Alberto Lupidi

Advanced Polarimetric Doppler Weather Radar Simulator

The Advanced Polarimetric Doppler Weather Radar Simulator (APDWRS) capable of generating I&Q time series voltages for a ground based fully-polarimetric Doppler weather radar is described in this paper. The Weather Research and Forecast (WRF) model is used in conjunction with the T-Matrix code to generate radar signals according to the propagation-modified covariance matrix. Mixtures of rain, hail, graupel and snow hydrometeors relative to a realistic weather phenomenon are considered. The polarimetric and Doppler observables estimated from the simulated radar signals showed a good agreement with those found in previous observations.

Simulation of X-band polarimetric weather radar returns based on the Weather Research and Forecast model

A model is developed in this paper that simulates polarimetric radar returns from rain and hail at X-Band. To do this, the output data from an open-source meteorological model, namely the Weather Research and Forecast (WRF), and a numerical electromagnetic prediction code based on the Transmission-Matrix (T-Matrix) method are jointly used. Promising results are obtained that are in accordance with real observations. This model is intended to be used as input for a weather radar simulator with polarimetric and Doppler estimation capabilities.

Ship detection from SAR images based on CFAR and wavelet transform

In this paper the authors propose an innovative two-stage technique for ship detection which is applied to sea synthetic aperture radar (SAR) images. This technique is based on the joint use of Wavelet theory, in particular of the two-dimensional Discrete Wavelet Transform (2D-DWT), and the Constant False Alarm Rate (CFAR) processor. Real data acquired from COSMO-SkyMed (CSK) system have been processed to verify the effectiveness of this proposed new technique.

Validation of the Advanced Polarimetric Doppler Weather Radar Simulator with Polar55C real observations

A preliminary validation of the Advanced Polarimetric Doppler Weather Radar Simulator (APDWRS) with real data is described in this paper. The APDWRS is used to reproduce an observation of a severe storm event which took place on the 15th of October 2012 over the Tyrrenian coast. One PPI scan performed by the dual polarization C-band Polar 55C weather radar at 17:30 UTC is simulated using APDWRS with meteorological data from the Weather Research and Forecast (WRF) model as input. The validity of the simulation is then compared both in the spatial domain and statistically observing the differences in the relationships between observables in real and simulated case.

Exploiting dual-polarization technique in weather radar for civil aircrafts to mitigate risk in adverse conditions

Trajectory of civil aircrafts is typically optimized off-board to optimize fuel consumption, using also information available from weather services. Changes to the set route are decided by the pilot based on METAR and NOTAM updates and unexpected adverse weather conditions detected by the weather radar installed on the nose of the aircraft [1]. Typically, weather radars of most civil aircrafts are single-polarization X-band systems (only larger airplanes use C-band) with 3° beam-width flat antenna, following the specifications set by the ARINC 708A standard. Notoriously, attenuation due to propagation through a precipitation filled medium is not negligible at X-band and in the presence of cluster of convective cells, the nearer cells masks or weakens returns from farther cells, ultimately determining a wrong input to the pilots decision on optimal trajectory. Unfortunately, attenuation correction techniques applicable to single polarization radar are notoriously unreliable and strongly affected by radar calibration bias. Conversely, dual polarization technologies in ground based weather radar have demonstrated the capability of mitigating X-band attenuation based on differential phase shift measurements [2] and therefore could be successfully exploited for civil aviation weather radars. Current systems show to the pilot precipitation returns according to a few levels of reflectivity (the correspondence between colors and levels of reflectivity is not shown) and, within a shorter range, also information on turbulence detected from radar Doppler spectrum width. Meteorological interpretation of such images is largely left to the pilots experience. Dual polarization radar provides more information arising from the sensitivity their measurements to microphysical properties of particles exploited in hydrometeor classification products [3]. On the other hand, dealing with more information yields increased workload for pilot and therefore, to keep simple and effective the information shown to the pilot, an automated software to process dual-polarization measurements along with trajectory information to support the pilot in decision making is essential. The European Union, through the Clean Sky framework funded several projects to improve airborne weather radars and to optimally use them to optimize flight route. The project KLEAN aimed at using output of the Selex ES Weather Radar Post-Processor software (WRPP) inside an EFB (Electronic Flight Bag) to produce weather classification maps and related binary risk maps as the final radar product to be shown to the pilots or to be used by a trajectory optimizer.

