Full Waveform LiDAR Understanding full waveform and how it works Jamie Young Senior Manager-LiDAR Solutions - AeroMetric.

Full Waveform LiDARUnderstanding full waveform and how it worksJamie YoungSenior Manager-LiDAR Solutions - AeroMetric

TOPICS History and background

What is Full Waveform

How does it work Specifications Hardware Process and Software Application

comparisonFull Waveform

BenefitsQuestions?

History of full waveform digitization almost as old as LIDAR

1994 Capability exists in bathymetric systems

2002 2d visualization concepts for pseudo-waveform data

2005 Waveform digitizing adapted to terrestrial use

2006 Gaussian waveform decomposition used in Bathymetric systems

2009 Capability available from all major manufacturers LAS 1.3 file format released TerraScan processing of waveform data

Glossary -frequently used termsFWD - Full Waveform DigitizationMRI - Multiple Returns with Intensity

Minimum return separation - minimum range difference for which independent range/intensity measurements can be made

Sample depth - resolution of the intensity measurement made at each digitizing interval

Sample interval- time interval (usually in nanoseconds) between intensity samples

Waveform length -number of samples, or total distance, digitized within the capture waveform

What is Full waveform?

The laser pulse is emitted and all the return information of that pulse is received back to the receiver and stored.

The system needs to be set up to store the amount of information desired 64 samples 128 samples 256 samples

The return information needs to be converted to usable data Basically, the full waveform data is converted to discrete

return information

What technology is used?

The systems used are the same as what is used for traditional LiDAR sensors with one exception. A full waveform digitizer

GPS IMU Laser Scanner

Footprint

Return waveform is generated by all reflective

surfaces within the

laser footprint

LIDAR waveformhow is it created? Multiple return pulses are

generated as the laser pulse hits various levels in the forest canopy, creating in total a complete return waveform

Waveform measurement is a natural extension of the conventional “discrete-return + intensity” measurement process

Laser

Footp

rin

t

Start Pulse

Detector Signal

T1 ,

I 1 Tn

,

I n

Full Waveform Digitization (FWD) basic concept

LIDAR waveform visualization

Each output laser pulse will hit a unique combination of surfaces on the terrain below:- Different elevation

- Different percent of footprint intercepted at each foliage level

- Different reflectivity of intercepted surfaces

Each output laser pulse will result in a unique waveform shape

PULSE 1 PULSE 2

PULSE 4

Pu

lse

3

PULSE 5

What is Full Waveform Digitization?capturing the complete return, not just the peaks Conventional discrete return

electronics capture only the exact time of the peaks of independently-recognized return pulses

Peak intensity is also measured In FWD systems, the entire

return signal is measured, allowing capture of subtle deviations in the shape of the reflected pulse as compared to the shape of the outbound laser pulse

Discrete Returns

Waveform

Exploiting individual waveformsGaussian decomposition for finding “buried” data

Gaussian decomposition Return signal from ground Return signal digitized at user-selected

interval (typically 1 ns; equivalent to ~15 cm height)

Fitting of first return Gaussian component Fitting of second Gaussian component Fitting of third Gaussian component

Note: Each Gaussian component must be fitted for: Time of occurrence Peak amplitude Pulse width

Benefit: any “stretching” of pulse detected can be used to indicate vegetation height on ground (and automatic adjustment of range) or inclined surfaces

AeroMetric (Leica ALS-70) SpecificationsWDM65 Waveform Digitizer ModuleSpecification Value

Equivalent tree heightMaximum waveform rate(waveforms captured for every other laser shot if

pulse rate>120 kHz)

120 kHz

Sample depth, Sample interval

256 samples @ 1.0 ns128 samples @ 1.0 ns256 samples @ 2.0 ns128 samples @ 2.0 ns 64 samples @ 2.0 ns256 samples @ 4.0 ns

38.4 m 19.2 m 76.8 m 38.4 m 19.2 m153.6 m

Integration New internal DLMWeight 1.0 kgPower 77 W

Typical Altitude 2400 AGLStorage 512 GB SSD

Operating envelopemax waveform rate versus slant range

At pulse rates below 120 kHz, waveforms captured at laser pulse rate

At pulse rates above 120 kHz, waveforms capture for every other pulse, up to 200 kHz (150 kHz for ALS50-II)

