The Experts below are selected from a list of 360 Experts worldwide ranked by ideXlab platform
Sidharth Misra - One of the best experts on this subject based on the ideXlab platform.
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real time detection and filtering of Radio Frequency Interference onboard a spaceborne microwave Radiometer the cuberrt mission
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2020Co-Authors: Joel T Johnson, Sidharth Misra, C. Mckelvey, M. Andrews, C D Ball, Chichih Chen, Andrew Obrien, Graeme Smith, Landon J Garry, Rudi BendigAbstract:The Cubesat Radiometer Radio Frequency Interference technology validation mission (CubeRRT) was developed to demonstrate real-time onboard detection and filtering of Radio Frequency Interference (RFI) for wide bandwidth microwave Radiometers. CubeRRT's key technology is its Radiometer digital backend (RDB) that is capable of measuring an instantaneous bandwidth of 1 GHz and of filtering the input signal into an estimated total power with and without RFI contributions. CubeRRT's onboard RFI processing capability dramatically reduces the volume of data that must be downlinked to the ground and eliminates the need for ground-based RFI processing. RFI detection is performed by resolving the input bandwidth into 128 Frequency subchannels, with the kurtosis of each subchannel and the variations in power across Frequency used to detect nonthermal contributions. RFI filtering is performed by removing corrupted Frequency subchannels prior to the computation of the total channel power. The 1 GHz bandwidth input signals processed by the RDB are obtained from the payload's antenna (ANT) and Radiometer front end (RFE) subsystems that are capable of tuning across RF center frequencies from 6 to 40 GHz. The CubeRRT payload was installed into a 6U spacecraft bus provided by Blue Canyon Technologies that provides spacecraft power, communications, data management, and navigation functions. The design, development, integration and test, and on-orbit operations of CubeRRT are described in this article. The spacecraft was delivered on March 22nd, 2018 for launch to the International Space Station (ISS) on May 21st, 2018. Since its deployment from the ISS on July 13th, 2018, the CubeRRT RDB has completed more than 5000 h of operation successfully, validating its robustness as an RFI processor. Although CubeRRT's RFE subsystem ceased operating on September 8th, 2018, causing the RDB input thereafter to consist only of internally generated noise, CubeRRT's key RDB technology continues to operate without issue and has demonstrated its capabilities as a valuable subsystem for future Radiometry missions.
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development of an on board wide band processor for Radio Frequency Interference detection and filtering
IEEE Transactions on Geoscience and Remote Sensing, 2019Co-Authors: Sidharth Misra, Shannon Brown, Rudi Bendig, Jonathon Kocz, R F Jarnot, Carl Felten, J JohnsonAbstract:The demand for microwave spectrum for commercial and industrial use has been increasing rapidly over the last decade, putting stress on the limited spectral resources for passive microwave remote sensing. Radio Frequency Interference from man-made sources is expected to become worse over the coming years. At 1.4 GHz, the SMAP mission has implemented and demonstrated advanced Interference detection algorithms for its microwave Radiometer. This scheme will not be feasible at higher microwave frequencies (above 6 GHz) due to much larger Radiometer bandwidths used and the limited downlink data volume available to implement RFI filtering algorithms in the ground processing. In this paper, we present the design, development, and test of an advanced on-board Interference detection and RFI filtering digital back-end that is capable of operation for a 1 GHz-Radiometer bandwidth. We describe the combined RFI detection algorithms implemented in the digital backend’s firmware and the on-board RFI filtering of Interference-corrupted data that will be necessary to limit downlink rate requirements for future high-Frequency microwave missions.
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development of the cubesat Radiometer Radio Frequency Interference technology validation cuberrt system
International Geoscience and Remote Sensing Symposium, 2017Co-Authors: C D Ball, Sidharth Misra, Joel T Johnson, C. Mckelvey, M. Andrews, Chichih Chen, Andrew Obrien, Graeme Smith, Landon J Garry, Shannon BrownAbstract:The CubeSat Radiometer Radio Frequency Interference Technology Validation (CubeRRT) mission is developing a 6U CubeSat system to demonstrate Radio Frequency Interference (RFI) detection and filtering technologies for future microwave Radiometer remote sensing missions. CubeRRT will perform observations of Earth brightness temperatures from 6–40 GHz using a 1 GHz bandwidth tuned channel and will demonstrate on-board real-time RFIS processing. The system is currently under development, with an expected launch date in mid-2018 followed by a one year period of on-orbit operations. Development of the CubeRRT spacecraft, Radiometer instrument, and concepts of operation are described in this paper.
