07-feb-2008rit dirsig ladar/lidar modelingslide #1 ladar/lidar system modeling scott d. brown

07-Feb-2008 RIT DIRSIG LADAR/LIDAR Modeling Slide #1

LADAR/LIDAR System Modeling

Scott D. Brown


Active Laser Sensing Capability

• The DIRSIG model has been enhanced to provide the user community with a very flexible, active laser sensing capability.– The synthetic world is stimulated with a pulsed beam that has a spatial,

spectral and temporal shape.• Elaborate radiative transfer mechanisms reproduce important phenomenology

and “noise” sources in the simulated returns.

– The instrument model captures a time gated, photon arrival stream• Dynamic instrument position and pointing can be incorporated.• Spatially, spectrally and temporally oversampled data products can be produced

to drive back-end sensor models.

Temporal Pulse

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1.2

4 3.5 3 2.5 2 1.5 1 0.5 0

Seconds

Power

x

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Power


• Historical focus on passive multi- and hyper-spectral systems• Driving motivation to simulate active and passive sensors using the

same scenes and scenarios– Perform trade studies between passive and active approaches

– Exploration of active/passive data fusion techniques

– Investigation of advanced exploitation algorithms

• Developed a challenging requirements set:

• Prototype completed in 2002 by Burton and Brown• Adapted prototype model and completed integration in 2004

• Rigorous atmospheric interactions• Participating mediums• Multiple bounce/scattering• Inclusion of passive returns• Complex scene geometries

• Moving platform and scanning effects• Detailed optical descriptions

(BRDF and Scattering models)• Arbitrary time-gated returns• Mono & Bistatic configurations

Active Channel Justification


End-to-End System Modeling

RadiometryPrediction

Focal Plane ReachingPhoton Counts

(as a function of time)

DIRSIG

Geiger-Mode Systems

RIT GmAPDModel

ITT GmAPDModel

Linear-Mode Systems

No Detector Model(yet)

Single rangemeasurement

First, last and otherrange measurement

plus intensity

Typical Products


Research Affiliations

FastMetrix, Inc.


System Parameters

Laser/SourceSpectral PeakSpectral WidthBeam RadiusBeam Divergence AngleBeam ShapePulse PowerPulse DurationPulse PeriodDesired Photon CountBeam Spread (On/Off)Beam Wander (On/Off)Image Wander (On/Off)

Instrument MountMount TypeScan RateStart Time OffsetStart AngleStop Angle

InstrumentFocal LengthReceiver RadiusReceiver Divergence AngleScan RateSignal Gate (Transmit, Receive, Wait)

Focal PlaneSize in pixelsOversamplingSpectral RegionSpectral ResolutionResponse


Noise Sources

• Passive/Environmental flux– The model continues to compute the passive (temporally constant) return from the

Solar/Lunar sources.• This includes atmospherically scattered (aerosol) photons.

• Photon arrival statistics– Incorporate the appropriate uncertainty of photon arrivals in low-count situations.

• Multiply-bounced source photons– Photons may arrive at the sensor at times that are correlated with longer ranges.

• Possible problems when imaging clouds, plumes, tree canopies, etc.

6 ns 7 ns 7 ns


Photon Starvation (1)

• Geiger-mode Avalanche Photo-Diode (GmAPD) LADAR systems can operate in photon starved conditions.– As a result, photon arrival and detection events are very rare.

• The detector technologies used in these cases cannot guarantee the ability to detect every possible return event.– For example, the APDs developed at MIT/LL have been shown to

follow Poisson detection statistics.

• But, this Poisson detection characteristic has benefits– It allows for foliage penetration.


Photon Starvation (2)

• Consider the case of a single leaf over the ground.– The leaf is reflective and transmissive (especially in the NIR region).

– The temporal return profile has two peaks• One for the leaf return and one for the transmitted ground return.

– The detector might not trigger on the first peak, and trigger on the second peak even though it is smaller.

• However, you need to shoot a lot of pulses to observe this low probability event.• To achieve this you interrogate the same scene voxel numerous times.

Leaf Return

Ground Return

Pho

ton

Cou

nts


Demonstrations


Tree Crown Demonstration

Scene Setup

SurfacePhoton Map

TreeCanopy

Ground Floor

“Late”Returns


Camouflaged Vehicle Simulation

• Contains Material and Bump Map made by thresholding image of camouflage– BM smoothed to create

gradients

• Material map contains a “null” material (holes)



High-fidelity 3D modeling and photon mapping accurately

reveals camo net and vehicle underneath for both active and passive simulations

Digital PhotoDigital Photo Passive SimulationPassive Simulation

DIRSIG LADAR Photon MapDIRSIG LADAR Photon Map

Overhead SimulationOverhead Simulation



Time

DIRSIGCAD Models

Height TruthImagery

LADARPulse Cubes

Top of net Spreader Humvee roof

t003 t012 t022 t033

Humvee shadow

t115

Humvee hood

t049


End-to-End System Simulation


End-to-End Topographical LADAR Demo

• Microscene Data Collection (Mar 2004)– MIT Lincoln Labs ALIRT System

• Topographical LADAR• Sinusoidal whisk broom scanner• Scan FOV: 15 deg• Laser Peak = 780 nm• Geiger-mode across-track scanned array

