The use of spatial and spatio-temporal data is rapidly changing the paradigm of wind wave observations, which have been traditionally restricted to time series from single-point measurements (e.g. from buoys, wave gauges). Active and passive 2D remote sensors mounted on platforms, ships, airplanes and satellites are now becoming standards in the oceanographic community and industry. Given the covered area ranging from centimeters to kilometers, such sensors are now a valuable tool for ocean and coastal observations. In this paper, we intercompare spatio-temporal wind wave data acquired with two state-of-the-art techniques, namely the stereo wave imaging and the X-band marine radar. The comparison was performed by operating the two instruments on an oceanographic research platform during a crossing-sea condition. We analyzed the statistical properties of the wave field, and its directional and omni-directional energy distributions. From our analysis, we suggest that stereo data can be exploited to find the best radar Modulation Transfer Function and scale factor needed to estimate wave parameters. Moreover, the fusion of the two systems will allow to broaden the scales covered by any one measurement, and to retrieve reliable directional wave spectra from short (∼1 m) to mid-wavelengths (∼100 m).

The use of spatial and spatio-temporal data is rapidly changing the paradigm of wind wave observations, which have been traditionally restricted to time series from single-point measurements (e.g. from buoys, wave gauges). Active and passive 2D remote sensors mounted on platforms, ships, airplanes and satellites are now becoming standards in the oceanographic community and industry. Given the covered area ranging from centimeters to kilometers, such sensors are now a valuable tool for ocean and coastal observations. In this paper, we inter compare spatio-temporal wind wave data acquired with two state-of-the-art techniques, namely the stereo wave imaging and the X-band marine radar. The comparison was performed by operating the two instruments on an oceanographic research platform during a crossing-sea condition. We analyzed the statistical properties of the wave field, and its directional and omni-directional energy distributions. From our analysis, we suggest that stereo data can be exploited to find the best radar Modulation Transfer Function and scale factor needed to estimate wave parameters. Moreover, the fusion of the two systems will allow to broaden the scales covered by any one measurement, and to retrieve reliable directional wave spectra from short (similar to 1 m) to mid-wavelengths (similar to 100 m).

Stereo imaging and X-band radar wave data fusion: An assessment

Bergamasco, Filippo;
2018-01-01

Abstract

The use of spatial and spatio-temporal data is rapidly changing the paradigm of wind wave observations, which have been traditionally restricted to time series from single-point measurements (e.g. from buoys, wave gauges). Active and passive 2D remote sensors mounted on platforms, ships, airplanes and satellites are now becoming standards in the oceanographic community and industry. Given the covered area ranging from centimeters to kilometers, such sensors are now a valuable tool for ocean and coastal observations. In this paper, we inter compare spatio-temporal wind wave data acquired with two state-of-the-art techniques, namely the stereo wave imaging and the X-band marine radar. The comparison was performed by operating the two instruments on an oceanographic research platform during a crossing-sea condition. We analyzed the statistical properties of the wave field, and its directional and omni-directional energy distributions. From our analysis, we suggest that stereo data can be exploited to find the best radar Modulation Transfer Function and scale factor needed to estimate wave parameters. Moreover, the fusion of the two systems will allow to broaden the scales covered by any one measurement, and to retrieve reliable directional wave spectra from short (similar to 1 m) to mid-wavelengths (similar to 100 m).
2018
152
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10278/3699696
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