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The CubeSat Radiometer Radio Frequency Interference Technology Validation (CubeRRT) mission
2016 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), 2016Co-Authors: J. T. Johnson, Sidharth Misra, C. C. Chen, A. O'brien, G. E. Smith, C. Mckelvey, M. Andrews, C. Ball, Shannon Brown, Jonathan KoczAbstract:The CubeSat Radiometer Radio Frequency Interference Technology Validation (CubeRRT) mission is developing a 6U CubeSat system to demonstrate Radio Frequency Interference (RFI) detection and mitigation technologies for future microwave Radiometer remote sensing missions. CubeRRT will perform observations of Earth brightness temperatures from 6-40 GHz using a 1 GHz bandwidth tuned channel, and will demonstrate on-board real-time RFI processing. The system is currently under development, with launch readiness expected in 2018 followed by a one year period of on-orbit operations. Project plans and status are reported in this paper.
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an improved Radio Frequency Interference model reevaluation of the kurtosis detection algorithm performance under central limit conditions
IEEE Transactions on Geoscience and Remote Sensing, 2012Co-Authors: Sidharth Misra, R D De Roo, C S RufAbstract:Recent airborne field campaigns making passive microwave measurements have observed some Radio Frequency Interference (RFI) that remained undetected by the kurtosis RFI-detection algorithm. The current pulsed-sinusoidal model for RFI does not explain this anomalous behavior of the detection algorithm. In this paper, a new RFI model is developed that takes into account multiple RFI sources within an antenna footprint. The performance of the kurtosis algorithm with the new model is evaluated. The behavior of the kurtosis detection algorithm under central-limit conditions due to multiple sources is experimentally verified. The new RFI model offers a plausible explanation for the lack of detection by the kurtosis algorithm of the RFI otherwise observed.
Joel T Johnson - One of the best experts on this subject based on the ideXlab platform.
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real time detection and filtering of Radio Frequency Interference onboard a spaceborne microwave Radiometer the cuberrt mission
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2020Co-Authors: Joel T Johnson, Sidharth Misra, C. Mckelvey, M. Andrews, C D Ball, Chichih Chen, Andrew Obrien, Graeme Smith, Landon J Garry, Rudi BendigAbstract:The Cubesat Radiometer Radio Frequency Interference technology validation mission (CubeRRT) was developed to demonstrate real-time onboard detection and filtering of Radio Frequency Interference (RFI) for wide bandwidth microwave Radiometers. CubeRRT's key technology is its Radiometer digital backend (RDB) that is capable of measuring an instantaneous bandwidth of 1 GHz and of filtering the input signal into an estimated total power with and without RFI contributions. CubeRRT's onboard RFI processing capability dramatically reduces the volume of data that must be downlinked to the ground and eliminates the need for ground-based RFI processing. RFI detection is performed by resolving the input bandwidth into 128 Frequency subchannels, with the kurtosis of each subchannel and the variations in power across Frequency used to detect nonthermal contributions. RFI filtering is performed by removing corrupted Frequency subchannels prior to the computation of the total channel power. The 1 GHz bandwidth input signals processed by the RDB are obtained from the payload's antenna (ANT) and Radiometer front end (RFE) subsystems that are capable of tuning across RF center frequencies from 6 to 40 GHz. The CubeRRT payload was installed into a 6U spacecraft bus provided by Blue Canyon Technologies that provides spacecraft power, communications, data management, and navigation functions. The design, development, integration and test, and on-orbit operations of CubeRRT are described in this article. The spacecraft was delivered on March 22nd, 2018 for launch to the International Space Station (ISS) on May 21st, 2018. Since its deployment from the ISS on July 13th, 2018, the CubeRRT RDB has completed more than 5000 h of operation successfully, validating its robustness as an RFI processor. Although CubeRRT's RFE subsystem ceased operating on September 8th, 2018, causing the RDB input thereafter to consist only of internally generated noise, CubeRRT's key RDB technology continues to operate without issue and has demonstrated its capabilities as a valuable subsystem for future Radiometry missions.