Fast Detection of Oil Spills and Ships Using SAR Images

In this paper, we show the capabilities of a new maritime control system based on the processing of COSMO-SkyMed Synthetic Aperture Radar (SAR) images. This system aims at fast detection of ships that may be responsible for illegal oil dumping. In particular, a novel detection algorithm based on the joint use of the significance parameter, wavelet correlator and a two-dimensional Constant False Alarm Rate (2D-CFAR) is designed. Results show the effectiveness of such algorithms, which can be used by the maritime authorities to have a faster although still reliable response. The proposed algorithm, together with the short revisit time of the COSMO-SkyMed constellation, can help with tracking the scenario evolution from one acquisition to the next.

Analysis of X-band weather polarimetric radar simulator for avionic purposes

The improvement of the essential aircraft equipment used by pilots has a very important role in safety enhancement. In this context polarimetric weather Doppler radars could offer a valuable aid in improving detection and classification of hydrometeors, helping pilots to take the more efficient trajectory, balancing risk level and unnecessary detours. In this work an analysis of a polarimetric radar signal simulator developed by the RaSS team is presented.

Polarimetric radar for civil aircrafts to support pilots' decision in bad weather conditions

This paper presents and discusses some results of a specific Weather Radar Post-Processor software that provides weather classification maps and related binary risk maps after the processing of dual polarization airborne X band radar outputs. Weather classification maps and binary risk maps are used as input to decision support systems for aircraft pilots in case of bad weather conditions. The software runs inside an Electronic Flight Bag and the results shown here are obtained using true flight plans coming from the flight management system of an ATR72 flight simulator. Dual polarization avionic X band radar outputs are generated assuming true weather scenarios with a radar signal simulation software developed by the research team of the Radar and Surveillance Systems Laboratory of CNIT.

Hydrometeor classification for X-band dual polarization radar on-board civil aircrafts

Polarimetric techniques applied to radars on-board civil aircraft can improve the estimation of risk zones due to dangerous weather during flight. Usually, X-band weather radars are installed at the nose of civil aircrafts. This band is affected by strong attenuation in case of intense precipitation (liquid or mixed phase). The current systems do not compensate backscattered power measurements for attenuation caused by propagation through precipitation, while dual-polarization radars are able to compensate effectively this source of error and to discriminate hydrometeors. In this work, a classification algorithm based on support vector machines (SVM) is proposed. Training is driven by the output of a Fuzzy Logic (FL) classification algorithm (typical classification approach used for ground-based weather radar). SVM high performance in terms of time processing and its flexibility of configuration using all type of inputs variables are important characteristics to be included in some avionic specific equipment, such as the Electronic Flight Bag (EFB). Two datasets have been used to test the SVM classification algorithm. The first dataset is composed of simulated radar polarimetric observations at X-band and the second one is composed of actual dual-polarization radar measurements collected during the Special Observation Period (SOP) 1.1 of HYdrological cycle in MEditerranean EXperiment (Hymex) campaign by the C-band Doppler dual-polarization weather radar (Polar 55C) installed at ISAC-CNR in Rome. Good performance are obtained for SVM classificator. The comparison with FL output shows a good agreement (up to 90%) both in qualitative comparison maps by maps and using a quantitative approach which metric is based on the confusion matrix.

Exploitation of COSMO-SkyMed system for detection of ships responsible for oil spills

In this paper, the authors propose an innovative technique which is applied to the sea Synthetic Aperture Radar (SAR) imagery in order to aid the detection of the oil tankers responsible for oil spills. This technique aims to identify these oil spills and to correlate them to the detected ships. Real data acquired from COSMO-SkyMed (CSK) system have been processed to verify the effectiveness of this proposed new algorithm.