– Pixel Count: 32 x 32

– Nominal Flight Altitude ~1200 m– Diverse Scene Content

• Trees, man-made objects, flat areas, etc.• Some ground truth available

– Data basis for on-going validation effort• Simulated real data collection for demo

purposes at this time

Collection Scenario


Modeling Process

Processing

Topographic Products

Simulated RawInstrument Data

Time-Gated Arriving PhotonCounts Data Cube(s)

Detector/Sensor

Modeling

Detailed Detector/Sensor ModelFill Factor, Probability of Detection

Curves, Detector Response Curves, MTFs, Dark Current, etc…


LADAR at MicroScene1

Time/DistanceGrass on hillGrass on hill

Shed RoofShed Roof

HumveeHumvee ““Late” photons that got “lost” in Late” photons that got “lost” in grassgrass

PortablePortableGeneratorGenerator

Lighter coloredLighter coloreddirtdirt

ShedShed““Shadow”Shadow”


MicroScene1 LADAR DemoD

eriv

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opo-

Pro

duct

Overhead Slant View

DIR

SIG

Pas

sive

Im

ager

y

Slant ViewOverhead

Topographic Products Courtesy of


“Spotlight” Collection Study

Concealed Targets - 45 deg Dwell


Tank with 60 Pulses


Tank with 240 Pulses


Tank with 480 Pulses


Geolocation Errors

• A set simulations using the DIRSIG instrument mount and platform uncertainty features to demonstrate the impact of uncertainty on geolocation and interpretibility.

• Scene consists of a 3D bar target with “tables” of different sizes.– The actual target exists at the MIT/LL flight facility and is routinely

collected by the MIT/LL ALIRT sensor.

~10 m

~26 m


Altitude Errors

• Comparison of baseline simulation and one with a 0.05 meter altitude error.


Cross-Track Pointing Errors

• Comparison of baseline simulation and one with a 0.5 mrad across-track pointing error.


Passive Illumination Effects

• DIRSIG’s LADAR photon flux includes all the passive radiometry of a “traditional” DIRSIG simulation.– Passive illumination from Sun, Moon, sources can affect LADAR

performance.

No Moon (11 PM) Full Moon (4 AM)


Future Work

• Support for geo-located scenes and platforms (in progress)• Track multiple-pulses in flight (in progress)

– Perform studies on the impacts of clouds

• Improved detector modeling– More GmAPD effects (pixel crosstalk, arming triggers, etc.)– Linear mode detector model

• Post-processing system trades– Pulse-to-pulse total power variations– Pulse-to-pulse temporal shape variations (e.g. multiple peaks)

• Improved user tools– Data collection design tools (flight lines, collection scans, etc.)– Sensor configuration and quick-look simulations.

• Enable and verify polarization


Summary

• DIRSIG has an active laser radar capability that has been demonstrated for topographical LADAR and atmospheric LIDAR problems.– The model can be used in a variety of system engineering or asset

utility workflos.

• DIRSIG is a tool available to the government community– Internally supported by RIT, no long term support contract.– Quarterly software updates/releases– Training courses

• DIRSIG development leverages commercial and government funding.– Everyone has access to same version of the model– We team with anyone willing to contribute to the overall capability.


Extra Slides


Implementation


Possible Approaches

• Many models simply render a pulse return at the time or range corresponding to the “target”.– This doesn’t account for several effects:

• Illumination obscurations (shadows).

• Tilted surfaces that temporally stretch and skew returns.

• Optical transmission through surfaces (e.g. glass, leaves, etc.)

• Multiple bounces.

• DIRSIG does have an “preview” mode that will use this approach to quickly give the user notional data.– However, a more robust solution was needed for a rigorous

prediction and absolute radiometry.


Photon Mapping Pass #1:Forward Photon Tracing

• Photon “bundles” are forward, Monte-Carlo ray-traced from the source(s) into the scene.

– A “bundle” is a set of photons that travel together.– Russian Roulette techniques are used to determine absorption, reflected directions,

etc. based on material optical properties.– Travel time is tracked throughout the photon’s flight.

• Each event is recorded into the 3D “photon map” data structure.


Pass #1 Details

• Bundles are shot from the source using a stochastic process– Random position within the exit aperture

• Position density is constrained by user-defined spatial beam shape.

• Currently using direct method for Uniform/Flat/Tophat and Gaussian beams.

• Rejection sampling could be used for TEM profiles.

– Bundle direction is based on position and source divergence.• Methods for turbulence driven divergence have been implemented.

– The beam centroid can be redirected in response to turbulence (e.g. beam wander)– The source is mounted to an agile instrument mount (e.g. scanner) which is

mounted on an agile platform.• Scanner/Mount positioning and platform noise can be modeled.

• Other source properties– Spectral shape is parametrically modeled (Gaussian and Lorentzian)– Temporal shape is currently parametrically modeled.

