東華大學圖書館 |

Passive Microwave Remote Sensing of Snow Layers Using Novel Wideband Radiometer Systems and RFI Mitigation.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Passive Microwave Remote Sensing of Snow Layers Using Novel Wideband Radiometer Systems and RFI Mitigation./
作者:	Salim, Maryam.
出版者:	Ann Arbor : ProQuest Dissertations & Theses, : 2021,
面頁冊數:	177 p.
附註:	Source: Dissertations Abstracts International, Volume: 83-05, Section: B.
Contained By:	Dissertations Abstracts International83-05B.
標題:	Electromagnetics. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=28846639
ISBN:	9798471103276

Passive Microwave Remote Sensing of Snow Layers Using Novel Wideband Radiometer Systems and RFI Mitigation.
Salim, Maryam.

Passive Microwave Remote Sensing of Snow Layers Using Novel Wideband Radiometer Systems and RFI Mitigation. - Ann Arbor : ProQuest Dissertations & Theses, 2021 - 177 p.

Source: Dissertations Abstracts International, Volume: 83-05, Section: B.

Thesis (Ph.D.)--University of Michigan, 2021.

This item must not be sold to any third party vendors.

Climate change can reduce the availability of water resources in many regions, and it will affect agriculture, industry, and energy supply. Snowpack monitoring is important in water resource management as well as flood and avalanche protection.The rapid melting process due to global warming changes the snowpacks' annual statistics, including the extent, and the snow water equivalent (SWE) of seasonal snowpacks, which results in non-stationary annual statistics that should be monitored in nearly daily intervals.The development of advanced radiometric sensors capable of accurately measuring the snowpack thickness and SWE is needed for the long-term study of the snowpack parameters' statistical changes. Passive microwave radiometry provides a means for measuring the microwave emission from a scene of snow and ice. A Wideband Autocorrelation Radiometer (ac{WiBAR}) operating from 1-2~GHz measures spontaneous emission from snowpack at long wavelengths where the scattering is minimized, but the snow layer coherent effects are preserved. By using a wide bandwidth to measure the spacing between frequencies of constructive and destructive interference of the emission from the soil under the snow, it can reveal the microwave travel time through the snow, and thus the snow depth.However, narrowband radio frequency interference (RFI) in the WiBAR's frequency of operations reduces the ability of the WiBAR to measure the thickness accurately. In addition, the current WiBAR system is a frequency domain, FD-WiBAR, system that uses a field-portable spectrum analyzer to collect the data and suffers from high data acquisition time which limits its applications for spaceborne and airborne technologies.In this work, a novel frequency tunable microwave comb filter is proposed for RFI mitigation. The frequency response of the proposed filter has a pattern with many frequencies band-pass and band rejection that preserves the frequency span while reducing the RFI. Moreover, we demonstrate time-domain WiBAR, TD-WiBAR, which presented as an alternative method for FD-WiBAR, and is capable of providing faster data acquisition. A new time-domain calibration is also developed for TD-WiBAR and evaluated with the frequency domain calibration.To validate the TD-WiBAR method, simulated laboratory measurements are performed using a microwave scene simulator circuit. Then the WiBAR instrument is enhanced with the proposed comb filter and showed the RFI mitigation in time-domain mode on an instrument bench test.Furthermore, we analyze the effects of an above snow vegetation layer on brightness temperature spectra, particularly the possible decay of wave coherence arising from volume scattering in the vegetation canopy. In our analysis, the snow layer is assumed to be flat, and its upward emission and surface reflectivities are modeled by a fully coherent model, while an incoherent radiative transfer model describes the volume scattering from the vegetation layer.We proposed a unified framework of vegetation scattering using radiative transfer (RT) theory for passive and active remote sensing of vegetated land surfaces, especially those associated with moderate-to-large vegetation water contents (VWCs), e.g., forest field. The framework allows for modeling passive and active microwave signatures of the vegetated field with the same physical parameters describing the vegetation structure. The proposed model is validated with the passive and active L-band sensor (PALS) acquired in SMAPVEX12 measurements in 2012, demonstrating the applicability of this model.

