Analysis of RF Interference Characteristics of Broadcasting Satellite TV Receivers to SMAP Satellite L-Band Microwave Radiometer

Xinxin WANG; Xiang WANG; Jianchao FAN; Lin WANG; Qinghui MENG; Enbo WEI

doi:10.11999/JEIT200593

Volume 43 Issue 8

Aug. 2021

Turn off MathJax

Article Contents

Article Navigation > Journal of Electronics & Information Technology > 2021 > 43(8): 2292-2299

Xinxin WANG, Xiang WANG, Jianchao FAN, Lin WANG, Qinghui MENG, Enbo WEI. Analysis of RF Interference Characteristics of Broadcasting Satellite TV Receivers to SMAP Satellite L-Band Microwave Radiometer[J]. Journal of Electronics & Information Technology, 2021, 43(8): 2292-2299. doi: 10.11999/JEIT200593

Citation:

Xinxin WANG, Xiang WANG, Jianchao FAN, Lin WANG, Qinghui MENG, Enbo WEI. Analysis of RF Interference Characteristics of Broadcasting Satellite TV Receivers to SMAP Satellite L-Band Microwave Radiometer[J]. Journal of Electronics & Information Technology, 2021, 43(8): 2292-2299. doi: 10.11999/JEIT200593

Citation:

Xinxin WANG, Xiang WANG, Jianchao FAN, Lin WANG, Qinghui MENG, Enbo WEI. Analysis of RF Interference Characteristics of Broadcasting Satellite TV Receivers to SMAP Satellite L-Band Microwave Radiometer[J]. Journal of Electronics & Information Technology, 2021, 43(8): 2292-2299. doi: 10.11999/JEIT200593

PDF( 2113 KB)

Analysis of RF Interference Characteristics of Broadcasting Satellite TV Receivers to SMAP Satellite L-Band Microwave Radiometer

doi: 10.11999/JEIT200593

Xinxin WANG^{1, 2, 3, 4},
Xiang WANG²,
Jianchao FAN²,
Lin WANG²,
Qinghui MENG²,
Enbo WEI^{1, 3
,
,}

1.
Institute of Oceanology, Chinese Academy of Sciences, Qingdao 266071, China
2.
National Marine Environmental Monitoring Center, Dalian 116023, China
3.
Key Laboratory of Ocean Circulation and Waves, Institute of Oceanology, Chinese Academy of Sciences, Qingdao 266071, China
4.
University of Chinese Academy of Sciences, Beijing 100049, China

Funds: The National Natural Science Foundation of China (41806212), The National Key R&D Program of China (2016YFC1401000)

Received Date: 2020-07-20
Rev Recd Date: 2021-03-23

Available Online: 2021-04-08

Publish Date: 2021-08-10

Abstract

Abstract

Based on the fusion of SMAP satellite L-band cross-polarized brightness temperature, a multi-iteration clustering Radio Frequency Interference (RFI) detection and recognition algorithm based on its spatial distribution of density and intensity is established, and the spatial and temporal distribution and variation characteristics of the density and cumulative intensity of typical Japanese RFI sources (broadcast satellite TV receivers) are analyzed and extracted. As a typical RFI source, TV receivers are mainly distributed in areas with relatively large urbanization level and range (stripes or planes), with dotted RFI sources (possibly microwave radiation base stations) distributed in local areas, resulting in local areas with high RFI levels. In other areas where the urbanization level and scope are relatively small, the dot-round RFI sources are also detected, but the interference intensity and range are relatively limited. Beginning in 2018, the overall RFI distribution range and intensity level showed a downward trend. This work is of great significance to the establishment of RFI detection, identification and suppression models in China.
- SMAP satellite,
- L-band RFI,
- Broadcast satellite TV receivers,
- Analysis of space-time characteristics

FullText(HTML)

References(29)