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location of Radio Frequency Interference sources using the smap l band Radiometer
IEEE Transactions on Geoscience and Remote Sensing, 2018Co-Authors: Yan Soldo, Joel T Johnson, Roger Oliva, David Le M Vine, Alexandra Bringer, Paolo De Matthaeis, Jeffrey R PiepmeierAbstract:The Soil Moisture Active/Passive (SMAP) satellite mission measures Earth’s radiation in the protected portion of the spectrum at 1.413 GHz (L-band) to retrieve geophysical quantities of the surface, such as soil moisture and the frozen/thawed state of the soil. The presence of Radio-Frequency Interference (RFI) in this band is significant and impacts the quality of SMAP measurements. Knowing the location of the sources of RFI is important, because it can help to identify the source itself and also be used to develop strategies to mitigate its impact of the RFI on the data. This paper presents an algorithm that takes advantage of the viewing geometry of SMAP to locate sources of RFI. The results are validated using known locations of RFI sources and by comparison with the measurements of Soil Moisture and Ocean Salinity (SMOS) and Aquarius, two other satellite missions with L-band microwave Radiometers operating in the protected band. Comparison with RFI of known location suggests that the algorithm is accurate to 1–2 km. The median distance between the locations reported by SMOS and this algorithm is 2.27 km. A study of the relationship between the localization error and the number of observations of RFI sources shows that the median localization error is about 2 km with 12 observations and about 1 km with 30 observations.
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development of the cubesat Radiometer Radio Frequency Interference technology validation cuberrt system
International Geoscience and Remote Sensing Symposium, 2017Co-Authors: C D Ball, Sidharth Misra, Joel T Johnson, C. Mckelvey, M. Andrews, Chichih Chen, Andrew Obrien, Graeme Smith, Landon J Garry, Shannon BrownAbstract:The CubeSat Radiometer Radio Frequency Interference Technology Validation (CubeRRT) mission is developing a 6U CubeSat system to demonstrate Radio Frequency Interference (RFI) detection and filtering technologies for future microwave Radiometer remote sensing missions. CubeRRT will perform observations of Earth brightness temperatures from 6–40 GHz using a 1 GHz bandwidth tuned channel and will demonstrate on-board real-time RFIS processing. The system is currently under development, with an expected launch date in mid-2018 followed by a one year period of on-orbit operations. Development of the CubeRRT spacecraft, Radiometer instrument, and concepts of operation are described in this paper.
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Radio Frequency Interference mitigation for the soil moisture active passive microwave Radiometer
IEEE Transactions on Geoscience and Remote Sensing, 2014Co-Authors: Jeffrey R Piepmeier, Joel T Johnson, Damon Bradley, Priscilla N Mohammed, C S Ruf, Mustafa Aksoy, Rafael Garcia, Derek Hudson, Lynn Miles, Mark WongAbstract:The Soil Moisture Active Passive (SMAP) Radiometer operates in the L-band protected spectrum (1400-1427 MHz) that is known to be vulnerable to Radio-Frequency Interference (RFI). Although transmissions are forbidden at these frequencies by international regulations, ground-based, airborne, and spaceborne Radiometric observations show substantial evidence of out-of-band emissions from neighboring transmitters and possibly illegally operating emitters. The spectral environment that SMAP faces includes not only occasional large levels of RFI but also significant amounts of low-level RFI equivalent to a brightness temperature of 0.1-10 K at the Radiometer output. This low-level Interference would be enough to jeopardize the success of a mission without an aggressive mitigation solution, including special flight hardware and ground software with capabilities of RFI detection and removal. SMAP takes a multidomain approach to RFI mitigation by utilizing an innovative onboard digital detector back end with digital signal processing algorithms to characterize the time, Frequency, polarization, and statistical properties of the received signals. Almost 1000 times more measurements than what is conventionally necessary are collected to enable the ground processing algorithm to detect and remove harmful Interference. Multiple RFI detectors are run on the ground, and their outputs are combined for maximum likelihood of detection to remove the RFI within a footprint. The capabilities of the hardware and software systems are successfully demonstrated using test data collected with a SMAP Radiometer engineering test unit.
