Iceberg Detection Using Simulated Radarsat Constellation Data

Iceberg Detection Using Simulated Radarsat Constellation Data

Abstract

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Michael Denbina and Michael J. Collins Department of Geomatics Engineering, University of Calgary, Calgary, AB T2N 1N4 Canada

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Iceberg monitoring, as well as maritime surveillance in general, is an important application of synthetic aperture radar (SAR), and is a stated objective of the Radarsat Constellation, the next generation of Canada’s Radarsat satellites. In this paper, we simulate Radarsat Constelation data in a number of different imaging modes, using Radarsat-2 single-look complex data covering a study area in the Labrador Sea. We test the iceberg detection performance of both linear dual-pol data as well as compact polarimetry, a novel SAR architecture that transmits circular polarization rather than the traditional horizontal or vertical polarizations. In doing so, it can provide polarimetric information that was previously inaccessible to dual-pol SAR data, while retaining a wider swath width than quad-pol data. We use the likelihood ratio test method to calculate a decision variable image for each of a number of different dual-pol and compact configurations, then analyze the detection performance using 25 validated iceberg locations spread across 12 different scenes. To study the effects of incidence angle on detection performance, we split the data into different incidence angle categories, then compared the detection performance (number of missed targets, and number of false alarms) of compact and linear dual-pol data in each incidence angle category. We also generated receiver operating characteristic (ROC) curves, showing the probability of missed detection vs. probability of false alarm for each target, then calculated the median ROC curve for each incidence angle category. We found that compared to the linear data, the compact data missed fewer targets, and detected a greater number of pixels of detected targets, for most of the incidence angles and imaging modes tested. Compact polarimetry seems to be a promising choice for iceberg detection applications.

Keywords

iceberg detection, compact polarimetry, circular polarization, synthetic aperture radar, Radarsat Constellation.

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Introduction

Iceberg monitoring, as well as maritime surveillance in general, is an important application of synthetic aperture radar (SAR). The wide area coverage of spaceborne SAR sensors, and their all-weather day-night operation, makes them well suited to this task. In particular, the use of polarimetric SAR rather than single-polarization systems can be of huge benefit, allowing increases in detection performance, as shown by the work of Howell et al. (2004, 2006, 2008) and a previous study by the authors (Denbina & Collins, 2012). While quad-polarization (quad-pol) SAR provides complete polarimetric scattering information, it has double the power and data rate requirements of dual-polarization (dual-pol) SAR. This is because a quad-pol SAR must transmit two orthogonal polarizations, and receive two orthogonal polarizations for each transmission, yielding four channels in total. A dual-pol SAR, on the other hand, transmits only one polarization, and receives two orthogonal polarizations, yielding two channels in total. On spaceborne SAR systems the available power is limited, and quad-pol modes generally have half the swath width of ∗

published in 2014: Canadian Journal of Remote Sensing, 40(3), 165–178

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dual-pol modes, in order to keep power usage constant. For applications in maritime surveillance, where mapping a large area is vital, the smaller swath width of quad-pol data makes these data unsuitable. We therefore restrict our attention, in the research reported here, to dual-polarized data. In our previous study of iceberg detection using Radarsat-2 data (Denbina & Collins, 2012), we reported results for a study area in the Labrador Sea, using a polarimetric SAR architecture known as compact polarimetry (CP). Most SAR systems traditionally transmit either horizontally or vertically polarized waves. There are a number of different implementations of compact polarimetry, but each of them involves the transmission of waves that are neither horizontal nor vertical. For example, in the π/4 mode (Souyris, Imbo, Fjortoft, Mingot, & Lee, 2005), the transmitted polarization is oriented at the angle of its namesake. Another option is the dual-circular polarization (DCP) mode (Stacy & Preiss, 2006), where circularly polarized waves are both transmitted and received. Our work focused on the circular transmit, linear receive (CTLR) mode, an architecture proposed for use in Earth-based remote sensing by Raney (2007). In this mode, circularly polarized waves are transmitted, but the received polarizations are the familiar linear horizontal and vertical. While new to terrestrial remote sensing, CP SAR systems have been used in planetary imaging for some time. Recently, the miniSAR on board Chandrayaan-1 (Raney et al., 2010) collected CP SAR images of our moon (Carter, Campbell, & Campbell, 2011). We can represent the polarimetric channels of a SAR system by the scattering vector, ~k, where each element of ~k contains a complex number, S, that describes the backscatter for a particular combination of transmitted and received polarizations. These polarizations are denoted by the subscripted letters of S, with the first letter denoting the transmitted polarization, and the second letter the received polarization. For example, the two most common dual-pol SAR configurations have the following scattering vectors (where “H” stands for horizontal, and “V” for vertical): T ~k dual-pol = [SHH , SHV ]

(1)

T ~k dual-pol = [SV V , SV H ]

(2)

Similarly, if we denote the transmitted polarization as “R” (for right-circular), the scattering vector of a CTLR SAR system can be written as follows: ~kCT LR = [SRH , SRV ]T

(3)

This scattering vector can be rewritten entirely in the linear (H,V) basis as: 1 kCT LR = √ [SHH − iSHV , −iSV V + SV H ]T 2

(4)

We see that the channels measured by a CTLR SAR system contain the four channels we would expect to receive from a typical quad-pol SAR system (HH, HV, VH, and VV). Of course, since the channels have been added together, information has been lost, and a CTLR SAR system in no way contains the same volume of polarimetric information as a quad-pol SAR. However, compared to the scattering vectors of a linear dual-pol SAR system, the potential of CTLR data is clear. By making a number of assumptions, some of the information in the CP scattering vector can be separated, allowing the approximation of some elements of the quad-pol covariance matrix. This process, known as pseudo quad-pol (or pseudo-quad, or PQ) reconstruction, was originally developed by Souyris et al. (2005), and expanded upon by Nord, Ainsworth, Lee, and Stacy (2009). Our previous work in iceberg detection (Denbina & Collins, 2012) made use of a modified version of the reconstruction algorithm suitable for use with ocean imagery (Collins, Denbina, & Atteia, 2013). We compared the detection performance of linear dual-pol SAR, the native channels of a CTLR SAR (RH and RV), and a number of configurations of pseudo quad-pol data, using 25 validated iceberg targets spread across 12 Radarsat-2 scenes. We calculated the receiver operating characteristics (ROC) (Scharf, 1990), plots of the probability of missed detection (PMD) vs. probability of false alarm (PFA) for a range of thresholds, and found that the reconstruction process could potentially augment the detection performance of the CTLR data. We also found that the 3

Table 1: An overview of the Radarsat-2 fine-quad scenes used in our study. Beam refers to the fine quad beam position, W.S. stands for estimated wind speed for the scene and N is an estimated reconstruction parameter (see section 3.1). Inc. 19.9◦ 19.9◦ 23.4◦ 23.4◦ 23.4◦ 23.4◦ 24.6◦ 25.8◦ 25.8◦ 28.0◦ 30.3◦ 30.3◦ 35.5◦

Angle - 21.8◦ - 21.8◦ - 25.3◦ - 25.3◦ - 25.3◦ - 25.3◦ - 26.5◦ - 27.6◦ - 27.6◦ - 29.9◦ - 32.0◦ - 32.0◦ - 37.0◦

W.S. (m/s) 5.0 5.0 1.3 1.5