Activity Report

April 2001 — April 2003

RADAR REMOTE SENSING GROUP

UBC

This report summarizes the research, teaching and administrative activities of the Radar

Remote Sensing Group of the Department of Electrical and Computer Engineering at

the University of British Columbia (http://www.ece.ubc.ca/) during the period from

April 2001 to April 2003.

The focus of the research work is on the processing of synthetic aperture radar (SAR)

data, concentrating on data from remote sensing satellites such as ERS and RADARSAT.

Various aspects of SAR processing, including

• Doppler centroid estimation,

• satellite roll angle estimation,

• ScanSAR data collection and calibration methods,

• polarimetric sea ice classification,

• SAR image data compression, and

• comparison of precision SAR processing algorithms

have been studied during the reporting period.

The research work has been documented in reports, conferences, journal papers, and

in student theses. The work is briefly described below, first categorized by “students

supervised”, then categorized under type of publication.

1 Graduate Students Supervised

Bernd Scheuchl: Bernd passed his Ph.D. qualifying exam in 2002, and is progressing

well in his research on the classification of sea ice in polarimetric radar data. The

project is being conducted in cooperation with MacDonald Dettwiler, where he

spends much of his time. His main work is on the development of polarimetric

radar classification algorithms, which he is applying to data of the various types

of sea ice found in the Canadian Arctic and North Atlantic. See [1–11] and Figure

1.

1

Dan Bast: Dan completed his M.A.Sc. thesis defense in May 2002, and spent some

time helping to write a journal paper in the summer. He has recently joined

the European Space Agency’s apprenticeship program at their Space Technology

Research Center, ESTEC, in Holland. In his UBC research work, he improved

the estimation of RADARSAT’s roll angle, by using extra data collected during

the ScanSAR beam switching cycle. This involved proposing a new method of

ScanSAR data collection, modifying a roll angle estimation algorithm to use the

new data, and developing a simulation to show how much the roll angle estimate

is improved. It is anticipated that the work will lead to more accurate joining of

RADARSAT-2 images, eliminating the edge artifact that is often seen in current

ScanSAR images. See [12–15] and Figure 2.

Jing Wang: Jing finished her M.A.Sc. program in December 2002. She worked on

the compression of SAR image data, using the approach of wavelet packets in

an adaptive block encoding scheme. A new algorithm called Wavelet Packet

Embedded Block (WPEB) coding was developed. Previous work had involved

the discrete wavelet transform [16], and it was found that the increased attention

paid to the higher frequencies in the SAR image by wavelet packets improved the

compression efficiency. In addition, a block coding method was used that improved

the coding by applying more bits to active areas of each scene. See [17–19] and

Figure 3.

Yewlam Neo: Yewlam joined us from Singapore, where he was a signal processing

engineer with the Radar Systems Department in the DSO National Labs. He

obtained a scholarship from his employer, and began at UBC in January 2002.

He has just finished his course requirements, and is beginning research work on

the comparison of precision SAR processing algorithms [20].

Flavio Wasniewski: Flavio came to us in September 2001 from Brazil, where he

worked as a cartographic engineer with RADARSAT data. He is presently com-

pleting his UBC course requirements, and is working part time at RADARSAT

International on the applications of polarimetric radar data. His research work

will be on the extraction of man-made targets from polarimetric radar data.

Millie Sikdar: Millie came to our group in September 2002 from the undergraduate

program of the Govt. College of Engineering, Aurangabad, India. She is just

finishing her course requirements, and will begin her research this summer on the

analysis of polarimetric radar data.

Kaan Ersahin: Kaan arrived at UBC in January 2003, after earning his M.Sc. at

the Istanbul Technical University (ITU) in Turkey. He worked at the satellite

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receiving station in Istanbul, including the processing of RADARSAT data, and

is keen to pursue his studies in radar remote sensing.

Vincent Yip and Vincent Siu: These two students completed their Master of En-

gineering program at UBC in April 2003. They worked on the MPEG-1, Level-3

audio data compression algorithm, known as MP3. The algorithm was simulated

in MATLAB, and audio examples were generated that illustrated the effect of

various bit rates from 64 to 256 Kbits/s [21].