Hardware configurationfull waveform digitizing for ALS Upcoming release – announce 17 Nov

2009 Core is new “FWD-ready” Data Logger

Module (DLM65) – installed in all new ALS60 systems

Existing HDD replaced by 160 GB SATA SSD (MM60) and allows missions up to 7620 m AMSL equivalent cabin pressure

3 variations Option on new ALS60 (771706) Upgrade on fielded ALS60 (771708) Upgrade on fielded ALS50-II (773668 +

771707) Waveform viewer software + ALSPP data

output in LAS 1.3 format

Hardware detailsDLM65 / digitizer kit

DLM65 chassisWaveform Interface PCB added to System Controller tray (signal splitter)Double-wide CPU replaced with faster single-wide CPU with on-board SATA driver (releases 2 slots)Slot BlockerExisting 32-bit DIO PCB for System Controller data logging remains

FWD kit2x waveform digitizer PCB (60 kHz max each)1x time synchronizer PCBFirmware license

DLM Power supply hard mounted to card cage (releases 2 slots)Baffle to direct airflow

Some points about FWD

Intensities must be digitized at <2 ns intervals to minimize aliasing, though 1 ns more common

1 ns in time represents 0.15 m in range (i.e., elevation) Signal amplitude at each interval typically digitized at 8-bit

resolution (i.e., one byte) Therefore, 256 additional bytes of waveform data needed to

digitize the return waveform from a 38.4 meter-tall object @ 1 ns intervals

Range data is still be measured independently to achieve typical 1.5 cm (i.e., 100 ps) range resolution

Using waveform data for classification concept Assumes that waveform shape/content, as opposed to mere

extraction of equivalent discrete returns, is used to classify object which reflected laser pulse

Assumes that waveform is compared to a “catalog” of “typical” waveforms for different target classes

Software FWD-equipped systems release summary

Software Release Number

Comments

TracGUI 2.73 #2

Datalogger 7.1.0.23

FCMS 3.20 Officially released beta to be used only for FWD-equipped; otherwise use 3.15 even for FWD-ready systemsFinished testing 10 November 2009

Intel SSD 2CV102HA

ALSPP 2.70 #7 Executable version only – works OKStill need installable version

WaveViewer

1.0.0.4 Executable version only – works OKStill need installable version

TerraScan 9.15 Released by Terrasolid November 2009

FWD post processing Overview ALS Post Processor

Support is available. v2.73 #2 (or greater) Outputs LAS 1.3 type 4 files

Wave Viewer Utility. v1.0.0.4 (or greater) Simple LAS 1.3 Waveform file viewer

TerraScan (See other CSS workflow documentation for details) Support for LAS 1.3 released Oct ’09. v9.14 (on www.terrasolid.fi) The following features are included:

View waveform data for a selected point in the point cloud Scan the waveform for returns that were too close together for the discrete-

ranging electronics to detect or because the returns were below the threshold discriminator (i.e., creates a new “discrete” return)

No other calibration needed

FWD processing directory structure

FWD - flight planning

No support for waveform data collection in FPES initially (i.e., waveform capture settings must be manually entered in FCMS)

Four settings control system configuration for waveform capture Pre-trigger samples (configured in FCMS hardware configuration) Number of samples Sample interval Maximum pulse rate

Options can be preconfigured or changed during flight execution

FWD - flight execution using FCMS

FWD -flight execution with FCMS

FWD - TracGUI real-time waveform display

Waveforms are shown in this display, in flight, while on- line using F4 F4 W command

Classification flowchart

Sample waveform

Target waveform

1

Target waveform

2

Target waveform

3

Assign class

Match?

Compare sample waveform to target

waveform

Load sample waveform

Load next target

waveform

Any target samples left?

No match

Yes

No

No

Yes

Wave Viewer screen

Data outputwaveform viewing and access

Wave Viewer Main statistics (sample rate, waveform depth,

waveform sequence number, timing data) Allows scrolling through entire captured series of

waveforms Displays waveform Displays time/intensity indicator (2 black boxes

near waveform peaks) from discrete-return data collection that operates in parallel with waveform capture

TerraScan Waveform display associated with any given

discrete-return point Future expansion allows possible improvement by

deriving additional parameter (pulse stretch) in pre-processing and passing these on to TerraScan for more efficient//accurate filtering

FWD - ALS Post Processor/ing

Select “Process Waveform Data” option.

