Engineering topics

Baumann, W. T.

Publications and source records attributed to Baumann, W. T..

3 records

NASA NTRS1993

Nonlinear effects of a modal domain optical fiber sensor in a vibration suppression control loop for a flexible structure

Recently, a modal domain optical fiber sensor has been demonstrated as a sensor in a control system for vibration suppression of a flexible cantilevered beam. This sensor responds to strain through a mechanical attachment to the structure. Because this sensor is of the interferometric type, the output of the sensor has a sinusoidal nonlinearity. For small levels of strain, the sensor can be operated in its linear region. For large levels of strain, the detection electronics can be configured to count fringes. In both of these configurations, the sensor nonlinearity imposes some restrictions on the performance of the control system. In this paper we investigate the effects of these sensor nonlinearities on the control system, and identify the region of linear operation in terms of the optical fiber sensor parameters.

Lindner, D. K.↗

NASA NTRS1984

Atmospheric frontal zone studies

The research supported by this contract and directed Activities in the inversion and interpretation of data produced by the Nimbus-7 scanning multichannel microwave radiometer (SMMR) are reported. There were five principal subjects: (1) modeling of the emissivity of foam patches on the ocean surface; (2) inversion of radiometric data by a multidimensional algorithm; (3) an operational water vapor retrieval algorithm; (4) inference of Antarctic firm accumulation rates; and (5) inference of water vapor over the Arctic sea ice.

Staelin, D. H.↗

NASA NTRS1980

Inversion of multiwavelength radiometer measurements by three-dimensional filtering

Remote sensing data from satellites typically have three dimensions: scan position, spacecraft position, and wavelength. Inversion of the radiometric data to infer geophysical parameters is a filtering problem in which the dimension of wavelength (or channel number) is transformed into a dimension of geophysical parameters, and the most general solution is a three-dimensional filter. Linear filters have the advantages of computational speed and easily described transfer functions; but often the measurements are nonlinear functions of the parameters to be inferred. To the extent that the nonlinear inversion problem is overdetermined, it can be modeled by a critically determined linear problem. As an example, inversion of Scanning Multichannel Microwave Radiometer (SMMR) data by means of a three-dimensional Wiener Filter is described. Atmospheric water vapor content, rain liquid water content, surface wind speed and surface temperature are the parameters inferred from the measurements. Nonprecipitating liquid water and water vapor scale height are also modeled but not retrieved. The a priori statistics on which the filter is trained have the effect of governing the selection of a trade-off point of noise as a function of resolution (in all three retrieval dimensions).

Rosenkranz, P. W.↗