2 Presentations at Conferences

During the reporting period, the following conferences were attended by Ian Cumming

and/or his students.

IGARSS’01 IEEE International Geoscience and Remote Sensing Symposium, Syd-

ney, Australia, July 9–13, 2001 [1, 22]. IGC was a session chairman.

CRSS’01 23rd Canadian Symposium on Remote Sensing, Quebec City, August 21–24,

2001 [2].

ASAR’01 4th Workshop on Advanced SAR Technology, Canadian Space Agency,

St. Hubert, Quebec, October 1–3, 2001 [3].

IGARSS’02 IEEE International Geoscience and Remote Sensing Symposium, Toronto,

June 24–28, 2002 [4–6, 12, 17]. IGC was on the technical organizing committee

and was a session chairman.

PolInSAR’03 Workshop on Applications of SAR Polarimetry and Polarimetric In-

terferometry, ESA/ESRIN, Frascati, Italy, January 14–16, 2003 [7, 8].

DCC’03 Data Compression Conference, IEEE Computer Society, Snowbird, Utah,

March 25-27, 2003 [19].

Future Conferences Papers has been submitted to the following future confer-

ences:

IGARSS’03 IEEE International Geoscience and Remote Sensing Symposium, Toulouse,

July 21–25, 2003 [9, 20]. IGC is a session chairman.

http://www.ewh.ieee.org/soc/grss/igarss.html

3

ASAR’03 Advanced SAR Workshop, Canadian Space Agency, Montreal, June 25–

27, 2003 [10, 15]. IGC is on the technical organizing committee and is a session

chairman. http://www.space.gc.ca/asc/eng/csa sectors/technology/development/csa labs/

expertise/asar2003.asp

3 Research Book on SAR Processing

Frank Wong and Ian Cumming have been writing a research book on SAR signal pro-

cessing over the last three years. The book brings together all the major developments

in satellite SAR processing in the last 20 years, based on their research and experience

at MacDonald Dettwiler. Chapter titles are:

1. Introduction

2. Signal Processing Fundamentals

3. Pulse Compression

4. Synthetic Aperture Concepts

5. SAR Signal Properties

6. The Range Doppler Algorithm

7. The Chirp Scaling Algorithm

8. The Omega-K Algorithm

9. The SPECAN Algorithm

10. ScanSAR Processing Algorithms

11. Doppler Parameter Estimation

12. Comparison of Algorithms

13. Summary

The book is now over 400 pages long, and it is expected that about 100 more pages

will be written before it is completed. Arrangements are underway for Artech House to

publish the book in late 2003.

4 Papers Submitted and/or Published

Because of the time and effort devoted to writing the book, there were fewer journal

papers written than usual during the reporting period.

4

Jonathan Zeng’s work on SAR speckle reduction and data compression using wavelets

was completed in the last reporting period, and appeared in the IEEE Transactions

of Geoscience and Remote Sensing in March 2001 [16]. It shows that SAR speckle

reduction and data compression can be efficiently combined, and that wavelets can

provide better data compression than traditional methods.

The work with Dan Bast produced a number of new ideas, including a new method of

ScanSAR data collection on SAR satellites, and the use of the new data for improving

the estimation of the satellite’s roll angle. When the roll angle is known more accurately,

the radiometry of the received data can be corrected with greater precision, with the

result that radiometric artifacts in the ScanSAR images can be reduced.

The new data comes from pulses transmitted on one beam, and received on another

beam, after the beams have been switched in range during the normal ScanSAR cycles.

The new data is referred to as “hybrid beam” data, and Figure 2(a) illustrates how

the new data is received within the normal inter-pulse periods. Figure 2(b) shows that

the roll angle accuracy improves by about 25% with the additional hybrid beam data,

when three burst periods are used in the estimator. The concepts and results have been

documented in a technical paper, which has been reviewed by the IEEE. The paper was

re-submitted in April 2003 with editing changes requested by the editor [14].