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airborne l band Radio Frequency Interference observations from the smapvex08 campaign and associated flights
IEEE Transactions on Geoscience and Remote Sensing, 2011Co-Authors: James Park, Sidharth Misra, Joel T Johnson, N Niamsuwan, Jeffrey R Piepmeier, Priscilla N Mohammed, C S Ruf, Ninoslav Majurec, S H Yueh, S J DinardoAbstract:Statistics of Radio Frequency Interference (RFI) observed in the band 1398-1422 MHz during an airborne campaign in the United States are reported for use in analysis and forecasting of L-band RFI for microwave Radiometry. The observations were conducted from September to October 2008, and included approximately 92 h of flight time, of which approximately 20 h of “transit” or dedicated RFI observing flights are used in compiling the statistics presented. The observations used include outbound and return flights from Colorado to Maryland, as well as RFI surveys over large cities. The Passive Active L-Band Sensor (PALS) Radiometer of NASA Jet Propulsion Laboratory augmented by three dedicated RFI observing systems was used in these observations. The complete system as well as the associated RFI characterization approaches are described, along with the resulting RFI statistical information and examinations of specific RFI sources. The results show that RFI in the protected L-band spectrum is common over North America, although the resulting Interference when extrapolated to satellite observations will appear as “low-level” corruption that will be difficult to detect for traditional Radiometer systems.
A R Offringa - One of the best experts on this subject based on the ideXlab platform.
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the low Frequency environment of the murchison widefield array Radio Frequency Interference analysis and mitigation
Publications of the Astronomical Society of Australia, 2015Co-Authors: A R Offringa, G Bernardi, R B Wayth, N Hurleywalker, David L Kaplan, N Barry, A P Beardsley, M E BellAbstract:This is the Accepted Manuscript version of the following article: A. R. Offringa, et al., “The low-Frequency environment of the Murchison Widefield Array: Radio-Frequency Interference analysis and mitigation”, Publications of the Astronomical Society of Australia, Vol. 32, March 2015. The final published version is available at: https://doi.org/10.1017/pasa.2015.7 © Astronomical Society of Australia 2015
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the low Frequency environment of the murchison widefield array Radio Frequency Interference analysis and mitigation
arXiv: Instrumentation and Methods for Astrophysics, 2015Co-Authors: A R Offringa, G Bernardi, R B Wayth, N Hurleywalker, David L Kaplan, N Barry, A P Beardsley, M E BellAbstract:The Murchison Widefield Array (MWA) is a new low-Frequency interferometric Radio telescope built in Western Australia at one of the locations of the future Square Kilometre Array (SKA). We describe the automated Radio-Frequency Interference (RFI) detection strategy implemented for the MWA, which is based on the AOFlagger platform, and present 72-231-MHz RFI statistics from 10 observing nights. RFI detection removes 1.1% of the data. RFI from digital TV (DTV) is observed 3% of the time due to occasional ionospheric or atmospheric propagation. After RFI detection and excision, almost all data can be calibrated and imaged without further RFI mitigation efforts, including observations within the FM and DTV bands. The results are compared to a previously published Low-Frequency Array (LOFAR) RFI survey. The remote location of the MWA results in a substantially cleaner RFI environment compared to LOFAR's Radio environment, but adequate detection of RFI is still required before data can be analysed. We include specific recommendations designed to make the SKA more robust to RFI, including: the availability of sufficient computing power for RFI detection; accounting for RFI in the receiver design; a smooth band-pass response; and the capability of RFI detection at high time and Frequency resolution (second and kHz-scale respectively).
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a morphological algorithm for improving Radio Frequency Interference detection
arXiv: Instrumentation and Methods for Astrophysics, 2012Co-Authors: A R Offringa, J J Van De Gronde, Jos B T M RoerdinkAbstract:A technique is described that is used to improve the detection of Radio-Frequency Interference in astronomical Radio observatories. It is applied on a two-dimensional Interference mask after regular detection in the time-Frequency domain with existing techniques. The scale-invariant rank (SIR) operator is defined, which is a one-dimensional mathematical morphology technique that can be used to find adjacent intervals in the time or Frequency domain that are likely to be affected by RFI. The technique might also be applicable in other areas in which morphological scale-invariant behaviour is desired, such as source detection. A new algorithm is described, that is shown to perform quite well, has linear time complexity and is fast enough to be applied in modern high resolution observatories. It is used in the default pipeline of the LOFAR observatory.
