Source analysis of spaceborne microwave radiometer interference over land

Li GUAN , Sibo ZHANG

Front. Earth Sci. ›› 2016, Vol. 10 ›› Issue (1) : 135 -144.

PDF (3041KB)
Front. Earth Sci. ›› 2016, Vol. 10 ›› Issue (1) : 135 -144. DOI: 10.1007/s11707-015-0487-6
RESEARCH ARTICLE
RESEARCH ARTICLE

Source analysis of spaceborne microwave radiometer interference over land

Author information +
History +
PDF (3041KB)

Abstract

Satellite microwave thermal emissions mixed with signals from active sensors are referred to as radio-frequency interference (RFI). Based on Advanced Microwave Scanning Radiometer–Earth Observing System (AMSR-E) observations from June 1 to 16, 2011, RFI over Europe was identified and analyzed using the modified principal component analysis algorithm in this paper. The X band AMSR-E measurements in England and Italy are mostly affected by the stable, persistent, active microwave transmitters on the surface, while the RFI source of other European countries is the interference of the reflected geostationary TV satellite downlink signals to the measurements of spaceborne microwave radiometers. The locations and intensities of the RFI induced by the geostationary TV and communication satellites changed with time within the observed period. The observations of spaceborne microwave radiometers in ascending portions of orbits are usually interfered with over European land, while no RFI was detected in descending passes. The RFI locations and intensities from the reflection of downlink radiation are highly dependent upon the relative geometry between the geostationary satellite and the measuring passive sensor. Only these fields of view of a spaceborne instrument whose scan azimuths are close to the azimuth relative to the geostationary satellite are likely to be affected by RFI.

Keywords

AMSR-E / RFI / geostationary TV satellite

Cite this article

Download citation ▾
Li GUAN, Sibo ZHANG. Source analysis of spaceborne microwave radiometer interference over land. Front. Earth Sci., 2016, 10(1): 135-144 DOI:10.1007/s11707-015-0487-6

登录浏览全文

4963

注册一个新账户 忘记密码

References

[1]

Adams I S, Bettenhaused M H, Gaiser P W, Johnston W (2010). Identification of ocean-reflected radio-frequency interference using WindSat retrieval Chi-Square probability. IEEE Geosci Remote Sens Lett, 7(2): 406–410

[2]

Chelle G, Marty B, Kyle H (2010). Algorithm development GCOM-W AMSR-2 ocean product suite, Joint PI Workshop of Global Environment Observation Mission, Tokyo, Japan

[3]

Ellingson S W, Johnson J T (2006). A polarimetric survey of radio-frequency interference in C- and X-Bands in the continental United States using WindSat Radiometry. IEEE Trans Geosci Rem Sens, 44(3): 540–548

[4]

Gaiser P W, St Germain K M, Twarog E M, Poe G A, Purday W, Richardson D, Grossman W, Jones W L, Spencer D, Golba G, Cleveland J, Choy L, Bevilacqua R M, Chang P S (2004). The WindSat spaceborne polarimetric microwave radiometer: sensor description and early orbit performance. IEEE Trans Geosci Rem Sens, 42(11): 2347–2361

[5]

Grody N C, Basist A N (1996). Global identification of snowcover using SSM/I measurements. IEEE Trans Geosci Rem Sens, 34(1): 237–249

[6]

Hollinger J P, Peirce J L, Poe G A (1990). SSM/I instrument evaluation. IEEE Trans Geosci Rem Sens, 28(5): 781–790

[7]

Jolliffe I T (1976). Principal Component Analysis. New York: Springer-Hill

[8]

Kawanishi T, Sezai T, Ito Y, Imaoka K, Takeshima T, Ishido Y, Shibata A, Miura M, Inahata H, Spencer R W (2003). The advanced microwave scanning radiometer for the earth observation system (AMSR-E), NASDA’s contribution to the EOS for global enery and water cycle studies. IEEE Trans Geosci Rem Sens, 41(2): 184–194

[9]

Kelly R E, Chang A T, Tsang L, Foster J L (2003). A prototype AMSR-E global snow area and snow depth algorithm. IEEE Trans Geosci Rem Sens, 41(2): 230–242

[10]

Lattin J M, Carroll J D, Green P E (2003). Analyzing Multivariate Data. Beijing: China Machine Press, 83–123

[11]

Li L, Gaiser P W, Bettenhausen M H, Johnston W (2006). WindSat radio-frequency interference signature and its identification over land and ocean. IEEE Trans Geosci Rem Sens, 44(3): 530–539

[12]

Li L, Njoku E G, Im E, Chang P S, St Germain K S (2004). A preliminary survey of radio-frequency interference over the U. S. in aqua AMSR-E data. IEEE Trans Geosci Rem Sens, 42(2): 380– 390

[13]

Njoku E G, Ashcroft P, Chan T K, Li L (2005). Global survey and statistics of radio-frequency interference in AMSR-E land observations. IEEE Trans Geosci Rem Sens, 43(5): 938–947

[14]

Njoku E G, Jackson T J, Lakshmi V, Chan T K, Nghiem S V (2003). Soil moisture retrieval from AMSR-E. IEEE Trans Geosci Rem Sens, 41(2): 215–229

[15]

Owe M, de Jeu R, Walker J (2001). A methodology for surface soil moisture and vegetation optical depth retrieval using the microwave polarization difference index. IEEE Trans Geosci Rem Sens, 39(8): 1643–1654

[16]

Wu Y, Weng F (2011). Detection and correction of AMSR-E radio-frequency interference. Acta Meteorologica Sinica, 25(5): 669–681

[17]

Zhang P, Yang J, Dong C, Lu N, Yang Z, Shi J (2009). General introduction on payloads, ground segment and data application of Fengyun 3A. Front Earth Sci China, 3(3): 367–373

[18]

Zhang S, Guan L (2013). Identifying AMSR-E Radio-Frequency Interference over Snow Covered Land. Frontiers of Earth Science (revised).

[19]

Zhao J, Zou X, Weng F (2013). WindSat radio-frequency interference signature and its identification over greenland and antarctic. IEEE Trans Geosci Rem Sens, 51(9): 4830–4839

[20]

Zou X, Zhao J, Weng F, Qin Z (2012). Detection of radio-frequency interference signal over land from FY-3B microwave radiation imager (MWRI). IEEE Trans Geosci Rem Sens, 50(12): 4994– 5003

RIGHTS & PERMISSIONS

Higher Education Press and Springer-Verlag Berlin Heidelberg

AI Summary AI Mindmap
PDF (3041KB)

883

Accesses

0

Citation

Detail

Sections
Recommended

AI思维导图

/