When Prof. Malek Hussain was an academic visitor in the Radar Remote Sensing Group

at UBC, he worked on the analysis of radar systems using very large bandwidths,

referred to as impulse radars. One significant advantage they have is the lack of side

lobes in the radiation patterns. Impulse radars can be conveniently analyzed using

Space-Time Processing, as Prof. Hussain explains in a paper produced from his work

at UBC [23].

Ian Cumming has refined his work on Doppler centroid estimation, by adding an

Earth/satellite geometry model that obtains the Doppler centroid from satellite roll

and pitch measurements. The earlier work used spatial diversity and quality criteria to

fit a Doppler surface over a whole frame of received data, without using roll and pitch

measurements [22]. The addition of the geometry model reduces the dimensionality of

the estimation problem, and places constraints on the solution to ensure a physically

plausible estimate. A draft of a technical paper has been written, and it is planned to

submit it for publication in the near future [24].

5 Educational Material

An interesting activity in the last year has been writing material for the educational

web site of the Canada Centre for Remote Sensing.

5

GlobeSAR-2

Nine chapters have been written for the “GlobeSAR-2 Educational Resources for Radar

Remote Sensing”. The material is now available at:

http://www.ccrs.nrcan.gc.ca/ccrs/learn/tutorials/gsarcd/intro e.html

The chapters that Ian wrote have the following titles and page numbers:

1. Introduction to RADAR Remote Sensing, pages 11-62

2. RADARSAT-1, pages 63-78

3. RADARSAT-2, pages 79-102

4. RADAR Systems, pages 103-119

5. SAR Image Formation, pages 120-142

6. SAR Image Characteristics, pages 143-161

7. SAR Systems and Digital Signal Processing, pages 394-477

8. Radar Polarimetry, pages 478-495

9. Radar Interferometry, pages 496-538

Glossary

CCRS has a large glossary of remote sensing terms on their web site. Ian has been

updating the glossary entries pertaining to polarimetric radar. About 62 current terms

have been updated and 52 new terms added. These terms are currently being incorpo-

rated into the “CCRS Glossary on Remote Sensing” at:

http://www.ccrs.nrcan.gc.ca/ccrs/learn/terms/glossary/glossary e.html

Tutorial

In addition, there is a tutorial on Remote Sensing on the CCRS web site, which includes

a module on SAR remote sensing. Ian has written three new chapters for the tutorial:

1. Understanding the Basics of SAR Sensors, 23 pages

2. Fundamentals of Polarimetry, 8 pages

3. Advanced Polarimetric Tutorial, 44 pages

These new chapters are in the process of being added to the web site “Fundamentals of

Remote Sensing”: http://www.ccrs.nrcan.gc.ca/ccrs/learn/tutorials/fundam/fundam e.html

6

6 Teaching at UBC

In September 2001 and again in September 2002, the course EECE 591 “Applied Digital

Signal Processing” was given to about 20 postgraduate students. After covering the

main theory and tools of DSP, a number of applications are explained. The main

application is processing of SAR data, but other applications include image interpolation

and compression, GPS navigation, and wavelets. Over 400 pages of electronic notes have

been prepared and made available to the students via the web.

In January 2002, the course EECE 466 “Digital Signal Processing” was taught to about

30 4th year undergraduates. A new book was used by Ifeachor and Jervis, which

combines theory and practice in a very readable format.

In January 2003, the lecture/lab course, EECE 467, was taught to 33 4th year students.

Four experiments were designed in which DSP algorithms were programmed on a TI

DSP board to perform functions such as an audio graphic equalizer, an IIR bandpass

filter in fixed point arithmetic, an audio filter implemented with FFTs, and a detector

for dual-tone multi-frequency telephone dialing. The lectures covered the DSP theory

needed to understand the experiments, and the technology of DSP hardware. Everyone

passed and we all had fun!

One novel aspect of the 467 course was using WebCT for web-based learning. Lecture

notes, lab instructions, and quizzes were posted on the web. We actually ran the exam

on WebCT, which worked well after we got over the embarrassment of prematurely

emailing the exam to all the students by mistake!

In September 2002, a 6-person ECE 285 group was supervised on the topic of Radar Re-

mote Sensing, concentrating on the new technologies being developed for RADARSAT-

2.

