The Radiation Laboratory. Outline: Motivation Motivation Detection of targets camouflaged under foliage using multi-frequency, -polarization, -incidence.

The Radiation Laboratory


Outline:Outline:

MotivationMotivation

Detection of targets camouflaged under foliage using Detection of targets camouflaged under foliage using multi-frequency, -polarization, -incidence angle multi-frequency, -polarization, -incidence angle SAR/INSAR sensors. SAR/INSAR sensors.

Physics-based scattering and propagation modeling of Physics-based scattering and propagation modeling of clutterclutter

Model reduction (extraction of channel parameters)Model reduction (extraction of channel parameters)

Scattering models for hard targets under trees Scattering models for hard targets under trees

High resolution SAR/INSAR image simulatorHigh resolution SAR/INSAR image simulator

3-D SAR at MMW for target detection and identification 3-D SAR at MMW for target detection and identification


MotivationMotivation

A reliable approach for detection and identification of A reliable approach for detection and identification of targets camouflaged under foliage with an acceptable false targets camouflaged under foliage with an acceptable false alarm rate and probability of detection has not yet been alarm rate and probability of detection has not yet been developed.developed.

Due to the complexity of the problem, i.e.Due to the complexity of the problem, i.e.

Signal attenuation, phase-front distortion, poor signal-Signal attenuation, phase-front distortion, poor signal-to-clutter ratio, etc., single sensor approaches (optical, IR, to-clutter ratio, etc., single sensor approaches (optical, IR, radar) do not produce satisfactory results.radar) do not produce satisfactory results.

“ “Capable sensors” operating in diverse modality in Capable sensors” operating in diverse modality in conjunction with novel algorithms can drastically enhance conjunction with novel algorithms can drastically enhance FAR and PD.FAR and PD.

Polarization diversity, Polarization diversity, Multi-frequencyMulti-frequency, Multi-static, , Multi-static, Multi-Multi-incidence angleincidence angle, Interferometric , Interferometric


receiver

Phenomenology of Wave Phenomenology of Wave Scattering & Propagation In ForestScattering & Propagation In Forest

Forest is a complex random medium composed of lossy Forest is a complex random medium composed of lossy scatterers arranged a semi-deterministic scatterers arranged a semi-deterministic

Foliage cause significant attenuation, scattering, field fluctuationFoliage cause significant attenuation, scattering, field fluctuation

To assess performance of radar sensors and target detection To assess performance of radar sensors and target detection algorithms phenomenology of EM wave interaction with foliage algorithms phenomenology of EM wave interaction with foliage must be understood.must be understood.

Scattering from foliage (clutter)Scattering from foliage (clutter)

Target is in the close proximity of many scatterersTarget is in the close proximity of many scatterers

Distortion of phase front and the scattered field from targetDistortion of phase front and the scattered field from target

Signal level, fluctuations, polarization state, Signal level, fluctuations, polarization state,

impulse response, spatial coherence etc. depend on:impulse response, spatial coherence etc. depend on:

Tree densityTree density

Tree typeTree type

Tree height and structureTree height and structure

Satellite

UAV


3D Tree Generation

Lindenmayer systems allow generation of complex tree structure using only a few parameters

An algorithm based on self-similarity

Gross structure: columnar, excurrent, decurren

Biophysical parameters include tree height, trunk diameter(dbh) and branching angle

Tree structure G = G(V,,P)

Axiom = X

Productions:

p1: X FF{-X}F{++X}F{+X}{-X}

p2: F FF


• Tree Type: Coniferous and Deciduous• Inclusion of Botanical Information

– Tapering in Length and Diameter*Law of conservation of cross section

area

– Stochastic Processing– Leaf Arrangement

• Computer Implementation– Tree DNA generation and structure

visualization• Forest stand generation and visualization

(scaling and view angle)

Red Mapler02 = ra

2 + rb2

r0

rarb

Red Pine



Put Matts stuff hereFractal tree details

GUIStill scenario

Movie

Tree generation graphical user interface


Scene Generation and VisualizationScene Generation and Visualization

Land coverLand cover

DEMDEM

Tree stand Tree stand placementplacement

Vehicles, Vehicles, transmitter, transmitter, and receiver and receiver placementplacement