References

[1]	DINNAT E P, LE VINE D M, BOUTIN J, et al. Satellite sea surface salinity: Evaluation of products and impact of retrieval algorithms[C]. 2019 IEEE International Geoscience and Remote Sensing Symposium, Yokohama, Japan, 2019: 7936–7939. doi: 10.1109/IGARSS.2019.8899065.
[2]	FORE A, YUEH S, TANG Wenqing, et al. The JPL SMAP sea surface salinity algorithm[C]. 2019 IEEE International Geoscience and Remote Sensing Symposium, Yokohama, Japan, 2019: 7920–7923. doi: 10.1109/IGARSS.2019.8898359.
[3]	OLIVA R, DAGANZO E, KERR Y H, et al. SMOS radio frequency interference scenario: Status and actions taken to improve the RFI environment in the 1400–1427-MHz passive band[J]. IEEE Transactions on Geoscience and Remote Sensing, 2012, 50(5): 1427–1439. doi: 10.1109/TGRS.2012.2182775
[4]	LE VINE D M, DE MATTHAEIS P, RUF C S, et al. Aquarius RFI detection and mitigation algorithm: Assessment and examples[J]. IEEE Transactions on Geoscience and Remote Sensing, 2014, 52(8): 4574–4584. doi: 10.1109/TGRS.2013.2282595
[5]	MISRA S, JOHNSON J, AKSOY M, et al. SMAP RFI mitigation algorithm performance characterization using airborne high-rate direct-sampled SMAPVEX 2012 data[C]. 2013 IEEE International Geoscience and Remote Sensing Symposium, Melbourne, Australia, 2013: 41–44. doi: 10.1109/IGARSS.2013.6721087.
[6]	MOHAMMED P N, AKSOY M, PIEPMEIER J R, et al. SMAP L-band microwave radiometer: RFI mitigation prelaunch analysis and first year on-orbit observations[J]. IEEE Transactions on Geoscience and Remote Sensing, 2016, 54(10): 6035–6047. doi: 10.1109/TGRS.2016.2580459
[7]	CAMPS A J, CORBELLA I, TORRES F, et al. RF interference analysis in aperture synthesis interferometric radiometers: Application to L-band MIRAS instrument[J]. IEEE Transactions on Geoscience and Remote Sensing, 2000, 38(2): 942–950. doi: 10.1109/36.841976
[8]	CAMPS A, GOURRION J, TARONGI J M, et al. Radio-frequency interference detection and mitigation algorithms for synthetic aperture radiometers[J]. Algorithms, 2011, 4(3): 155–182. doi: 10.3390/a4030155
[9]	PARK J, JOHNSON J T, MAJUREC N, et al. Airborne L-Band radio frequency interference observations from the SMAPVEX08 campaign and associated flights[J]. IEEE Transactions on Geoscience and Remote Sensing, 2011, 49(9): 3359–3370. doi: 10.1109/TGRS.2011.2107560
[10]	SOLDO Y, DE MATTHAEIS P, and LE VINE D M. L-band RFI in Japan[C].2016 Radio Frequency Interference (RFI), Socorro, USA, 2016: 111–114. doi: 10.1109/RFINT.2016.7833542.
[11]	LE VINE D M, JOHNSON J T, and PIEPMEIER J. RFI and remote sensing of the earth from space[C]. 2016 Radio Frequency Interference (RFI), Socorro, USA, 2016: 49–54. doi: 10.1109/RFINT.2016.7833530.
[12]	SOLDO Y, LE VINE D M, DE MATTHAEIS P, et al. L-Band RFI detected by SMOS and Aquarius[J]. IEEE Transactions on Geoscience and Remote Sensing, 2017, 55(7): 4220–4235. doi: 10.1109/TGRS.2017.2690406
[13]	MIRANDA J J, VALL-LLOSSERA M, CAMPS A, et al. Sea state effect on the sea surface emissivity at L-band[J]. IEEE Transactions on Geoscience and Remote Sensing, 2003, 41(10): 2307–2315. doi: 10.1109/TGRS.2003.817190
[14]	KERR Y H, WALDTEUFEL P, WIGNERON J P, et al. Soil moisture retrieval from space: The Soil Moisture and Ocean Salinity (SMOS) mission[J]. IEEE Transactions on Geoscience and Remote Sensing, 2001, 39(8): 1729–1735. doi: 10.1109/36.942551
[15]	MISRA S and RUF C S. Detection of radio-frequency interference for the Aquarius radiometer[J]. IEEE Transactions on Geoscience and Remote Sensing, 2008, 46(10): 3123–3128. doi: 10.1109/TGRS.2008.920371