In September 2001 and January 2002, groups of 3rd and 4th year students were super-

vised in an ECE 496 project on GPS receivers. After learning how signal processing

is used in the GPS system, they used a hand-held receiver to assess the position and

velocity accuracy in dynamic experiments. PC-based mapping software was used to

plot the GPS measurements on topographic maps.

In September 2002, January 2003 and again in May 2003, ECE 496 groups were super-

vised on a new project building an ultrasound model of the GPS system. The students

have to understand how the GPS system works, and then build a model in the lab to

illustrate the principles and to show how signal processing is used. Ultrasound signals

were used so that the transmitted signal would not be noticeable (i.e. not offensive to

the ears), and to obtain resolutions in the order of a centimeter using a bandwidth as

low as 4 KHz. The first group experimented with various ultrasound transducers, and

7

built a system that obtained 2 cm accuracy over one meter. The second group built

an improved modulator using FSK, and obtained 1.5 cm accuracy over 15 meters. The

third group is now building a system to measure position in two dimensions. The stu-

dents learn how spread spectrum and pulse compression techniques can obtain accurate

position and velocity measurements in the face of low signal/noise ratios.

The following ECE 571 reading courses were designed and conducted for individual

students:

1. “Polarimetric SAR Interferometry (PolInSAR)”, Bernd Scheuchl, April 2001

2. “SAR Systems and Signal Processing”, Yewlam Neo, July 2002

3. “Fundamentals of Polarimetry”, Flavio Wasniewski, April 2003

4. “Principles and Applications of Imaging Radar”, Millie Sikdar, May 2003

5. “SAR Signal Processing”, David Alton, Univ. of Calgary

Approximately two coop students have been supervised per term.

7 Theses Supervised

Being on sabbatical in 2000, new students were not accepted until 2001. This meant

that the number of theses in 2001-2003 were below average. The two M.A.Sc. students

who completed their theses during the reporting period were Dan Bast [13] and Jing

Wang [18]. In addition, two M.Eng. students were supervised, Vincent Yip and Vincent

Siu, who wrote a report almost as long as a masters thesis [21] (80 pages).

8 Educational Service

Ian Cumming was invited to be the external Ph.D. examiner of Juergen Holzner at

the University of Edinburgh in November 2002. As the topic of “ScanSAR Radar

Interferometry” was very pertinent to the group’s research, Ian travelled to Edinburgh,

and conducted a 6-hour exam. A very good thesis and a worthwhile trip.

Other educational activities included:

• serving on the committee of five Ph.D. examinations held at the Faculty of Grad-

uate Studies at UBC,

• serving on the committee of 11 ECE Master’s and Ph.D. examinations in the ECE

department,

8

• presenting two seminars on Radar Polarimetry at Pre-conference Workshop at

IGARSS’02 (Ian Cumming and Bernd Scheuchl),

• running a reading course for a student at the University of Calgary (see Section

6),

• reviewing 9 papers for several IEEE Transactions and the Canadian Journal of

Remote Sensing,

• reviewing 3 NSERC applications.

9 UBC Administration

• ECE Building committee, 2001

• ECE Faculty Recruiting committee, 2001 – 2003

10 Industrial Liaison

Ian and his students visit MacDonald Dettwiler often, and usually make presentations

at the MDA Quarterly R&D reviews.

Their current work with MacDonald Dettwiler concentrates on developing applications

for RADARSAT-2. One of the main applications of RADARSAT-1 is ice mapping, and

the main innovation on RADARSAT-2 is polarimetry, so it is important to develop

algorithms for ice classification with polarimetric data. This is the focus of Bernd

Scheuchl’s research, and present results indicate that polarimetric SAR data will provide

substantially better automatic ice classification than data from existing single-channel

radars (see Figure 1) [9].