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post correlation Radio Frequency Interference classification methods
Monthly Notices of the Royal Astronomical Society, 2010Co-Authors: A R Offringa, A G De Bruyn, Michael Biehl, Saleem Zaroubi, G Bernardi, V N PandeyAbstract:We describe and compare several post-correlation Radio Frequency Interference (RFI) classification methods. As data sizes of observations grow with new and improved telescopes, the need for completely automated, robust methods for RFI mitigation is pressing. We investigated several classification methods and find that, for the data sets we used, the most accurate among them is the SumThreshold method. This is a new method formed from a combination of existing techniques, including a new way of thresholding. This iterative method estimates the astronomical signal by carrying out a surface fit in the time-Frequency plane. With a theoretical accuracy of 95 per cent recognition and an approximately 0.1 per cent false probability rate in simple simulated cases, the method is in practice as good as the human eye in finding RFI. In addition, it is fast, robust, does not need a data model before it can be executed and works in almost all configurations with its default parameters. The method has been compared using simulated data with several other mitigation techniques, including one based upon the singular value decomposition of the time-Frequency matrix, and has shown better results than the rest.
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post correlation Radio Frequency Interference classification methods
arXiv: Instrumentation and Methods for Astrophysics, 2010Co-Authors: A R Offringa, A G De Bruyn, Michael Biehl, Saleem Zaroubi, G Bernardi, V N PandeyAbstract:We describe and compare several post-correlation Radio Frequency Interference classification methods. As data sizes of observations grow with new and improved telescopes, the need for completely automated, robust methods for Radio Frequency Interference mitigation is pressing. We investigated several classification methods and find that, for the data sets we used, the most accurate among them is the SumThreshold method. This is a new method formed from a combination of existing techniques, including a new way of thresholding. This iterative method estimates the astronomical signal by carrying out a surface fit in the time-Frequency plane. With a theoretical accuracy of 95% recognition and an approximately 0.1% false probability rate in simple simulated cases, the method is in practice as good as the human eye in finding RFI. In addition it is fast, robust, does not need a data model before it can be executed and works in almost all configurations with its default parameters. The method has been compared using simulated data with several other mitigation techniques, including one based upon the singular value decomposition of the time-Frequency matrix, and has shown better results than the rest.
G Bernardi - One of the best experts on this subject based on the ideXlab platform.
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the low Frequency environment of the murchison widefield array Radio Frequency Interference analysis and mitigation
Publications of the Astronomical Society of Australia, 2015Co-Authors: A R Offringa, G Bernardi, R B Wayth, N Hurleywalker, David L Kaplan, N Barry, A P Beardsley, M E BellAbstract:This is the Accepted Manuscript version of the following article: A. R. Offringa, et al., “The low-Frequency environment of the Murchison Widefield Array: Radio-Frequency Interference analysis and mitigation”, Publications of the Astronomical Society of Australia, Vol. 32, March 2015. The final published version is available at: https://doi.org/10.1017/pasa.2015.7 © Astronomical Society of Australia 2015
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the low Frequency environment of the murchison widefield array Radio Frequency Interference analysis and mitigation
arXiv: Instrumentation and Methods for Astrophysics, 2015Co-Authors: A R Offringa, G Bernardi, R B Wayth, N Hurleywalker, David L Kaplan, N Barry, A P Beardsley, M E BellAbstract:The Murchison Widefield Array (MWA) is a new low-Frequency interferometric Radio telescope built in Western Australia at one of the locations of the future Square Kilometre Array (SKA). We describe the automated Radio-Frequency Interference (RFI) detection strategy implemented for the MWA, which is based on the AOFlagger platform, and present 72-231-MHz RFI statistics from 10 observing nights. RFI detection removes 1.1% of the data. RFI from digital TV (DTV) is observed 3% of the time due to occasional ionospheric or atmospheric propagation. After RFI detection and excision, almost all data can be calibrated and imaged without further RFI mitigation efforts, including observations within the FM and DTV bands. The results are compared to a previously published Low-Frequency Array (LOFAR) RFI survey. The remote location of the MWA results in a substantially cleaner RFI environment compared to LOFAR's Radio environment, but adequate detection of RFI is still required before data can be analysed. We include specific recommendations designed to make the SKA more robust to RFI, including: the availability of sufficient computing power for RFI detection; accounting for RFI in the receiver design; a smooth band-pass response; and the capability of RFI detection at high time and Frequency resolution (second and kHz-scale respectively).