Software looks for “RawWfd” folder with matching mission ID.

Automatically output LAS 1.3 file for each flight line

FWD - Wave Viewer

X-axis: sample (number), time (ns) or range (m)

Y–axis: signal strength (volts or counts)

Used to review data and confirm that waveform data is correctly correlated with discrete-return data

FWD - post processing: Wave Viewer

In this example, two returns were missed by the discrete-return ALS range electronics The first missed pulse was too

close to the first pulse to be seen The second missed pulse was too

small to be seen.

FWD - post processing: intensity scale Note: Y scale factor of the raw intensity values and the waveform

digitized values are not the same. Intensity PCB in the SCM is designed to use the full 8-bits for the typical signal amplitudes The waveform digitizer PCB has limited configuration options so the the option closest to

the Intensity PCB scale factor is used The intensity board uses the following scale (latest revision only,

earlier versions may have different scale factors): 0.110V signal = 10 counts 3.7V signal = 250 counts

The waveform digitizers use the following scale: 0 V = 0 counts 4.1V = 255 counts

FWD - post processing: sample files Sample LAS 1.3 files will be located on FTP site Contents

Wave Viewer LAS 1.3 file format specification (can be released to public) Data set

Note: Contact PM for FTP information

FWD –post processingTerraScan displays

FWD - post processing TerraScan capabilities

Viewing of waveform profile when clicking on discrete points in the point cloud

Mensurating more discrete returns from WF data (“extract echos” feature)

FWD -TerraScan V10.17+ “Extract Echoes” feature Allows extraction of small signals via user-adjustable “ambient noise”

threshold Allows extraction of returns at less than the minimum separation

dictated by discrete-return electronics (see cyan-colored points below)

MRI versus FWD: Applications

Application or surface type MRI LIDAR FWD LIDAR

Tree height Yes Yes, but overkill

Forest canopy structure Maybe, species dependent Yes, but may be overkill

Forest floor Yes, depending on floor cover Yes, but may be overkill

Tall dense grass No Yes

Power line profiling YesMaybe, if lines separated

by less than minimum separation distance

Tree species identification Maybe, species dependent Yes

Sloped surface detection NoYes, but height difference

over laser footprint must be ~1 sample interval

Bathymetry No Yes

Using waveform data for classification caveats Each return waveform highly dependent on

Specific geometry (i.e., portion of laser footprint intercepted at different heights above ground)

Reflectivity of each surface intercepting a portion of the laser footprint Therefore

Waveforms returned from a group of nearby laser shots may have to be averaged to arrive at a more consistent “typical” waveform for comparison to the target waveform library

Waveforms to be averaged must be referenced to some consistent key point (e.g., ground level) before averaging, in order to generate a meaningful comparison

MRI and FWD provide some similar functionality FWD exploitation techniques can extract returns that are “buried” FWD waveforms from a group of adjacent laser shots may need to be

averaged to make automated classification feasible Averaging MRI “pseudo-waveforms” from a group of adjacent laser

shots may be an effective alternative to FWD, especially if LIDAR system can measure intensity for a large enough number of returns for

each outbound laser pulse (e.g., 3+) Inter-return minimum separation distance is small enough (target dependent)

High point density in MRI systems helps to overcome the additional per-pulse information supplied by FWD systems

Some applications may be accomplished by both methods, but may be better suited to one or the other (see table)

Benefits of FWDgetting more from a single flight

Present Extraction of points below the discrimination threshold of discrete-return electronics (weak

returns) Extraction of points with smaller vertical separation than detectable by discrete-return

electronics (close, but not overlapping pulses) Future

Detection of pulse stretching (return pulse wider than laser pulse) indicating Potentially sloped surfaces Low vegetation on ground, indicating need to adjust point elevation downward Improved classification by using combination of return pulse width and spatial context

Indication of biomass by evaluating area contained under the pulse shape

WILDER LiDAR Blog

http://bloglidar.wordpress.com

Thank You

Thank You to Leica for Contributions to this presentation