Gisela Carvajal - Academia.edu (original) (raw)

Papers by Gisela Carvajal

Wind velocity measurements at 10 meters over the ocean surface represent an important parameter t... more Wind velocity measurements at 10 meters over the ocean surface represent an important parameter to study the ocean behavior. Wind vector fields are available from different sources, such as satellite derived measurements and weather forecast models. Nevertheless, the limited availability in time, low spatial resolution and poor coverage close to the coasts motivate research on the use of Synthetic Aperture Radar (SAR) for wind velocity retrieval. This report presents an description and assessment of a wind velocity algorithm implemented for C-band (frequency 4–8 GHz) SAR data. Results obtained with the algorithm are compared and validated with wind velocity estimates from the Global Forecast System (GFS) model and the Advanced SCATterometer (ASCAT) sensor on-board the MetOp-A satellite. The statistical results show that the wind velocity retrievals are in very good agreement with the validation data when the wind field is slowly varying, leading to a bias in the wind speed smaller t...

2021 IEEE Radar Conference (RadarConf21), 2021

Intelligent transportation is heavily reliant on radar, which have unique robustness under heavy ... more Intelligent transportation is heavily reliant on radar, which have unique robustness under heavy rain/fog/snow and poor light conditions. With the rapid increase of the number of radars used on modern vehicles, most operating in the same frequency band, the risk of radar interference becomes an important issue. As in radio communication, interference can be mitigated through coordination. We present and evaluate two approaches for radar interference coordination, one for FMCW and one for OFDM, and highlight their challenges and opportunities.

Using sea surface temperature from satellite images to retrieve sea surface currents is not a new... more Using sea surface temperature from satellite images to retrieve sea surface currents is not a new idea, but so far its operational near-real-time implementation has not been possible. Validation studies are too region specific or uncertain, sometimes because of the satellite images themselves. Moreover, the sensitivity of the most common retrieval method, the maximum cross correlation, to the parameters that have to be set is unknown. Using model outputs instead of satellite images, biases induced by this method are assessed here, for four different seas of western Europe, and the best of nine settings and eight temporal resolutions are determined. The regions with strong currents return the most accurate results when tracking a 20-km pattern between two images separated by 6–9 h. The regions with weak currents favor a smaller pattern and a shorter time interval, although their main problem is not inaccurate results but missing results: where the velocity is too low to be picked by the retrieval. The results are not impaired by the restrictions imposed by ocean surface current dynamics and available satellite technology, indicating that automated sea surface current retrieval from sea surface temperature images is feasible, for pollution confinement, search and rescue, and even for more energy-efficient and comfortable ship navigation.

The European Community’s Seventh Framework Programme project SECTRONIC will provide information o... more The European Community’s Seventh Framework Programme project SECTRONIC will provide information on safety and security to maritime infrastructures at a global scale. Focus of this paper is on two implemented algorithms that employ data from Synthetic Aperture Radar (SAR) sensors. The first algorithm retrieves wind direction directly from the SAR image using standard image processing techniques. Wind speed is estimated by the inversion of a geophysical model function (GMF), having wind direction estimates as an input. Operational implemetation of mentioned algorithms is described and an example of results is provided.