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post correlation Radio Frequency Interference classification methods
Monthly Notices of the Royal Astronomical Society, 2010Co-Authors: A R Offringa, A G De Bruyn, Michael Biehl, Saleem Zaroubi, G Bernardi, V N PandeyAbstract:We describe and compare several post-correlation Radio Frequency Interference (RFI) classification methods. As data sizes of observations grow with new and improved telescopes, the need for completely automated, robust methods for RFI mitigation is pressing. We investigated several classification methods and find that, for the data sets we used, the most accurate among them is the SumThreshold method. This is a new method formed from a combination of existing techniques, including a new way of thresholding. This iterative method estimates the astronomical signal by carrying out a surface fit in the time-Frequency plane. With a theoretical accuracy of 95 per cent recognition and an approximately 0.1 per cent false probability rate in simple simulated cases, the method is in practice as good as the human eye in finding RFI. In addition, it is fast, robust, does not need a data model before it can be executed and works in almost all configurations with its default parameters. The method has been compared using simulated data with several other mitigation techniques, including one based upon the singular value decomposition of the time-Frequency matrix, and has shown better results than the rest.
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post correlation Radio Frequency Interference classification methods
arXiv: Instrumentation and Methods for Astrophysics, 2010Co-Authors: A R Offringa, A G De Bruyn, Michael Biehl, Saleem Zaroubi, G Bernardi, V N PandeyAbstract:We describe and compare several post-correlation Radio Frequency Interference classification methods. As data sizes of observations grow with new and improved telescopes, the need for completely automated, robust methods for Radio Frequency Interference mitigation is pressing. We investigated several classification methods and find that, for the data sets we used, the most accurate among them is the SumThreshold method. This is a new method formed from a combination of existing techniques, including a new way of thresholding. This iterative method estimates the astronomical signal by carrying out a surface fit in the time-Frequency plane. With a theoretical accuracy of 95% recognition and an approximately 0.1% false probability rate in simple simulated cases, the method is in practice as good as the human eye in finding RFI. In addition it is fast, robust, does not need a data model before it can be executed and works in almost all configurations with its default parameters. The method has been compared using simulated data with several other mitigation techniques, including one based upon the singular value decomposition of the time-Frequency matrix, and has shown better results than the rest.
C S Ruf - One of the best experts on this subject based on the ideXlab platform.
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adaptive control of undetected Radio Frequency Interference with a spaceborne microwave Radiometer
IEEE Transactions on Geoscience and Remote Sensing, 2015Co-Authors: David D Chen, C S RufAbstract:In microwave Radiometric remote sensing, undetected Radio Frequency Interference (RFI) can adversely affect the accuracy of the science products. A method is presented to adaptively tune the parameters of an RFI detection algorithm which controls the equivalent brightness temperature of undetected RFI. The method is adaptive in the sense that it adjusts to variations in the RFI environment, e.g., from high RFI conditions near some population centers to low RFI conditions in the tropical Pacific Ocean. The RFI environment is characterized by inferring the distribution of low-level undetected RFI from that of high-level detected RFI using appropriate scaling arguments. The resulting tuned algorithm adjusts its detection threshold to equalize the brightness temperature calibration bias due to RFI at the expense of the now variable measurement precision (noise equivalent delta temperature). This tradeoff between calibration bias and measurement precision can be represented as a modified version of the classic receiver-operating-characteristic curve. The Radiometer on the Aquarius/SAC-D mission is used as an example.