The Radiation Laboratory Propagation & Scattering Model for Forest Canopies

• Scattering from discrete scatterersScattering from discrete scatterers- Trunk: stratified dielectric cylinder- Trunk: stratified dielectric cylinder- Branch: homogeneous dielectric cylinder- Branch: homogeneous dielectric cylinder- Leaf: dielectric disk or needle- Leaf: dielectric disk or needle- Ground: layered dielectric half-space- Ground: layered dielectric half-space

•• Single Scattering is invokedSingle Scattering is invoked

•• Four Scattering Mechanisms are includedFour Scattering Mechanisms are included

ES eik

0r

re

ik0ˆ k i

ˆ k s

rn

n1

N SnEoi

where Sn Snt Sn

gt Sntg Sn

gtgRough

Interface

0 0.05 0.1 0.15 0.2 0.25 0.30

2

4

6

8

10

12

14

16

h-pol.v-pol.

Hei

ght

Attenuation rate NP/m

The Radiation Laboratory Source or Observation Point Source or Observation Point in the Forestin the Forest

Near-field calculation is requiredNear-field calculation is required

Approximate analytical formulations for near-field Approximate analytical formulations for near-field scattering from branches and tree trunks are derive. scattering from branches and tree trunks are derive.

Coherent summation of scattered field from all tree Coherent summation of scattered field from all tree components. (Coherence is important at S-band and lower)components. (Coherence is important at S-band and lower)

Single scattering theory Interaction among tree structures are ignored.

E i

E s

E d

E rE r


The Radiation Laboratory Backscattering Coefficient of Red Pine Forest

150 trees & 100 realization.

Density: 0.1/m2

30 40 50 60 70 80 90 100-60

-50

-40

-30

-20

-10

0

10

ovv

Frequency [MHz]

dB

MeanMax.Min.

30 40 50 60 70 80 90 100-50

-40

-30

-20

-10

0

10

ohh

Frequency [MHz]

dB

MeanMax.Min.

Red pineRed pine

Tree height: 15.3 mTree height: 15.3 m

Crown Height: 9.5 mCrown Height: 9.5 m

45

The Radiation Laboratory Time-Domain Response at a Time-Domain Response at a FDTD Grid PointFDTD Grid Point

0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 2

x 10-7

-1.5

-1

-0.5

0

0.5

1

1.5

time [s]

Ey: h-pol.

With forestWithout forest

attenuation

0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 2

x 10-7

-1

-0.8

-0.6

-0.4

-0.2

0

0.2

0.4

0.6

0.8

1

time [s]

Ex: v-pol.


attenuation0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 2

x 10-7

-0.4

-0.3

-0.2

-0.1

0

0.1

0.2

0.3

0.4

time [s]

Ez: v-pol.


dispersion

Note: Small effect of forest

Frequency: 30MHz – 100MHz

10 trees are considered.

Dielectric constants: 21.7 + i14.6 for branch

9.8 + i1.7 for ground.

Height of tree: 15m, Diameter of trunk: 22cm.

45o Incidence angle.


Time-domain ResponseTime-domain Response Observation point is 1m above the ground inside a pine forest.Observation point is 1m above the ground inside a pine forest.

v-pol. wave is incident at v-pol. wave is incident at 4040oo, and BW 1GHz (, and BW 1GHz (11GHz – GHz – 22GHz).GHz).

30 40 50 60 70-0.4

-0.2

0

0.2

0.4

0.6Free SpaceForest Channel: Mean field

Time[ns]

V/m

Ez

30 40 50 60 70-0.4

-0.2

0

0.2

0.4

0.6

Time[ns]

[V/m

]

Free SpaceForest Channel: Total field

V/m

Time[ns]

Ez

Severe distortion due to trees

& Dispersion

The Radiation Laboratory Interaction of Foliage and Target Hybrid Interaction of Foliage and Target Hybrid Frequency/Time-Domain SimulationsFrequency/Time-Domain Simulations

1.1. Using the forest model, calculate time domain response of several Using the forest model, calculate time domain response of several trees in the proximity of the target at FDTD grids on a box (excitation).trees in the proximity of the target at FDTD grids on a box (excitation).

h-pol. or v-pol.

