Charles Randell

Comparison of C-band SAR algorithms to derive surface wind vectors and initial findings in their use in marine search and rescue

This paper presents a comparison of existing algorithms to derive surface winds from synthetic aperture radar (SAR) satellites and investigates their use in drift forecasting for search and rescue purposes. Specifically, SAR-derived winds from RADARSAT-1 and ENVISAT advanced synthetic aperture radar (ASAR) data at 1.5 km resolution are compared with scatterometer-derived winds. Three approaches were used to retrieve the wind vector from the SAR data, including an optimal inversion method combining SAR data and background numerical weather prediction, the geophysical model function CMOD-IFR2 with an a priori wind direction, and a technique that uses the backscatter values corresponding to two neighboring subimages with slightly different incidence angles. Our comparisons of SAR wind mapping with scatterometer winds from QuikSCAT and ERS-2 produced a root mean square error (RMSE) of 1.5 m/s. The optimal inversion method seems very promising and appears to be the best choice for assimilation of SAR-derived winds into operational wind products with respect to the datasets presented here. Additionally, the suitability of SAR imagery for search and rescue operations is reviewed. It is recommended that a method should be explored to automatically assimilate such data into operational search and rescue tools. Use of SAR winds in a search and rescue drift model is shown herein to produce improved drift trajectories on a number of search and rescue targets (e.g., life boat, sail boat, person in water).

Dual Polarization Detection of Ships and Icebergs - Recent Results with ENVISAT ASAR and Data Simulations of RADARSAT-2

The RADARSAT-2 satellite is an advanced C-band synthetic aperture radar (SAR) with a variety of new modes including options for polarization combinations, resolution, and swath width. This paper examines the potential of multi polarization data for detecting and discriminating ship and iceberg targets Data used in this study consist of well validated airborne Convair-580 SAR and spaceborne ASAR HH/HV and HH/VV. In total, the data set used for evaluating detection and discrimination consists of 901 validated iceberg and ship targets. Optimizing target detection is accomplished using receiver operator curves (ROC) as proposed by [6] and discrimination is conducted using a quadratic discriminant (QD) with feature selection based on sequential forward selection (SFS). In general it was found that detection and discrimination improve with more polarimetric information; however, HH/HV and VV/VH only had nominally less discrimination performance than the quad polarization modes evaluated.

Toward the use of Earth Observation Wind Data for Marine Search and Rescue Operations

In an effort to increase the accuracy of drift prediction for search and rescue purposes, the authors have investigated the use of Earth Observation (EO) derived wind fields in drift modeling software used operationally by the Canadian Coast Guard. This investigating included both QuickSCAT and Synthetic Aperture Radar wind fields. Field campaigns were conducted off the coast of Newfoundland, Canada, during years 2004-2005, in which drift experiments were conducted with complementary EO acquisitions. Three SAR wind retrieval approaches were used. Our comparisons of SAR winds with scatterometer and in situ data show promising results for the optimal inversion method using a background wind model. At first glance, QuickSCAT winds do not improve the forecasted drift for any of the drifter configurations. However, an improvement is observed in short timescale drift trajectories with the use of SAR winds for most of the target configurations. The observed improvement decreases for increased duration of drift tracks, but this is to be expected since the uncertainties and errors associated drift prediction increase with time. Synthetic Aperture Radar, Search and Rescue, wind retrieval, , drift forecasting