bistatic/monostatic synthetic aperture radar for ice sheet

36
University of Kansas John Paden MS Thesis Defense April 18, 2003 Committee Chairperson: Dr. Chris Allen Committee Members: Dr. Prasad Gogineni Dr. Glenn Prescott Bistatic/Monostatic Synthetic Aperture Radar for Ice Sheet Measurements

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University of Kansas

John PadenMS Thesis Defense

April 18, 2003

Committee Chairperson: Dr. Chris AllenCommittee Members:Dr. Prasad GogineniDr. Glenn Prescott

Bistatic/Monostatic Synthetic Aperture Radar for Ice Sheet Measurements

University of Kansas

Topics

• Overview

• EM Model

• Sensor Geometry

• Antenna Array

• Position Errors

• Sandbox Tests

University of Kansas

Overview – Motivation

• Global sea level rise threatens coastal regions

• Contributions from an ice sheet are measured by finding the mass balance of the ice sheet.

• Create ice flow model to predict mass balance

• Basal conditions needed for ice flow model

• We can drill boreholes in a few places, but not all over the Arctic and Antarctic regions à RADAR.

University of Kansas

Overview – Basal Scattering• The bedrock is thought to

be smooth with respect to wavelength.

• Therefore it looks like a mirror at our frequencies of operation.

Origin

S1

αβ

α

D

0

T

S2

T

RXRM

β

Tx

BedrockIce

Swath

yz

x

University of Kansas

Data Collection Geometries• Monostatic Arrangement

• Used when the surface is rough and side-looking radar techniques can be employed

Tran

smitt

ers/

Rec

eive

rs

σx

σx

Ice

Bedrock

Air

MeasurementSwath

yz

x

University of Kansas

Data Collection Geometries• Bistatic Arrangement

• Used when the surface is smooth and exhibits specular (mirror-like) characteristics

• New variable: separation distance between transmitter and receiver

Tran

smitt

ers

Rec

eive

rs

σx

σx

Ice

Bedrock

Air

MeasurementSwath

yz

x

University of Kansas

Overview – System Model

• Modes of operation: monostatic and bistatic

• Broadband operation: nearly three octaves

Rough Surface

Liquid Water

Sloped Surface

Smooth Surface

Geophysical Model

SAR Processing

EM Model

Physical Characteristics

Sensor Geometry

Measurement Swath

RxTxAirIce

Data

University of Kansas

EM Model

• Magnitude of Transfer Function• TEM Horn Antenna Measurements

• Radar System Transfer Function

• Spherical Spreading

• Phase of Transfer Function• TEM Horn Antenna Measurements

• Radar System Transfer Function

• Path length, phase velocity, and refraction

RffR

R

T

bsTTeffTTR H

R

A

RDHPP Re22 44

ηππ

ση=

University of Kansas

EM Model – TEM Horn Antenna

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University of Kansas

EM Model – TEM Horn Antenna

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University of Kansas

Radar System Transfer Function

• NA Calibration and Amp/Cable Assembly

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P QRS

University of Kansas

Radar System Transfer Function

• Calibration and Amp/Cable

P2P1

Network Analyzer

Horn AntennasAdapters

Amplifier

Reference-Plane

12" Coax

20" Coax

20" Coax

37' Coax

37' Coax

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University of Kansas

Dielectric Half-space Model

• Three-dimensional geometry of refracted ray can be projected onto the plane of incidence (two-dimensional)

Target, S

θ 1

θ 2

Antenna, A

y’

z

n1

n2

Ay’

Sy’

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2'

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21

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University of Kansas

Sensor Geometry• Find the optimal transmitter position that minimizes

the cross-track aperture size, R.

S1

D

0

T

θ1 θ1

φ1φ2

RM R2R1

R'1

R'2

θ2θ2

S2

R

BedrockIce

Tx

β β

yz

x

University of Kansas

Backscatter Characteristics• Bistatic forward scattering characteristics are

approximated with our knowledge of backscatter characteristics.

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Backscatter Angle (deg)

Bac

ksca

tter

Mag

. (dB

)

Range of maximum backscatter angles

Bedrock

Ice

TX/RX

Backscatter

Angle

Bedrock

Ice

RX

Forward scatter

AngleTX

University of Kansas

Advantage of Separation

B

A

TX

TX

Swath

Swath

• As the transmitter moves away from the swath, the ice surface illuminated by the forward scatter cones grows.

• In turn, the minimum required receiver movement decreases (i.e. B < A).

University of Kansas

Disadvantages of Separation

Off-nadirWorse Resolution

NadirBest Resolution

Bedrock

Ice

ρx

• As the transmitter-receiver separation is increased, the angular resolution decreases.

