65 research outputs found

    Analysis of RFI Identification and Mitigation in CAROLS Radiometer Data Using a Hardware Spectrum Analyser

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    A method to identify and mitigate radio frequency interference (RFI) in microwave radiometry based on the use of a spectrum analyzer has been developed. This method has been tested with CAROLS L-band airborne radiometer data that are strongly corrupted by RFI. RFI is a major limiting factor in passive microwave remote sensing interpretation. Although the 1.400–1.427 GHz bandwidth is protected, RFI sources close to these frequencies are still capable of corrupting radiometric measurements. In order to reduce the detrimental effects of RFI on brightness temperature measurements, a new spectrum analyzer has been added to the CAROLS radiometer system. A post processing algorithm is proposed, based on selective filters within the useful bandwidth divided into sub-bands. Two discriminant analyses based on the computation of kurtosis and Euclidian distances have been compared evaluated and validated in order to accurately separate the RF interference from natural signals

    CAROLS: A New Airborne L-Band Radiometer for Ocean Surface and Land Observations

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    The “Cooperative Airborne Radiometer for Ocean and Land Studies” (CAROLS) L-Band radiometer was designed and built as a copy of the EMIRAD II radiometer constructed by the Technical University of Denmark team. It is a fully polarimetric and direct sampling correlation radiometer. It is installed on board a dedicated French ATR42 research aircraft, in conjunction with other airborne instruments (C-Band scatterometer—STORM, the GOLD-RTR GPS system, the infrared CIMEL radiometer and a visible wavelength camera). Following initial laboratory qualifications, three airborne campaigns involving 21 flights were carried out over South West France, the Valencia site and the Bay of Biscay (Atlantic Ocean) in 2007, 2008 and 2009, in coordination with in situ field campaigns. In order to validate the CAROLS data, various aircraft flight patterns and maneuvers were implemented, including straight horizontal flights, circular flights, wing and nose wags over the ocean. Analysis of the first two campaigns in 2007 and 2008 leads us to improve the CAROLS radiometer regarding isolation between channels and filter bandwidth. After implementation of these improvements, results show that the instrument is conforming to specification and is a useful tool for Soil Moisture and Ocean Salinity (SMOS) satellite validation as well as for specific studies on surface soil moisture or ocean salinity

    Remote sensing for agriculture, ecosystems, and hydrology XVII

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    GLORI (GLObal navigation satellite system Reflectometry Instrument) is a new receiver dedicated to the airborne measurement of surface parameters such as soil moisture, above ground biomass, and continental water levels as well as sea state (wave height and direction) above oceans. The instrument is based on the PARIS concept [1] using both the direct and surface-reflected L-band signals from the GPS constellation as a multistatic radar source. A test campaign has been performed in November 2014, and the results show a great potential for reflectometry applications

    Analysis of RFI identification and mitigation in CAROLS radiometer data using a hardware spectral analyser

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    International audienceA method based on the use of a spectral analyzer has been developed in order to identify and mitigate radio frequency interference (RFI) in microwave radiometry. This method has been tested with L-band CAROLS airborne data highly corrupted by interferences. RFI is a major limiting factor in passive microwave remote sensing. Although the 1.4-1.427 GHz bandwidth is protected, RFI sources close to these frequencies may still corrupt radiometer measurements. In order to reduce RFI bad effects on the brightness temperature measurements, a new instrument called spectral analyzer has been added to the CAROLS radiometer system. A post processing algorithm based on a selective filtering with the division of bandwidth in subbands is proposed. Two discriminant analysis based on the computation of kurtosis and Mahalanobis distance have been compared, evaluated and validated in order to separate accurately the RF interference with natural signal

    Analysis of RFI Issue Using the CAROLS L-Band Experiment

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    International audienceIn this paper, different methods are proposed for the detection and mitigation of the undesirable effects of radio-frequency interference (RFI) in microwave radiometry. The first of these makes use of kurtosis to detect the presence of non-Gaussian signals, whereas the second imposes a threshold on the standard deviation of brightness temperatures in order to distinguish natural-emission variations from RFI. Finally, the third approach is based on the use of a threshold applied to the third and fourth Stokes parameters. All these methods have been applied and tested, with the cooperative airborne radiometer for ocean and land studies radiometer operating in the L-band, on the data acquired during airborne campaigns made in the spring of 2009 over the southwest of France. The performance of each approach, or of two combined approaches, is analyzed with our database. We thus show that the kurtosis method is well suited to detect pulsed RFI, whereas the method based on the second moment of brightness temperatures seems to be better suited to detect continuous-wave RFI in airborne brightness-temperature measurements

    Low-cost GPS receivers for the monitoring of sunflower cover dynamics

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    The aim of this research is to analyze the potential use of Global Navigation Satellite System (GNSS) signals for the monitoring of in situ vegetation characteristics. An instrument, based on the use of a pair of low-cost receivers and antennas, providing continuous measurements of all the available Global Positioning System (GPS) satellite signals is proposed for the determination of signal attenuation caused by a sunflower cover. Experimental campaigns with this instrument, combined with ground truth measurements of the vegetation, were performed over a nonirrigated sunflower test field for a period of more than two months, corresponding to a significant portion of the vegetation cycle. A method is proposed for the analysis of the signal attenuation data as a function of elevation and azimuth angles. A high correlation is observed between the vegetation's water content and the GPS signals attenuation, and an empirical modeling is tested for the retrieval of signal behavior as a function of vegetation water content (VWC). The VWC was estimated from GNSS signals on a daily basis, over the full length of the study period
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