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Halimi A.,Tesa | Mailhes C.,Tesa | Tourneret J.-Y.,Tesa | Boy F.,French National Center for Space Studies | Moreau T.,Collecte Localisation Satellite CLS
International Geoscience and Remote Sensing Symposium (IGARSS) | Year: 2014

This paper introduces a new model for delay/Doppler altimetry, taking into account the effect of antenna mispointing. After defining the proposed model, the effect of the antenna mispointing on the altimetric waveform is analyzed as a function of along-track and across-track angles. Two least squares approaches are investigated for estimating the parameters associated with the proposed model. The first algorithm estimates four parameters including the across-track mispointing (which affects the echo's shape). The second algorithm uses the mispointing angles provided by the star-trackers and estimates the three remaining parameters. The proposed model and algorithms are validated via simulations conducted on both synthetic and real data. © 2014 IEEE. Source


Halimi A.,Tesa | Mailhes C.,Tesa | Tourneret J.-Y.,Tesa | Thibaut P.,Collecte Localisation Satellite CLS
International Geoscience and Remote Sensing Symposium (IGARSS) | Year: 2011

Coastal altimetric waveforms may be corrupted by peaks. A simple parametric model was recently introduced to model peaky altimetric waveforms. This model assumes that the received altimetric waveform is the sum of a Brown echo and a Gaussian peak. This model has provided interesting results for symmetric peaks affecting altimetric signals. However, it is not appropriate for altimetric signals corrupted by asymmetric peaks. This paper introduces a Brown with asymmetric Gaussian peak model for altimetric waveforms. The parameters of this model are estimated by a maximum likelihood estimator. The performance of the proposed model and the resulting estimation strategy is evaluated via simulations conducted on synthetic and real data. © 2011 IEEE. Source


Tourneret J.-Y.,Tesa | Mailhes C.,Tesa | Severini J.,Tesa | Thibaut P.,Collecte Localisation Satellite CLS
International Geoscience and Remote Sensing Symposium (IGARSS) | Year: 2010

This paper addresses the problem of classifying altimetric signals according to their shapes. The proposed classifier is divided into three steps. A one-class support vector machine method is first used to isolate the large amount of Brown-like echoes from others signals which are considered as outliers. The second step extracts pertinent features from the the remaining echoes (which cannot be well described by the Brown model). These features are projected onto discriminant axes using linear discriminant analysis. The final step classifies the projected feature vectors using a standard Bayesian classifier. The proposed three step classification strategy is evaluated on supervised real altimetric echoes. © 2010 IEEE. Source


Struve J.,Imperial College London | Lorenzen K.,Imperial College London | Blanchard J.,Imperial College London | Borger L.,University of Guelph | And 12 more authors.
Biology Letters | Year: 2010

The workshop 'Spatial models in animal ecology, management and conservation' held at Silwood Park (UK), 9-11 March 2010, aimed to synthesize recent progress in modelling the spatial dynamics of individuals, populations and species ranges and to provide directions for research. It brought together marine and terrestrial researchers working on spatial models at different levels of organization, using empirical as well as theory-driven approaches. Different approaches, temporal and spatial scales, and practical constraints predominate at different levels of organization and in different environments. However, there are theoretical concepts and specific methods that can fruitfully be transferred across levels and systems, including: habitat suitability characterization, movement rules, and ways of estimating uncertainty. © 2010 The Royal Society. Source


Tournadre J.,French Research Institute for Exploitation of the Sea | Poisson J.C.,Collecte Localisation Satellite CLS | Steunou N.,French National Center for Space Studies | Picard B.,Collecte Localisation Satellite CLS
Marine Geodesy | Year: 2015

The major drawback of Ka band, operating frequency of the AltiKa altimeter on board SARAL, is its sensitivity to atmospheric liquid water. Even light rain or heavy clouds can strongly attenuate the signal and distort the signal leading to erroneous geophysical parameters estimates. A good detection of the samples affected by atmospheric liquid water is crucial. As AltiKa operates at a single frequency, a new technique based on the detection by a Matching Pursuit algorithm of short scale variations of the slope of the echo waveform plateau has been developed and implemented prelaunch in the ground segment. As the parameterization of the detection algorithm was defined using Jason-1 data, the parameters were re-estimated during the cal-val phase, during which the algorithm was also updated. The measured sensor signal-to-noise ratio is significantly better than planned, the data loss due to attenuation by rain is significantly smaller than expected (<0.1%). For cycles 2 to 9, the flag detects about 9% of 1Hz data, 5.5% as rainy and 3.5 % as backscatter bloom (or sigma0 bloom). The results of the flagging process are compared to independent rain data from microwave radiometers to evaluate its performances in term of detection and false alarms. © 2015, Copyright © Taylor & Francis Group, LLC. Source

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