ISBN: 9798471103276Subjects--Topical Terms:

3173223
Electromagnetics.
Subjects--Index Terms:

Microwave radiometry

Passive Microwave Remote Sensing of Snow Layers Using Novel Wideband Radiometer Systems and RFI Mitigation.
LDR:04912nmm a2200397 4500 001 2343389
005 20220502104243.5
008 241004s2021 ||||||||||||||||| ||eng d
020 $a 9798471103276
035 $a (MiAaPQ)AAI28846639
035 $a (MiAaPQ)umichrackham003833
035 $a AAI28846639
040 $a MiAaPQ $c MiAaPQ
100 1 $a Salim, Maryam. $3 3681949
245 1 0 $a Passive Microwave Remote Sensing of Snow Layers Using Novel Wideband Radiometer Systems and RFI Mitigation.
260 1 $a Ann Arbor : $b ProQuest Dissertations & Theses, $c 2021
300 $a 177 p.
500 $a Source: Dissertations Abstracts International, Volume: 83-05, Section: B.
500 $a Advisor: De Roo, Roger D.;Sarabandi, Kamal.
502 $a Thesis (Ph.D.)--University of Michigan, 2021.
506 $a This item must not be sold to any third party vendors.
506 $a This item must not be added to any third party search indexes.
520 $a Climate change can reduce the availability of water resources in many regions, and it will affect agriculture, industry, and energy supply. Snowpack monitoring is important in water resource management as well as flood and avalanche protection.The rapid melting process due to global warming changes the snowpacks' annual statistics, including the extent, and the snow water equivalent (SWE) of seasonal snowpacks, which results in non-stationary annual statistics that should be monitored in nearly daily intervals.The development of advanced radiometric sensors capable of accurately measuring the snowpack thickness and SWE is needed for the long-term study of the snowpack parameters' statistical changes. Passive microwave radiometry provides a means for measuring the microwave emission from a scene of snow and ice. A Wideband Autocorrelation Radiometer (ac{WiBAR}) operating from 1-2~GHz measures spontaneous emission from snowpack at long wavelengths where the scattering is minimized, but the snow layer coherent effects are preserved. By using a wide bandwidth to measure the spacing between frequencies of constructive and destructive interference of the emission from the soil under the snow, it can reveal the microwave travel time through the snow, and thus the snow depth.However, narrowband radio frequency interference (RFI) in the WiBAR's frequency of operations reduces the ability of the WiBAR to measure the thickness accurately. In addition, the current WiBAR system is a frequency domain, FD-WiBAR, system that uses a field-portable spectrum analyzer to collect the data and suffers from high data acquisition time which limits its applications for spaceborne and airborne technologies.In this work, a novel frequency tunable microwave comb filter is proposed for RFI mitigation. The frequency response of the proposed filter has a pattern with many frequencies band-pass and band rejection that preserves the frequency span while reducing the RFI. Moreover, we demonstrate time-domain WiBAR, TD-WiBAR, which presented as an alternative method for FD-WiBAR, and is capable of providing faster data acquisition. A new time-domain calibration is also developed for TD-WiBAR and evaluated with the frequency domain calibration.To validate the TD-WiBAR method, simulated laboratory measurements are performed using a microwave scene simulator circuit. Then the WiBAR instrument is enhanced with the proposed comb filter and showed the RFI mitigation in time-domain mode on an instrument bench test.Furthermore, we analyze the effects of an above snow vegetation layer on brightness temperature spectra, particularly the possible decay of wave coherence arising from volume scattering in the vegetation canopy. In our analysis, the snow layer is assumed to be flat, and its upward emission and surface reflectivities are modeled by a fully coherent model, while an incoherent radiative transfer model describes the volume scattering from the vegetation layer.We proposed a unified framework of vegetation scattering using radiative transfer (RT) theory for passive and active remote sensing of vegetated land surfaces, especially those associated with moderate-to-large vegetation water contents (VWCs), e.g., forest field. The framework allows for modeling passive and active microwave signatures of the vegetated field with the same physical parameters describing the vegetation structure. The proposed model is validated with the passive and active L-band sensor (PALS) acquired in SMAPVEX12 measurements in 2012, demonstrating the applicability of this model.
590 $a School code: 0127.
650 4 $a Electromagnetics. $3 3173223
650 4 $a Aerospace engineering. $3 1002622
650 4 $a Electrical engineering. $3 649834
650 4 $a Remote sensing. $3 535394
653 $a Microwave radiometry
653 $a Snow layers
653 $a Wideband radiometer systems
653 $a RFI mitigation
690 $a 0544
690 $a 0607
690 $a 0538
690 $a 0799
710 2 $a University of Michigan. $b Electrical and Computer Engineering. $3 3284714
773 0 $t Dissertations Abstracts International $g 83-05B.
790 $a 0127
791 $a Ph.D.
792 $a 2021
793 $a English
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=28846639