2020 IEEE Radar Conference (RadarConf20)

IEEE Signal Processing Magazine

Autonomous driving relies on a variety of sensors, especially on radars, which have unique robust... more Autonomous driving relies on a variety of sensors, especially on radars, which have unique robustness under heavy rain/fog/snow and poor light conditions. With the rapid increase of the amount of radars used on modern vehicles, where most radars operate in the same frequency band, the risk of radar interference becomes a compelling issue. This article analyses automotive radar interference and proposes several new approaches, which combine industrial and academic expertise, toward the path of interference-free autonomous driving. INTRODUCTION AND MOTIVATION Radar is becoming the standard equipment in all modern cars, supporting, e.g., cruise control and collision avoidance in most weather conditions whilst providing high-resolution detections on the order of centimeters in the millimeter-wave (mmWave) band. The next generation of Advanced Driver Assistance (ADAS) and Autonomous Drive (AD) vehicles will have a multitude of radars covering multiple safety and comfort applications like crash-avoidance, self-parking, in-cabin monitoring, cooperative driving, collective situational awareness and more. Since automotive radar transmissions are uncoordinated, there is a non-negligible probability of interference among vehicles, as shown in Fig. 1. While current automotive radars are already impacted by interference to some extent, it is today unlikely to get issues noticeable to the customer as the state-of-the-art automotive radars are continuously updated and improved on multiple system levels. However, the mutual interference problem is expected to become more challenging, unless properly handled, as more vehicles are equipped with a larger number of radars providing 360 • situational awareness at various distances to enable more advanced future ADAS and AD functionalities.

2016 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), 2016

Estimation of surface currents still presents a challenge. In this work validates surface current... more Estimation of surface currents still presents a challenge. In this work validates surface current estimates from the Maximum Cross Correlation (MCC) method, that uses spaceborne radiometer data, against ground-based retrievals from a High Frequency (HF) radar system. Moreover, these datasets have been compared with surface current data from two assimilated satellite products and four weather prediction models. The comparison shows large differences in the spatial resolution and the location of specific features. It is concluded that the variation of the observations may be due to the difference between the measuring or estimated method used in each case and the forces driving them.

2013 IEEE International Geoscience and Remote Sensing Symposium - IGARSS, 2013

ABSTRACT The understanding of the relationship between surface currents derived from weather mode... more ABSTRACT The understanding of the relationship between surface currents derived from weather models and remote sensing data is essential in order to produce an improved and integrated surface current information of high quality and resolution. The large availability of satellite derived infrared radiometer data at the high latitudes of the coastal waters surrounding Sweden makes the Maximum Cross Correlation (MCC) method a feasible alternative to produce real time measurements of surface currents. This work compares current retrievals from the MCC method and model data around Sweden. Our results indicate a similar magnitude for both sources of current fields in most of the locations. However, there exist small discrepancies in the localization of the larger current values. Also, the MCC retrievals generally present more features than the modeled ones. Possible reasons for these discrepancies might be the MCC detection of circulation patterns not predicted by the model, or the depreciation in the MCC performance due to the influence of diurnal variability of the sea surface temperature, wind driven mixing due to upwelling or tides.

Analysis of ocean surface dynamics has been proven to be of vital importance in many areas (e.g. ... more Analysis of ocean surface dynamics has been proven to be of vital importance in many areas (e.g. shipping, fishing). Two important parameters to describe the ocean dynamics are the wind velocity (speed and direction) and advective surface velocities (ocean current velocity). These parameters are currently provided operationally by forecast models, surface sensors (e.g. buoys, coastal radar) and satellite sensors. However, coverage limitations, low resolution and limited temporal availability impose a need for implementation and evaluation of new data sources and techniques for estimation of these parameters. In this paper we implement and evaluate known techniques for determination of wind and ocean current velocity from satellite data. Wind is determined from Synthetic Aperture Radar (SAR) data by applying two algo-rithms. First, the Local Gradient method is implemented to extract wind direction from the SAR data, and then the CMOD-5 Geophysical Model Function of the backscatter is...

2014 IEEE Geoscience and Remote Sensing Symposium, 2014

There are different parameters inherent to coastal areas that can affect the backscattering of th... more There are different parameters inherent to coastal areas that can affect the backscattering of the ocean surface detected by Synthetic Aperture Radar (SAR). The parameters include the influence of land, the influence of the SAR acquisition geometry, and the influence of backscattering features not directly related to wind variations. This work focuses on the study of the influence of those parameters for the performance of surface wind retrieval with C-band SAR data in coastal areas.