Bernd was given the technical lead on the EOADP project “Multi-Polarimetric SAR

Product for Operational Sea Ice Monitoring” at MDA. His work in 2002 included:

• Analysis of AIRSAR three-frequency fully polarimetric data of sea ice

• Analysis of Convair-580 data of sea ice (incidence angle analysis, dual-pol and

quad-pol classification)

• Preparation of a sample data set including polarimetric data, polarimetric param-

eters, data description, and auxiliary data

Four reports have been written to date on the work at MDA [25–28]. Bernd’s work is

continuing with an investigation of ENVISAT alternating polarization data with respect

to the separation of sea ice and open water, and its data visualization.

9

We also have connections with RADARSAT International Inc. (RSI) of Richmond, BC.

In particular, Flavio Wasniewski has spent about a quarter of his time at RSI, working

on the interpretation of Convair-580 polarimetric SAR data from the Gagetown base, in

order to explore the potential of RADARSAT-2 for various applications. The analysis

results have been used for customer training and marketing. The work involved:

• Exploration of the polarimetric signatures of targets;

• Addition of noise to Convair-580 multi-looked data to emulate RADARSAT-2

data.

• Extraction of visual examples that illustrate the advantage of multi-polarized

data;

• Comparisons between RADARSAT-1 and Convair-580 data to predict RADARSAT-

2 feature extraction capabilities;

• Identification of features in the Gagetown images to verify via fieldwork. The

fieldwork has been done and there is now more data to work on.

Acknowledgments

We would like to express our sincere appreciation to MacDonald Dettwiler, NSERC, the

Canadian Space Agency and the BC Advanced Systems Institute for providing financial

support for the research activities of the UBC Radar Remote Sensing Group throughout

the period of this report.

We continue to enjoy access to radar data from the RADARSAT, ERS and X-SAR/SRTM

programs.

Ian Cumming

May 8, 2003

References

[1] B. Scheuchl, R. Caves, I. Cumming, and G. Staples. Automated Sea Ice Classifica-

tion Using Spaceborne Polarimetric SAR Data. In Proceedings of the IEEE Interna-

tional Geoscience and Remote Sensing Symposium, IGARSS’01, pages 3117–3119,

Sydney, Australia, July 9–13, 2001.

[2] B. Scheuchl, R. G. Caves, I. G. Cumming, and G. Staples. H/A/alpha-based Clas-

sification of Sea Ice Using SAR Polarimetry. In Proceedings of the 23rd Canadian

Symposium on Remote Sensing, Quebec City, August 21–24, 2001.

10

[3] I. Hajnsek, B. Scheuchl, R. G. Caves, and I. G. Cumming. Surface Parameters

Inversion from Sea Ice Using Spaceborne Polarimetric SAR Data. In 4th Work-

shop on Advanced SAR Technology, Canadian Space Agency, St. Hubert, Quebec,

October 1–3, 2001.

[4] B. Scheuchl, I. Hajnsek, and I. G. Cumming. Model-Based Classification of Polari-

metric SAR Sea Ice Data. In Proceedings of the IEEE International Geoscience and

Remote Sensing Symposium, IGARSS’02, pages 1521–1523, Toronto, June 24–28,

2002.

[5] B. Scheuchl, I. Hajnsek, and I. G. Cumming. Sea Ice Classification Using Multi-

Frequency Polarimetric SAR Data. In Proceedings of the IEEE International Geo-

science and Remote Sensing Symposium, IGARSS’02, pages 1914–1916, Toronto,

June 24–28, 2002.

[6] B. Scheuchl and I. G. Cumming. Potential of RADARSAT-2 for Sea Ice Classifi-

cation. In Proceedings of the IEEE International Geoscience and Remote Sensing

Symposium, IGARSS’02, pages 2185–2187, Toronto, June 24–28, 2002.

[7] Bernd Scheuchl, Irena Hajnsek, and Ian Cumming. Classification strategies for po-

larimetric SAR sea ice data. In Workshop on Applications of SAR Polarimetry and

Polarimetric Interferometry, ESA/ESRIN, Frascati, Italy, January 14–16, 2003.

[8] Bernd Scheuchl, Dean Flett, Gordon Staples, Gordon Davidson, and Ian Cum-

ming. Preliminary classification results of simulated RADARSAT-2 polarimetric

sea ice data. In Workshop on Applications of SAR Polarimetry and Polarimetric

Interferometry, ESA/ESRIN, Frascati, Italy, January 14–16, 2003.

