LIDAR and Compressive Sensing

LIDAR and C Compressive i Sensing g Myron Z. Brown 26 February 2009 Compressive Sensing Workshop Work performed under contract to NGA by M.Z. Brown; N...
Author: Damian Caldwell
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LIDAR and C Compressive i Sensing g Myron Z. Brown 26 February 2009 Compressive Sensing Workshop Work performed under contract to NGA by M.Z. Brown; NGA Contract: HM1582-0-R-0004 1

Approved for Public Release, PA Case 09-147B

Outline • Provide an introductory discussion of LIDAR – LIDAR 101 – Key capabilities – Geiger-mode detectors and unique challenges

• Discuss objectives and challenges • Solicit ideas from Compressive Sensing community 2

Approved for Public Release, PA Case 09-147B

LIDAR •

Principle of LIDAR – –



A laser (pulse or continuous wave) is fired from a transmitter and reflected energy is captured (see illustration below) Used to measure distance, velocity, chemical composition, etc.

Nomenclature – – – –

“LIDAR” – light detection and ranging “LADAR” – laser detection and ranging “L “Laser radar” d ” These terms are almost always used interchangeably

TL = Time of travel Receiver

Reflector

Transmitter

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Range and Intensity Products LIDAR Range Reveals 3D Structure

Data from Optech Lynx system

LIDAR Intensity Supports Image Interpretation

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Multiple Returns Light Pulse

first return 2nd return

Can collect multiple returns per pulse along z-axis within the beam width (footprint) First Returns

3rd return

Point Clo oud

Last Returns

last return

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Multiple Looks with Gimbaled LIDAR Elkhorn Lake, Single Pass, No Gimbal, 66k points

Data from NGA ILAP system Approved for Public Release, PA Case 09-147B

Single Pass w/Gimbal, 461k points

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F li Foliage R Removall Before Foliage Removal

Mingo Knob, WV – 0.5m GSD GS

Data from NGA ILAP system Approved for Public Release, PA Case 09-147B

“Bare Earth” reveals roads, trails, etc.

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Vertical Obstructions LIDAR Point Cloud

Data from Optech Lynx system Approved for Public Release, PA Case 09-147B

Vertical Features Extracted from LIDAR

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Geiger-mode Detectors •

A linear-mode avalanche p photo-diode ((APD)) is a p photodetector that is biased at close-to but below the breakdown voltage of the semiconductor, so a single photon in is multiplied to produce at most a few hundred electrons.



A Geiger-mode APD (GmAPD), also called a Single Photon Avalanche Diode (SPAD) operates at a bias voltage above breakdown (SPAD), breakdown, so a single photon in sets off an avalanche, triggering the timing register. Range Histogram Counts Per Range Bin

Early Fires



GmAPD LIDAR data can include p points due to dark current and background light as well as surfaces of interest.



Range histogram is built up over many pulses pulses.

End of Gate

Signal



Each pulse contributes either (1) a “1” to a single range bin or (2) a null result.

Background

• Range Bin (Cropped Near Peak)

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Photon counting methods are employed to determine which points to retain.

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GmAPD Benefits and Challenges • Benefits – Highly sensitive detectors support lower power, longer ranges – Multiple Multiple-pixel pixel APD arrays support increased area rates of coverage

• Challenges Ch ll – Additional processing (and time) required to remove noise – Greater amount of raw data collected for GmAPD compared to conventional LIDAR – Noise in raw data poses additional challenges for compression

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Objectives and Challenges • Explore methods to efficiently manage large volumes of data – Processing – Exploitation p / visualization – Dissemination / storage

• Retain fidelity of datasets

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Conclusions •

LIDAR provides id kkey capabilities bili i – – – –



3D structure Intensity information Foliage penetration Bare earth and vertical obstruction extraction

Geiger-mode detectors present unique benefits and challenges – Lower power, longer ranges, increased area rates of coverage compared to linear mode sensors – More data, noisier data



Goals – Investigate methods to efficiently manage large volumes of data – Retain fidelity of data 12

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www.nga.mil

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