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Radio Frequency Interference mitigation for the soil moisture active passive microwave Radiometer
IEEE Transactions on Geoscience and Remote Sensing, 2014Co-Authors: Jeffrey R Piepmeier, Joel T Johnson, Damon Bradley, Priscilla N Mohammed, C S Ruf, Mustafa Aksoy, Rafael Garcia, Derek Hudson, Lynn Miles, Mark WongAbstract:The Soil Moisture Active Passive (SMAP) Radiometer operates in the L-band protected spectrum (1400-1427 MHz) that is known to be vulnerable to Radio-Frequency Interference (RFI). Although transmissions are forbidden at these frequencies by international regulations, ground-based, airborne, and spaceborne Radiometric observations show substantial evidence of out-of-band emissions from neighboring transmitters and possibly illegally operating emitters. The spectral environment that SMAP faces includes not only occasional large levels of RFI but also significant amounts of low-level RFI equivalent to a brightness temperature of 0.1-10 K at the Radiometer output. This low-level Interference would be enough to jeopardize the success of a mission without an aggressive mitigation solution, including special flight hardware and ground software with capabilities of RFI detection and removal. SMAP takes a multidomain approach to RFI mitigation by utilizing an innovative onboard digital detector back end with digital signal processing algorithms to characterize the time, Frequency, polarization, and statistical properties of the received signals. Almost 1000 times more measurements than what is conventionally necessary are collected to enable the ground processing algorithm to detect and remove harmful Interference. Multiple RFI detectors are run on the ground, and their outputs are combined for maximum likelihood of detection to remove the RFI within a footprint. The capabilities of the hardware and software systems are successfully demonstrated using test data collected with a SMAP Radiometer engineering test unit.
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an improved Radio Frequency Interference model reevaluation of the kurtosis detection algorithm performance under central limit conditions
IEEE Transactions on Geoscience and Remote Sensing, 2012Co-Authors: Sidharth Misra, R D De Roo, C S RufAbstract:Recent airborne field campaigns making passive microwave measurements have observed some Radio Frequency Interference (RFI) that remained undetected by the kurtosis RFI-detection algorithm. The current pulsed-sinusoidal model for RFI does not explain this anomalous behavior of the detection algorithm. In this paper, a new RFI model is developed that takes into account multiple RFI sources within an antenna footprint. The performance of the kurtosis algorithm with the new model is evaluated. The behavior of the kurtosis detection algorithm under central-limit conditions due to multiple sources is experimentally verified. The new RFI model offers a plausible explanation for the lack of detection by the kurtosis algorithm of the RFI otherwise observed.
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airborne l band Radio Frequency Interference observations from the smapvex08 campaign and associated flights
IEEE Transactions on Geoscience and Remote Sensing, 2011Co-Authors: James Park, Sidharth Misra, Joel T Johnson, N Niamsuwan, Jeffrey R Piepmeier, Priscilla N Mohammed, C S Ruf, Ninoslav Majurec, S H Yueh, S J DinardoAbstract:Statistics of Radio Frequency Interference (RFI) observed in the band 1398-1422 MHz during an airborne campaign in the United States are reported for use in analysis and forecasting of L-band RFI for microwave Radiometry. The observations were conducted from September to October 2008, and included approximately 92 h of flight time, of which approximately 20 h of “transit” or dedicated RFI observing flights are used in compiling the statistics presented. The observations used include outbound and return flights from Colorado to Maryland, as well as RFI surveys over large cities. The Passive Active L-Band Sensor (PALS) Radiometer of NASA Jet Propulsion Laboratory augmented by three dedicated RFI observing systems was used in these observations. The complete system as well as the associated RFI characterization approaches are described, along with the resulting RFI statistical information and examinations of specific RFI sources. The results show that RFI in the protected L-band spectrum is common over North America, although the resulting Interference when extrapolated to satellite observations will appear as “low-level” corruption that will be difficult to detect for traditional Radiometer systems.
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characterization of k band Radio Frequency Interference from amsr e windsat and ssm i
International Geoscience and Remote Sensing Symposium, 2010Co-Authors: Darren Mckague, John Puckett, C S RufAbstract:An algorithm to detect Radio-Frequency Interference in microwave Radiometer brightness temperatures is developed and applied to K-band observations from AMSR-E, WindSat and SSM/I. This algorithm uses the monthly peak difference between co-polar brightness temperatures at 22 and 19 GHz to find RFI. Data from July 2005, July 2008, and January 2008 are shown. Less K-band RFI is seen in SSM/I data than in WindSat or AMSR-E data, likely due to differences in K-band center Frequency and spatial resolution. A significant source of RFI is present in the 2008 and 2009 AMSR-E and WindSat data that was not present in 2005. This is likely due to transmissions from the DirecTV 10 satellite, which was launched in July of 2007. This RFI source is seen in reflection off of the Earth's surface. This reflection is strongest over ocean, but is also seen over snow where the diffuse component of the reflection creates a relatively wide swath of RFI.
