Mark Wong
Goddard Space Flight Center
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IEEE Transactions on Geoscience and Remote Sensing | 2014
Jeffrey R. Piepmeier; Joel T. Johnson; Priscilla N. Mohammed; Damon Bradley; Christopher S. Ruf; Mustafa Aksoy; Rafael Garcia; Derek Hudson; Lynn Miles; Mark Wong
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.
international geoscience and remote sensing symposium | 2010
Damon Bradley; Cliff Brambora; Mark Wong; Lynn Miles; David Durachka; Brian Farmer; Priscilla N. Mohammed; Jeff Piepmier; Jim Medeiros; Neil Martin; Rafael Garcia
The presence of anthropogenic RFI is expected to adversely impact soil moisture measurement by NASAs Soil Moisture Active Passive mission. The digital signal processing approach and preliminary design for detecting and mitigating this RFI is presented in this paper. This approach is largely based upon the work of Johnson [1] and Ruf [2].
2016 14th Specialist Meeting on Microwave Radiometry and Remote Sensing of the Environment (MicroRad) | 2016
Adam J. Schoenwald; Damon Bradley; Priscilla N. Mohammed; Jeffrey R. Piepmeier; Mark Wong
In the field of microwave radiometry, Radio Frequency Interference (RFI) consistently degrades the value of scientific results. Through the use of digital receivers and signal processing, the effects of RFI on scientific measurements can be reduced depending on certain circumstances. As technology allows us to implement wider band digital receivers for radiometry, the problem of RFI mitigation changes. Our work focuses on finding a detector that outperforms real kurtosis in wide band scenarios. The algorithm implemented is a complex signal kurtosis detector which was modeled and simulated. The performance of both complex and real signal kurtosis is evaluated for continuous wave, pulsed continuous wave, and wide band quadrature phase shift keying (QPSK) modulations. The use of complex signal kurtosis increased the detectability of interference.
international geoscience and remote sensing symposium | 2015
Damon Bradley; Adam J. Schoenwald; Mark Wong; Priscilla N. Mohammed; Jeffrey R. Piepmeier
RFI is a persistent and growing problem experienced by spaceborne microwave radiometers. Recent missions such as SMOS, SMAP, and GPM have all detected RFI in L, C, X, and K bands. To proactively deal with this issue, microwave radiometers must include digital back-end processors that generate data products that facilitate the detection and excision of RFI from desired brightness temperature measurements. The wideband digital signal processing testbed is a platform that allows rapid development of various RFI detection and mitigation algorithms using digital hardware akin to that which might be used for final spaceflight implementation. On it, we evaluate an improved version of the SMAP RFI Digital Signal Processor (DSP) that utilizes the new complex signal kurtosis algorithm as opposed to the real signal kurtosis that is used on the SMAP radiometer. In addition, we show how we scale the DSP to operate at 8.3 times the bandwidth of the SMAP radiometer for operation in K-band.
international geoscience and remote sensing symposium | 2016
Lynn Miles; Mark Wong; Albert Wu; Eugenia DeMarco; Edward J. Kim; Tammy Haynes
Scanning L-band Active/Passive (SLAP) is an airborne remote sensing instrument developed at NASA Goddard Space Flight Center specifically as an airborne simulator of the Soil Moisture Active/Passive (SMAP) satellite instrument suite, for remote sensing of soil moisture, freeze-thaw state, ocean salinity, sea ice, and other physical phenomena that display characteristics at microwave L-band. This paper will present example observations from a recent soil freeze-thaw campaign in Winnipeg, Manitoba, Canada, as well as detail enhancements made to the SLAP RFI processor beyond the capabilities of the SMAP RFI processor.
2016 Radio Frequency Interference (RFI) | 2016
Adam J. Schoenwald; Armen Gholian; Damon Bradley; Mark Wong; Priscilla N. Mohammed; Jeffrey R. Piepmeier
Radio-frequency interference (RFI) has negatively impacted scientific measurements of passive remote sensing satellites. This has been observed in the L-band radiometers Microwave Imaging Radiometer with Aperture Synthesis (MIRAS) for the Soil Moisture and Ocean Salinity (SMOS) mission, Aquarius and more recently, Soil Moisture Active Passive (SMAP). RFI has also been observed at higher frequencies such as K band. Improvements in technology have allowed wider bandwidth digital back ends for passive microwave radiometry. A radio frequency interference detector based on complex signal kurtosis was developed to help identify corrupted measurements. This work explores the use of Independent Component Analysis (ICA) as a blind source separation (BSS) technique to pre-process radiometric signals for use with the previously developed real and complex signal kurtosis detectors.
international geoscience and remote sensing symposium | 2012
Damon Bradley; Cliff Brambora; Ali Feizi; Rafael Garcia; Lynn Miles; Priscilla N. Mohammed; Jinzheng Peng; Jeffrey R. Piepmeier; Kamdin B. Shakoorzadeh; Mark Wong
SMAP is one of four Tier-1 missions recommended by the National Research Councils Committee on Earth Science and Applications from Space [1]. The mission consists of a spacecraft with two instruments: an active L-band 1.26 GHz synthetic aperture radar and a passive L-band radiometer that operates in the 1.400 to 1.427 GHz microwave band. The goal of the mission is to use data derived from both instruments to construct high-resolution, high-accuracy global maps of soil moisture and freeze/thaw states over a 3 year mission duration. The SMAP radiometer has an entirely digital back-end processor that builds upon the findings by Misra et. al. [2], [3] for its digital signal processing (DSP) and radio frequency interference (RFI) mitigation. The implementation of this radiometer is currently under way and the mission is scheduled to launch in 2015. This paper summarizes the design and performance results of the RDE engineering test unit (ETU).
biomedical engineering and informatics | 2015
Amir H. Kashani; Mark Wong; Nicole Koulisis; Chein-I Chang; Gabriel Martin; Mark S. Humayun
Investigative Ophthalmology & Visual Science | 2014
Amir H. Kashani; Mark Wong; Mark S. Humayun
Investigative Ophthalmology & Visual Science | 2013
Mark Wong; Carol Y. Cheung; Yi-Ting Ong; Saima Hilal; Yingfeng Zheng; Merwyn Chew; Philip Yap; Dennis Seow; Christopher Chen; Tien Wong