heads toward sound sources with great accuracy in the azimuthal plane, yielding mean errors of <1.0°, but show a slight tendency to undershoot more peripherally located sounds. Vertical localization is somewhat less precise, but still very accurate. Subsequent studies will be aimed at elucidating the physiological and anatomical substrates of this extreme accuracy in auditory localization ability.


2015 ◽  
Vol 143 (9) ◽  
pp. 3664-3679 ◽  
Author(s):  
Lili Lei ◽  
Jeffrey L. Anderson ◽  
Glen S. Romine

Abstract For ensemble-based data assimilation, localization is used to limit the impact of observations on physically distant state variables to reduce spurious error correlations caused by limited ensemble size. Traditionally, the localization value applied is spatially homogeneous. Yet there are potentially larger errors and different covariance length scales in precipitation systems, and that may justify the use of different localization functions for precipitating and nonprecipitating regions. Here this is examined using empirical localization functions (ELFs). Using output from an ensemble observing system simulation experiment (OSSE), ELFs provide estimates of horizontal and vertical localization for different observation types in regions with and without precipitation. For temperature and u- and υ-wind observations, the ELFs for precipitating regions are shown to have smaller horizontal localization scales than for nonprecipitating regions. However, the ELFs for precipitating regions generally have larger vertical localization scales than for nonprecipitating regions. The ELFs are smoothed and then applied in three additional OSSEs. Spatially homogeneous ELFs are found to improve performance relative to a commonly used localization function with compact support. When different ELFs are applied in precipitating and nonprecipitating regions, performance is further improved, but varying ELFs by observation type was not found to be as important. Imbalance in initial states caused by use of different localization functions is diagnosed by the domain-averaged surface pressure tendency. Forecasts from analyses with ELFs have smaller surface pressure tendencies than the standard localization, indicating improved initial balance with ELFs.


2016 ◽  
Vol 144 (8) ◽  
pp. 2889-2913 ◽  
Author(s):  
Stacey M. Hitchcock ◽  
Michael C. Coniglio ◽  
Kent H. Knopfmeier

Abstract This study examines the impact of assimilating three radiosonde profiles obtained from ground-based mobile systems during the Mesoscale Predictability Experiment (MPEX) on analyses and convection-permitting model forecasts of the 31 May 2013 convective event over Oklahoma. These radiosonde profiles (in addition to standard observations) are assimilated into a 36-member mesoscale ensemble using an ensemble Kalman filter (EnKF) before embedding a convection-permitting (3 km) grid and running a full ensemble of 9-h forecasts. This set of 3-km forecasts is compared to a control run that does not assimilate the MPEX soundings. The analysis of low- to midlevel moisture is impacted the most by the assimilation, but coherent mesoscale differences in temperature and wind are also seen, primarily downstream of the location of the soundings. The ensemble of forecasts of convection on the 3-km grid are improved the most in the first three hours of the forecast in a region where the analyzed position of low-level frontal convergence and midlevel moisture was improved on the mesoscale grid. Later forecasts of the upscale growth of intense convection over central Oklahoma are improved somewhat, but larger ensemble spread lowers confidence in the significance of the improvements. Changes in the horizontal localization radius from the standard value applied to the MPEX sounding assimilation alters the specific times that the forecasts are improved in the first three hours of the forecasts, while changes to the vertical localization radius and specified temperature and wind observation error result in little to no improvements in the forecasts.


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