[16]	PIEPMEIER J R, JOHNSON J T, MOHAMMED P N, et al. Radio-frequency interference mitigation for the soil moisture active passive microwave radiometer[J]. IEEE Transactions on Geoscience and Remote Sensing, 2014, 52(1): 761–775. doi: 10.1109/TGRS.2013.2281266
[17]	王新新, 王祥, 韩震, 等. 基于L波段Stokes参数遥感数据射频干扰检测及特性分析[J]. 电子与信息学报, 2015, 37(10): 2342–2348. doi: 10.11999/JEIT141577 WANG Xinxin, WANG Xiang, HAN Zhen, et al. Radio frequency interference detection and characteristic analysis based on the L band Stokes parameters remote sensing data[J]. Journal of Electronics &Information Technology, 2015, 37(10): 2342–2348. doi: 10.11999/JEIT141577
[18]	PENG Jinzheng, MISRA S, CHAN S, et al. SMAP radiometer brightness temperature calibration for the L1B_TB, L1C_TB (Version 4), and L1C_TB_E (Version 2) data products[EB/OL]. https://nsidc.org/sites/nsidc.org/files/technical-references/SMAP_L1_Assessment%20Report%2020180601_v9.pdf.2020.2.
[19]	QUEROL J, PEREZ A, and CAMPS A. A review of RFI mitigation techniques in microwave radiometry[J]. Remote Sensing, 2019, 11(24): 3042. doi: 10.3390/rs11243042
[20]	DAGANZO E, OLIVA R, RICHAUME P, et al. SMOS RFI experience in the 1400–1427 MHz passive band: Case of extended interference caused by broadcasting satellite home-TV receivers[C]. 2019 IEEE International Geoscience and Remote Sensing Symposium, Yokohama, Japan, 2019: 4455–4458. doi: 10.1109/IGARSS.2019.8897873.
[21]	AKSOY M. Radio frequency interference characterization and detection in L-band microwave radiometry[D]. [Ph. D. dissertation], The Ohio State University, 2015.
[22]	PIEPMEIER J R, FOCARDI P, HORGAN K A, et al. SMAP L-band microwave radiometer: Instrument design and first year on orbit[J]. IEEE Transactions on Geoscience and Remote Sensing, 2017, 55(4): 1954–1966. doi: 10.1109/TGRS.2016.2631978
[23]	SOLDO Y, LE VINE D M, BRINGER A, et al. Recent advances in Smap RFI processing[C]. 2018 IEEE International Geoscience and Remote Sensing Symposium, Valencia, Spain, 2018: 313–315. doi: 10.1109/IGARSS.2018.8518891.
[24]	SOLDO Y, LE VINE D M, BRINGER A, et al. Location of radio-frequency interference sources using the SMAP L-band radiometer[J]. IEEE Transactions on Geoscience and Remote Sensing, 2018, 56(11): 6854–6866. doi: 10.1109/TGRS.2018.2844127
[25]	姜涛, 赵凯, 万祥坤. L波段微波辐射计周期脉冲式干扰时域检测方法研究[J]. 电子与信息学报, 2018, 40(7): 1539–1545. doi: 10.11999/JEIT170954 JIANG Tao, ZHAO Kai, and WAN Xiangkun. Research on detection methods to periodic pulsed interference for L band microwave radiometer in time domain[J]. Journal of Electronics &Information Technology, 2018, 40(7): 1539–1545. doi: 10.11999/JEIT170954
[26]	KRISTENSEN S S, BALLING J E, SKOU N, et al. RFI detection in SMOS data using 3^rd and 4^th Stokes parameters[C]. The 12th Specialist Meeting on Microwave Radiometry and Remote Sensing of the Environment (MicroRad), Rome, Italy, 2012: 1–4. doi: 10.1109/MicroRad.2012.6185254.
[27]	WANG Xinxin, WANG Xiang, FAN Jianchao, et al. Automatic detection and identification of RFI sources for SMAP satellite polarized data based on IDL[C]. The 10th International Conference on Intelligent Control and Information Processing (ICICIP), Marrakesh, Morocco, 2019: 76–80. doi: 10.1109/ICICIP47338.2019.9012190.
[28]	马廷. 夜光遥感大数据视角下的中国城市化时空特征[J]. 地球信息科学学报, 2019, 21(1): 59–67. doi: 10.12082/dqxxkx.2019.180361 MA Ting. Spatiotemporal characteristics of urbanization in china from the perspective of remotely sensed big data of nighttime light[J]. Journal of Geo-Information Science, 2019, 21(1): 59–67. doi: 10.12082/dqxxkx.2019.180361
[29]	JIN Rong, LI Qingxia, and LIU Hang. A subspace algorithm to mitigate energy unknown RFI for synthetic aperture interferometric radiometer[J]. IEEE Transactions on Geoscience and Remote Sensing, 2020, 58(1): 227–237. doi: 10.1109/TGRS.2019.2936005