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ρx

• The bedrock surface subtended also increases for the same angular resolution.

University of Kansas

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Plot of Receiver Array Size

• The minimum receive aperture occurs when the transmitter position is 1580 m from the center of the swath.

• The minimum receive aperture is 47 m.

Across-track resolution: 100 m

Ice thickness: 3 km

Frequency: 150 MHz

Swatch Width: 1 km

Backscatter: 7.5 deg

Minimum Receive

Array

TVUXWZY[

\^] Swath

University of Kansas

Results for 3000 m thick ice

60

611020350

21920158015350

484307243510350

748104928315350

1326020150

23447161015150

498371243510150

762112528315150

326602060

27312117101560

53553824351060

799132328315

Min. Monostatic Aperture (m)

Min. Receiver Aperture (m)

Tx Position (m)Max forward-

scatter angle (deg)Frequency

(MHz)

University of Kansas

Monostatic Mode

• For comparison.

• Using a cross-track spatially sampled monostatic array.

S1 S20

Swath

z

xyρ ρ

RM R2R1

RMono

Tx/Rx

University of Kansas

Monostatic vs. Bistatic

• Minimum SAR aperture required using a bistatic configuration (also compared to monostatic).

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University of Kansas

Along-track Array

• Along-track antenna array• Sharpens along-track beam

• Less frequent along-track sampling

• Sum antenna array elements together

• SAR focusing hindered by loss of control over individual elements

Rx

Tx

Rx

Tx

zy

x

Cro

ss-t

rack

Along-track

SAR Antenna Array

TX Vehicle

University of Kansas

Results

• This plot shows the maximum SAR resolution attainable versus aperture size.

• One tenth of a wavelength variation across the aperture was tolerated.

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University of Kansas

Position Errors

• The Radar will derive its position using the global positioning system (GPS).

• GPS’s have errors that are a significant fraction of a wavelength

• Need to answer the question: How do positioning errors effect the performance of the SAR processor?

University of Kansas

Position Errors• Gaussian random process• Correlated errors created by low pass filtering• Topcon GPS system:

• 0.1 m standard deviation in latitude• 0.1 m standard deviation in longitude• 0.2 m standard deviation in elevation

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University of Kansas

Results for σ = 0.05 m

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University of Kansas

Results for σ = 0.1 m

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University of Kansas

Results for σ = 0.1 m (fixed aperture)

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University of Kansas

Sandbox Laboratory

• Test the EM model

• Test the SAR processing algorithm• Ability to determine the position of a target

• Ability to accurately determine the target’s reflectance

University of Kansas

Measurement Setup

• Left side: measurement setup

• Right side: simulation setup

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University of Kansas

A-ScopesLeft side: measured datasetRight side: simulated dataset

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University of Kansas

SAR Processed

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Left side: measured dataset after SAR processingRight side: simulated dataset after SAR processing

University of Kansas

Ten Targets

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University of Kansas

Table of Results

1

1 cm-49 dBAir-filled15 cm10

1 cm-52 dBAir-filled11.5 cm9

6.08 cm-49 dBAir-filled15 cm8

2.24 cm-53 dBAir-filled11.5 cm7

3.16 cm-42 dBMetal10 cm6

2.24 cm-40 dBMetal10 cm5

1.41 cm-42 dBMetal10 cm4

2 cm-35 dBMetal12.5 cm3

5 cm-38 dBMetal10 cm2

2 cm-35 dBMetal12.5 cm

Position ErrorSignal PowerMetal/AirDiameterTarget #

• Max sidelobe is –49 dB

• Signal to sidelobe is at least 4 dB within the region of the target

University of Kansas

Conclusions

• Transmitter Location (Sensor Geometry)• The transmitter position has a very large effect on the size of the

bistatic array.

• Depending on the type of scattering and thickness of the ice, the bistatic mode may or may not be faster than the monostatic mode.

• The bistatic transmitter position that minimizes the receiver cross-track movement was found.

• Along-track Antenna Array• Along-track antenna array could be helpful in expediting the bistatic

measurements.

• For high-precision measurements (e.g. 10 m) its usefulness is limited unless each element can be controlled individually.

University of Kansas

Conclusions

• Position Errors• Position errors can be very severe at higher frequencies. Increasing

aperture length does not help position errors.

• GPS errors need to be characterized in terms of magnitude of relative error and error correlation over time and space.

• Sandbox lab tests showed:• First-order EM Model gives results consistent with the measured

results

• Ability to position targets to within a few centimeters

• Ability to distinguish targets with different reflectivities (with similar targets giving consistent reflectivities)