X. Bosch-Lluis

New Instrument Concepts for Ocean Sensing: Analysis of the PAU-Radiometer

Sea surface salinity can be remotely measured by means of L-band microwave radiometry. However, the brightness temperature also depends on the sea surface temperature and on the sea state, which is probably today one of the driving factors in the salinity retrieval error budgets of the European Space Agencys Soil Moisture and Ocean Salinity (SMOS) mission and the NASA-Comision Nacional de Actividades Espaciales Aquarius/SAC-D mission. This paper describes the Passive Advanced Unit (PAU) for ocean monitoring. PAU combines in a single instrument three different sensors: an L-band radiometer with digital beamforming (DBF) (PAU-RAD) to measure the brightness temperature of the sea at different incidence angles simultaneously, a global positioning system (GPS) reflectometer [PAU-reflectometer of Global Navigation Satellite Signals (GNSS-R)] also with DBF to measure the sea state from the delay-Doppler maps, and two infrared radiometers to provide sea surface temperature estimates. The key characteristic of this instrument is that both PAU-RAD and the PAU-GNSS/R share completely the RF/IF front-end, and analog-to-digital converters. Since in order to track the GPS-reflected signal, it is not possible to chop the antenna signal as in a Dicke radiometer, a new radiometer topology has been devised which makes uses of two receiving chains and a correlator, which has the additional advantage that both PAU-RAD and PAU-GNSS/R can be operated continuously and simultaneously to perform the sea-state corrections of the brightness temperature. This paper presents the main characteristics of the different PAU subsystems, and analyzes in detail the PAU-radiometer concept.

Calibration of Correlation Radiometers Using Pseudo-Random Noise Signals

The calibration of correlation radiometers, and particularly aperture synthesis interferometric radiometers, is a critical issue to ensure their performance. Current calibration techniques are based on the measurement of the cross-correlation of receivers’ outputs when injecting noise from a common noise source requiring a very stable distribution network. For large interferometric radiometers this centralized noise injection approach is very complex from the point of view of mass, volume and phase/amplitude equalization. Distributed noise injection techniques have been proposed as a feasible alternative, but are unable to correct for the so-called “baseline errors” associated with the particular pair of receivers forming the baseline. In this work it is proposed the use of centralized Pseudo-Random Noise (PRN) signals to calibrate correlation radiometers. PRNs are sequences of symbols with a long repetition period that have a flat spectrum over a bandwidth which is determined by the symbol rate. Since their spectrum resembles that of thermal noise, they can be used to calibrate correlation radiometers. At the same time, since these sequences are deterministic, new calibration schemes can be envisaged, such as the correlation of each receiver’s output with a baseband local replica of the PRN sequence, as well as new distribution schemes of calibration signals. This work analyzes the general requirements and performance of using PRN sequences for the calibration of microwave correlation radiometers, and particularizes the study to a potential implementation in a large aperture synthesis radiometer using an optical distribution network.

Improving the accuracy of sea surface salinity retrieval using GNSS‐R data to correct the sea state effect

[1]xa0Reflectometry using GNSS signals of opportunity (GNSS-R) has stood as a powerful technique for ocean remote sensing. Particularly, the use of these techniques has been proposed to retrieve sea state information (i.e. sea surface roughness) among other applications. Precise knowledge of the sea state is a key issue to process L-band radiometric measurements for sea surface salinity retrieval. It has been recently shown that GNSS-R data can be directly linked to the brightness temperature variations caused by the sea state effect, without the use of emission/scattering models or sea spectra models. In this study, this approach is applied to CoSMOS 2007 flights data. Firstly, the radiometric and GNSS-R data sets are presented. Secondly, measured brightness temperature is corrected using the collocated GNSS-R data. In particular, the area under the normalized waveforms is used to directly compute the required brightness temperature correction. Thirdly, the salinity retrievals are presented (achieving an error reduction from 2.8 psu for the raw measurements down to 0.51 psu). Finally, the obtained results are compared with the WISE correction approach, based on the wind speed correction, and the conclusions of this work are presented.

PAU instrument aboard INTA MicroSat-1: A GNSS-R demonstration mission for sea state correction in L-band radiometry

Global Navigation Satellite System (GNSS) Reflectometry was originally proposed for mesoscale altimetry, but today its feasibility for sea state, soil moisture, vegetation and snow height has already been demonstrated. This paper describes a GNSS-Reflectometer develop to perform the sea state correction in L-band radiometric measurements, and therefore, improve the quality of the sea surface salinity retrievals. The instrument is currently being developed as a secondary payload to be launched aboard INTA (Instituto Nacional de Técnicas Aerospaciales, Spanish Aerospace Center) MicroSat-1. The basic principles of operation and the instrument development status are presented.