[9] B. Scheuchl, I. G. Cumming, and I. Hajnsek. Consolidation of a Pixel-Based

Classification Using Neighbourhood Information. In Proceedings of the IEEE In-

ternational Geoscience and Remote Sensing Symposium, IGARSS’03, Toulouse,

July 21–25, 2003.

[10] B. Scheuchl, I. Hajnsek, and I. G. Cumming. Potential of SAR Polarimetry for

Sea Ice Discrimination. In Proceedings of the Advanced SAR Workshop, ASAR’03,

Canadian Space Agency, Montreal, June 25–27, 2003.

[11] B. Scheuchl, D. Flett, R. Caves, and I. Cumming. Potential of RADARSAT-

2 multiple polarization and polarimetric data for operational sea ice monitoring.

Canadian J. of Remote Sensing, submitted February 2003.

[12] D. Bast and I. Cumming. RADARSAT ScanSAR Roll Angle Estimation. In

Proceedings of the IEEE International Geoscience and Remote Sensing Symposium,

IGARSS’02, pages 152–154, Toronto, June 24–28, 2002.

11

[13] Daniel C. Bast. ScanSAR radiometric calibration based on roll angle estimation.

Master’s thesis, Dept. of Electrical and Computer Eng., The University of Britsh

Columbia, 2356 Main Mall, Vancouver, BC, Canada V6T 1Z4, May 2002.

[14] I. G. Cumming and D. C. Bast. A New Hybrid-Beam Data Collection Strategy to

Support ScanSAR Radiometric Calibration. IEEE Trans. on Geoscience and Re-

mote Sensing, 2003. To be published, final editorial revisions have been completed.

[15] I. G. Cumming and D. C. Bast. A Method of Improving Roll Angle Estimation in

Future RADARSATs. In Proceedings of the Advanced SAR Workshop, ASAR’03,

Canadian Space Agency, Montreal, June 25–27, 2003.

[16] Z. Zeng and I. G. Cumming. Modified SPIHT Encoding for SAR Image Data.

IEEE Trans. on Geoscience and Remote Sensing, 39(3): pp. 546–552, March 2001.

[17] I. Cumming and J. Wang. Polarimetric SAR Data Compression Using Wavelet

Packets in a Block Coding Scheme. In Proceedings of the IEEE International

Geoscience and Remote Sensing Symposium, IGARSS’02, Toronto, June 24–28,

2002.

[18] Jing Wang. Investigations on single and multipolarization SAR image compression.

Master’s thesis, Dept. of Electrical and Computer Eng., The University of Britsh

Columbia, 2356 Main Mall, Vancouver, BC, Canada V6T 1Z4, December 2002.

[19] I. Cumming and J. Wang. Compression of RADARSAT Data with Block Adap-

tive Wavelets. In Proc. Data Compression Conference, IEEE Computer Society,

Snowbird, Utah, March 25-27, 2003.

[20] I. G. Cumming, Y. L. Neo, and F. H. Wong. Interpretations of the Omega-K

Algorithm and Comparisons with other Algorithms. In Proceedings of the IEEE

International Geoscience and Remote Sensing Symposium, IGARSS’03, Toulouse,

July 21–25, 2003.

[21] Vincent Yip and Vincent Siu. MATLAB Implementation of the MP3 Encoder.

Master of Engineering Report, Department of Electrical and Computer Engineer-

ing, The University of British Columbia, 80 pages, April 2003.

[22] Ian Cumming. Model-Based Doppler Estimation for Frame-Based SAR Process-

ing. In Proceedings of the IEEE International Geoscience and Remote Sensing

Symposium, IGARSS’01, pages 2645–2647, Sydney, July 9–13, 2001.

[23] Malek G. M. Hussain. Principles of Space-Time Array Processing for Ultrawide-

Band Impulse Radar and Radio Communications. IEEE Transactions on Vehicular

Technology, 51(3): pp. 393–403, May 2002.