• A tabulated temporal shape could be added.


O’Shea, Donald C. O’Shea, Donald C. Introduction to Lasers and Their Applications. Introduction to Lasers and Their Applications. Addison-Wesley, 1978.Addison-Wesley, 1978.

Source Lasers

• Transverse Electro-magnetic (TEM) profile defines beam cross-sectional intensity – TEM 00 ≡ Gaussian beam profile (typically considered ideal)

Example laser TEM profiles


Beam Density

• Locations of ground arriving photon bundles from a uniform (left) and Gaussian (right) beam densities with the same beam width.


Participating Mediums

Forward Scattering

Isotropic Scattering

A 2D side-looking view of the photon map with a box containing a scattering medium hovering over the ground plane.


r

Surface CollectionSurface CollectionVolume CollectionVolume Collection

Photon Mapping Pass #2:Photon Collection/Rendering

• Rays are shot from focal plane plane and intersect surfaces

• Photons are collected at each intersected point– Search area/volume is determined by projected detector at range.

• Individual bundles are redirected toward sensor based upon local optical properties

– BRDF or scattering phase function depends on material type.– Received bundles distributed and quantized for listening window and temporal

sampling frequency

• Passive returns added by traditional radiance solvers


Pass #2: Collection

Recorded Photon MapTrace Ray

from DetectorProject FOVIdentify EventsApply Phase Function &

Scattering ProbabilitySum, Range-gate,

& Sample


Pass #2 Details

• The range dependent projected area of the detector is used in the collection search.– That includes within a participating medium

– A surface search area is computed as a projected volume

• Geometry specific reflectance or scattering coefficients are used for each photon bundle collected from the map.– BRDF or scattering is potentially different for each bundle.

– Each bundle is absorbed within a medium based on its specific path length.

• Atmospheric returns analytically evaluated for efficiency– An empirical solution is usually used as for the atmospheric returns.

• Direct calculation is very costly due to low probability of scattering/absorption events in most atmospheres.

• The photon mapping approach can be used instead if the user desires.


Atmospheric Returns

• The scattering coefficient for a dry atmosphere might be approximately 1x10-5 [1/m]– Need to shoot 105 photons into a 1-meter long box to witness a

single scattering event.

• What is a realistic modeling scenario?– Attempt to resolve vertical resolutions of a fraction of a meter.– Interested in a path length of several thousand meters.

• How does that affect this approach?– Need to model ~1010 photons within each spatial detector element

in order to witness a single scattering event within each numerical contribution element.

– Ideally, a few orders of magnitude more to be statistically robust.

• What does that mean?– Need an analytical solution


Atmospheric Returns

• Utilize the analytical solution proposed by Measures.– For the ALIRT system, the returns are a fraction to a handful of a

photons integrated over the full 1,000 meter path.• However, this depends on the type of atmosphere, altitude, etc.

– For different geometries (beam vs. detector FOV) or different altitudes (path lengths), this component of the overall photon count will be larger.

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Atmospheric Properties

• Where do the atmospheric extinction and backscatter coefficients come from?– MODTRAN and/or FASCODE– Only MODTRAN models scattering.– MODTRAN5’s 1/10th wavenumber resolution is nearly small

enough for laser line transmission modeling.

• Backscatter coefficients are not normally output by MODTRAN.– Customized versions of MODTRAN are problematic.– The DIRSIG4 make_adb tool computes the backscatter coefficients

as a function of altitude using a smaller differential volume approach and a pair of MODTRAN runs.


Atmospheric Properties:Extraction Methodology


Temporal Pulse Spread

• Important notes– Smoothness of the temporal shape for a tilted surface is dependant on the number

of bundles available in the collection area.

On a flat surface, all bundles have the same travel time

On a tilted surface, bundles have a range of

travel times

Collection Area Collection Area

3 bundles on top of each other

3 bundles temporally spread out

Integrated return

Integrated return


Temporal Pulse Spread

Scene Setup

DIRSIG accurately simulates the temporal pulse spreading by linear convolution with impulse response of a scene

while still accommodating very high sampling rates

10 deg ~1m difference in range

Pulse width ~13.33 ns instead of 1.5 ns


Other Sources of Geolocation Errors

• Atmospheric turbulence along longer paths with deflect light from the straight line path.– Deflect the beam arriving at the ground from pulse to pulse.

• Sometimes referred to as “beam wander”.• Not such a big deal as long as the projected beam overfills the

detector.

– Deflect the arrivals onto the focal plane.• Sometimes referred to as “image wander”.• The geolocation algorithms assume photons take straight paths.• A deflected arrival will be recorded within the “wrong” pixel and

therefore will be incorrectly located within the scene.

• DIRSIG has some tools for modeling turbulence effects including beam and image wander using Cn

2 characterizations of the turbulence.– Currently not available via the DIRSIG inputs files.

07-feb-2008rit dirsig ladar/lidar modelingslide #1 ladar/lidar system modeling scott d. brown

Documents

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instrument model

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pulsed beam

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ns7 ns slide

time gated