The recent observed thinning of the glacier ice shelves in the Amundsen Sea (Antarctica) has been... more The recent observed thinning of the glacier ice shelves in the Amundsen Sea (Antarctica) has been attributed to warm deep currents, possibly induced by along-coast winds in the vicinity of the glacial ice sheet. Here, high resolution maps of wind fields derived from Synthetic Aperture Radar (SAR) data have been studied and correlated with subsurface measurements of the deep water velocities in the Amundsen Sea area. Focus is on periods with low ice coverage in 2010 and 2011. In 2010, which had comparatively low ice coverage, the results indicate a more rapid response to wind forcing in the deep currents than in 2011. The SAR wind speed maps have better spatial resolution than available reanalysis data, and higher maximum correlation was obtained with SAR data than with reanalysis data despite the lower temporal resolution. The maximum correlation was R = 0.71, in a direction that is consistent with wind-driven Ekman theory. This is significantly larger than in previous studies. The larger correlation could be due to the better spatial resolution or the restriction to months with minimum ice coverage. The results indicate that SAR is a useful complement to infer the subsurface variability of the ocean circulation in remote areas in polar oceans.

Journal of Physical Oceanography, 2013

The ice shelves in the Amundsen Sea are thinning rapidly, and the main reason for their decline a... more The ice shelves in the Amundsen Sea are thinning rapidly, and the main reason for their decline appears to be warm ocean currents circulating below the ice shelves and melting these from below. Ocean currents transport warm dense water onto the shelf, channeled by bathymetric troughs leading to the deep inner basins. A hydrographic mooring equipped with an upward-looking ADCP has been placed in one of these troughs on the central Amundsen shelf. The two years (2010/11) of mooring data are here used to characterize the inflow of warm deep water to the deep shelf basins. During both years, the warm layer thickness and temperature peaked in austral fall. The along-trough velocity is dominated by strong fluctuations that do not vary in the vertical. These fluctuations are correlated with the local wind, with eastward wind over the shelf and shelf break giving flow toward the ice shelves. In addition, there is a persistent flow of dense lower Circumpolar Deep Water (CDW) toward the ice s...

IEEE Transactions on Geoscience and Remote Sensing, 2000

ABSTRACT Wind vector fields derived from synthetic aperture radar (SAR) sensors show variations a... more ABSTRACT Wind vector fields derived from synthetic aperture radar (SAR) sensors show variations at smaller scales than most other globally available surface wind sources. However, few studies have been devoted to the investigation of the accuracy of SAR-derived wind fields at different scales and how they compare with other wind data. In order to investigate these issues, an algorithm for the retrieval of SAR-derived wind vectors has been developed, and a quality assessment between the retrievals and in situ, scatterometer, and numerical weather model (NWM) wind data has been performed. The implemented wind retrieval algorithm detects streak features in the SAR image to estimate wind directions and inverts wind speeds using CMOD-IFR2, CMOD5, or CMOD5.N geophysical model functions. In addition, a regularization method for filtering outliers in the wind direction retrievals is used. Retrievals compared with in situ data indicated better performance at offshore locations for wind speed inversions with CMOD5.N. The bias and standard deviation for offshore regularized wind directions and CMOD5.N speeds are 9° and 25° and -0.1 and 1.4 m/s, respectively. The comparison with the scatterometer and NWM wind data has been performed for retrievals at 5-, 10-, and 20-km resolution. The results indicate a better agreement of the coarser retrievals with the reference data. Nevertheless, mapping of smaller scale features requires wind directions from the SAR image itself.

IEEE Geoscience and Remote Sensing Letters, 2000

We propose a compression algorithm for hyperspectral images featuring both lossy and near-lossles... more We propose a compression algorithm for hyperspectral images featuring both lossy and near-lossless compression. The algorithm is based on JPEG 2000 and provides better near-lossless compression performance than 3D-CALIC. We also show that its effect on the results of selected applications is negligible and, in some cases, better than JPEG 2000.