2. Using FDTD, compute scattering from the target on the same grid Using FDTD, compute scattering from the target on the same grid points.points.

including all interactions


3. To calculate the interaction between the target and the forest, reciprocity theorem is used. After exchanging observation & source points, use the previously calculated scattering property of the forest to obtain the final backscattering result.

Observation point

Source point

exchanging

Note: Using this procedure, interaction between forest & target is taken account into up to first order.

Hybrid Frequency/Time-Domain Hybrid Frequency/Time-Domain Simulations (Cont.)Simulations (Cont.)


Validation

A 2x2x2 FDTD mesh is used to model free space within the forest (in the absence of any vehicles).

The same problem is solved by a pure MoM code.

Results of the two methods are in excellent agreement.

(y)(z)

(x)

2x2x2 FDTD mesh and electric field component that is plotted in the figure on the right.

FDTD simulation parameters :

x = y = z = 0.3 m

t = 0.314 nsec

Validation of Hybrid Frequency/Time-Domain Modeling

A FDTD box around the

observation point


Discretized HUMVEE for Discretized HUMVEE for FDTD AnalysisFDTD Analysis

x

y

z400

Ei

Bistatic Scattering From Bistatic Scattering From HUMVEEHUMVEE


Current Distribution over the HUMVEECurrent Distribution over the HUMVEE

Preliminary Results

The Radiation Laboratory Field Distribution On the FDTD Box(2 GHz)

v-pol. incidenceh-pol. incidence

Note : Considerable distortion due to trees.


Mean Field at receiver is of the form:Mean Field at receiver is of the form:

Functional to macromodel mean field should be of similar formFunctional to macromodel mean field should be of similar form such as Prony’s exponential series expansion:such as Prony’s exponential series expansion:

According to Foldy’s approximation According to Foldy’s approximation < < S S > in forward > in forward direction, remembering:direction, remembering:

Macromodeling of Field Macromodeling of Field Statistics – Mean FieldStatistics – Mean Field

jαβkCeE effθz/jkT

ieff wherecos

pqSk

NIm

2

0


<ETvx>

Pine Forest - Mean Field

<EThy> Simulated Data

Macromodel

i = 45o

Prony’s order = 3

<ETvz>


Standard deviation is a smooth function of f It is therefore possible to macromodel the standard deviation with a functional in the form of a Taylor series polynomial:

Model reduction: Field STD

std(Ethy)

std(Etvx)

std(Etvz)


Spatial Correlation

-5 0 50

0.2

0.4

0.6

0.8

1h-pol.

Calculated1/(1+ ax)

a = 1.58

-5 0 50

0.2

0.4

0.6

0.8

1

v-pol.

Calculated1/(1+ ax)

a = 1.07

iE

Observation line

Note: Since observation line is inside the shadow region, field should be highly correlated.

Model Reduction: Spatial Correlation


VV Polarization HH PolarizationDirection of Flight

Incr

easi

ng R

ange

0dBsm Point Target 0dBsm Point Target

Michigan SAR Image Simulator Geometry


Future Works

1.1. Use physics-based model for generating synthetic multi-Use physics-based model for generating synthetic multi-modal data modal data

• Statistics of clutter scattering and channel (Monte Carlo Statistics of clutter scattering and channel (Monte Carlo simulations)simulations)

• Hard target interaction with foliage (model reduction)Hard target interaction with foliage (model reduction)

2.2. Improvement of Forest Model AccuracyImprovement of Forest Model Accuracy

• Including the effects of near-field multiple scattering among Including the effects of near-field multiple scattering among vegetation components.vegetation components.

3.3. Hard target model reduction (scattering centers)Hard target model reduction (scattering centers)

4.4. Implement hybrid foliage/hard target interaction.Implement hybrid foliage/hard target interaction.

5.5. Improve computation time: Parallel processingImprove computation time: Parallel processing


.

Z

BA1

A2

V

H

R

R+²R

h

h: height of a particular pixel

H: height of the radar

sinsincoscosRHh

50 Km X-band

225 Km C-band Swath Width

Shuttle Radar Topography Mission

The Radiation Laboratory. Outline: Motivation Motivation Detection of targets camouflaged under foliage using multi-frequency, -polarization, -incidence.

Documents

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radiation laboratory

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