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[24] I. G. Cumming. A Spatially-Selective Approach to Doppler Estimation for Frame-

Based SAR Processing. IEEE Trans. on Geoscience and Remote Sensing, 2003. In

preparation.

[25] Ron Caves, Gordon Staples, and Bernd Scheuchl. Multi-Polarimetric SAR Prod-

ucts for Operational Sea Ice Monitoring. Technical Report RX-RP-51-2570, Mac-

Donald Dettwiler, Richmond, BC, November 2001.

[26] Bernd Scheuchl. Analysis of CV-580 Fully Polarimetric Data of Sea Ice – Data Cali-

bration Test. Technical Report RX-TN-51-4118, MacDonald Dettwiler, Richmond,

BC, September 2002.

[27] Bernd Scheuchl, Gordon Staples, and Gordon Davidson. Analysis of CV-580 Fully

Polarimetric Data of Sea Ice – Final Report. Technical Report RX-RP-51-3699,

MacDonald Dettwiler, Richmond, BC, March 2003.

[28] Bernd Scheuchl. Analysis of CV-580 Fully Polarimetric Data of Sea Ice – Executive

Summary. Technical Report RX-RP-51-4625, MacDonald Dettwiler, Richmond,

BC, March 2003.

Many of the above references are available on the group’s web site:

http://www.ece.ubc.ca/sar/

13

(a) Convair-580 SAR scene of Northumberland Strait, PEI, acquired March 8, 2001.

Red – VV ; Green – HV ; Blue – HH.

(b) Classification result:

Grey – Young ice; White – rough FYI (strong HV); Green – ridged FYI;

Blue – Leads; Orange – FYI (near range); Magenta – FYI (far range);

Figure 1: Classification of C-band CV-580 polarimetric sea ice data using a Bayesian

algorithm with a Wishart distribution. Image size: 6.4 km (range) by 8 km (azimuth);

Pixel size: 16 m; Incidence angle: 41 – 64 degrees; Number of looks: 4x40.

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9 10 11 12 13 14 15 16 17 18 19 20 21

1 2 3 4 5 6 7 8 9 10 11 12 13 14

Case 1: PRF DOWN 2 Delta PRF = −180 HzPRF1 = 1230 m

1 = 8 PRF

2 = 1050 m

2 = 7

beamswitchover

point

9 10 11 12 13 14 15 16 17 18 19 20 21 22 23

1 2 3 4 5 6 7 8 9 10 11 12 13 14

Case 2: PRF DOWN 1 Delta PRF = −60 HzPRF1 = 1230 m

1 = 8 PRF

2 = 1170 m

2 = 8

9 10 11 12 13 14 15 16 17 18 19 20 21 22 23

1 2 3 4 5 6 7 8 9 10 11 12 13 14

Case 3: PRF UP 1 Delta PRF = 80 HzPRF1 = 1230 m

1 = 8 PRF

2 = 1310 m

2 = 9

9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24

1 2 3 4 5 6 7 8 9 10 11 12 13 14

Case 4: PRF UP 2 Delta PRF = 210 HzPRF1 = 1230 m

1 = 8 PRF

2 = 1440 m

2 = 10

(a) Timing of hybrid beam data collection for 4 values of PRF change.

The PRF and the beam elevation angle change at the beam switchover point.

−20 −18 −16 −14 −12 −10 −8 −6 −4 −2 00

0.05

0.1

0.15

0.2

Scene brightness (sigma nought)

Rol

l err

or m

agni

tude

(de

g)

Without hybrid beam data

With hybrid beam data

Noise equivalent sigma nought = −23 dB

Correct beam patterns used

Recommended accuracy

(b) Improvement in roll angle accuracy with the hybrid data

Figure 2: Illustrating the improvement of satellite roll angle estimation when hybrid

beam ScanSAR data are used [14].

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(a) Original RADARSAT scene of Vancouver Airport with 16 bits/pixel

(b) The scene encoded with the WPEB algorithm using 1 bit/pixel

Figure 3: Illustrating image interpretability when the SAR image is encoded with

wavelet packets by the WPEB algorithm using 1 bit/pixel [19].

16