Soil moisture and vegetation height retrieval using GNSS-R techniques

Global Navigation Satellite Signals Reflections (GNSS-R) techniques are currently being used for remote sensing purposes retrieving geophysical parameters over different types of surfaces. Over the ocean, sea state information can be retrieved to improve the ocean salinity retrieval. Furthermore, over land these techniques can be used to retrieve soil moisture. This paper presents the theoretical and experimental results of using GNSS-R to retrieve soil moisture when vegetation is present. The particular technique being applied in this study is the Interference Pattern Technique (IPT) that measures the interference pattern of the GPS direct and reflected signals, after reflecting over the surface.

Study of maize plants effects in the retrieval of soil moisture using the interference pattern GNSS-R technique

The use of Global Navigation Satellite Signals Reflections (GNSS-R) techniques to retrieve geophysical parameters from surfaces has been increased in the recent years. These techniques have resulted in suitable tools to obtain information about the sea state of oceans, which is very useful to improve the ocean salinity retrieval [1–3], and also, information about the soil moisture [4–6] of lands. The present work focuses on the use of the Interference Pattern Technique (IPT) [7–10], a particular type of GNSS-R technique, to study vegetation-covered soils. The IPT consists mainly of the measurement of the interference pattern between the GPS direct and reflected signals (the interference power), after they impinge over the ensemble soil surface and vegetation layer. The measured interference signal provides information on the soil moisture of the surface and also, on the vegetation height.

Brightness temperature correction of the sea state effect using GNSS-R data

Sea Surface Salinity (SSS) is a very important océanographie parameter that can be measured using L-band microwave radiometry. The measured brightness temperature measured over the ocean is influenced by the sea state that can even mask the salinity signature. Reflectometry using navigation signals (GNSS-R) has been proven to achieve sea state determination and has been proposed to be used to correct the measured brightness temperature for the sea state effect. In this framework, the Advanced L-BAnd emissiviTy and Reflectivity Observations of the Sea Surface 2009 (ALBATROSS 2009) field experiment was undertaken collecting an extensive dataset of collocated radiometnc and reflectometnc measurements. In this paper the experimental results and mam conclusions of the ALBATROSS 2009 field experiment are presented.

PAU-SA: A Synthetic Aperture Interferometric Radiometer Test Bed for Potential Improvements in Future Missions

The Soil Moisture and Ocean Salinity (SMOS) mission is an Earth Explorer Opportunity mission from the European Space Agency (ESA). Its goal is to produce global maps of soil moisture and ocean salinity using the Microwave Imaging Radiometer by Aperture Synthesis (MIRAS). The purpose of the Passive Advanced Unit Synthetic Aperture (PAU-SA) instrument is to study and test some potential improvements that could eventually be implemented in future missions using interferometric radiometers such as the Geoestacionary Atmosferic Sounder (GAS), the Precipitation and All-weather Temperature and Humidity (PATH) and the Geostationary Interferometric Microwave Sounder (GIMS). Both MIRAS and PAU-SA are Y-shaped arrays with uniformly distributed antennas, but the receiver topology and the processing unit are quite different. The purpose of this work is to identify the elements in the MIRASs design susceptible of improvement and apply them in the PAU-SA instrument demonstrator, to test them in view of these future interferometric radiometer missions.

Altimetry study performed using an airborne GNSS-Reflectometer

The Global Navigation Satellite Signals Reflections (GNSS-R) techniques have been widely used for remote sensing purposes retrieving geophysical parameters over different types of surfaces. Over the ocean, altimetry [1, 2] or sea state [3, 4] can be retrieved. Over land, soil moisture [5, 6] can be inferred and over ice, altimetry, and ice age [7] are also retrieved. This paper presents the results of using GNSS-R techniques to retrieve altimetry from the measurements of an airborne GNSS-Reflectometer.

Delay-Doppler Maps study over ocean, land and ice from space

This work analyzes the properties of the Delay-Doppler Maps (DDM) derived from the limited experimental data freely available from the UK-DMC. The quality of the received signal over ocean, land and ice is evaluated. In this study the minimum number of incoherent integrations after 1 ms basic coherent integration that are needed to obtain a quality DDM over each surface type is determined using three different techniques: studying the volume of the DDM against the incoherent integration time, observing the signal-to-noise ratio of the signal, and finally analyzing two pixels of the DDM, the maximum and another one noisier, and performing histograms of these points as a function of the incoherent integration time.