Eye-safe laser radar 3D imaging

Stettner, Roger; Bailey, Howard; Richmond, Richard D.

doi:10.1117/12.553992

Cited by 38 publications

(14 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Advanced Scientific Concepts, Inc. produces commercially available Flash LIDAR products that measure the time-of-flight of a light pulse to compute distance. The development of an eye-safe 128 × 128 pixel system is given in [16].…”

Section: Figure 3 Flash Lidar Angular Fields-of-viewmentioning

confidence: 99%

Runway obstacle detection using onboard sensors: Modeling and simulation analysis

Vadlamani

Smearcheck

Bhattacharya

et al. 2008

2008 IEEE/AIAA 27th Digital Avionics Systems Conference

View full text Add to dashboard Cite

In recent years, the increasing demand on the national airspace system (NAS) has propelled further research on new technologies, communication systems, sensors and methods to handle the growing congestion around the terminal area. These include programs such as the Runway Incursion Prevention System (RIPS), Automatic Dependent Surveillance -Broadcast (ADS-B), the National Aeronautics and Space Administration's (NASA) Synthetic Vision Systems (SVS) and more recently, NASA's Integrated Intelligent Flight Deck (IIFD) project. One of the aspects of the IIFD is an External Hazard Monitor (EHM) function that interfaces with onboard terrain and obstacle databases, communications, and also with aircraft sensors. The EHM is envisioned to provide improved obstacle detection and hazard evaluation with added integrity and reliability.The work in this paper is performed in support of the EHM function and presents a modeling and simulation framework that models the aircraft sensors, synthesizes their measurements and analyzes their runway obstacle detection capability using both simulations and flight data playback. Various sensor parameters, measurement errors and physical properties of potential runway hazards/objects are evaluated in the simulations. Particular sensors that are considered for this work are: airborne laser scanner (ALS), 3D imaging camera, and forward-looking infrared camera (FLIR). The sensors are evaluated with regard to detection metrics such as probability of detection and time-to-alarm. Furthermore, results from the simulations using playback of actual flight test data in the vicinity of Braxton county airport (K48I), WV and Reno (RNO), NV are presented.

show abstract

Section: Figure 3 Flash Lidar Angular Fields-of-viewmentioning

confidence: 99%

Runway obstacle detection using onboard sensors: Modeling and simulation analysis

Vadlamani

Smearcheck

Bhattacharya

et al. 2008

2008 IEEE/AIAA 27th Digital Avionics Systems Conference

View full text Add to dashboard Cite

show abstract

“…Lidar was selected as the primary sensor for these new algorithms to accomplish ALHAT's task of providing technology that works autonomously under any lighting conditions. In particular, flash lidar [8] is a promising new technology -providing high data rate and instantaneous capture of an entire range image. Currently, ALHAT is developing a flash lidar sensor with a 5cm range precision that will be able to detect 30cm-high hazards when viewed from a 1000m slant range at a 15-degree path angle.…”

Section: Introductionmentioning

confidence: 99%

Analysis of flash lidar field test data for safe lunar landing

Johnson

Keim

Ivanov

2010

2010 IEEE Aerospace Conference

View full text Add to dashboard Cite

In May 2008, the Autonomous Landing and Hazard Avoidance Technology (ALHAT) Project conducted a helicopter field test of a commercial flash lidar to assess its applicability to safe lunar landing. The helicopter flew several flights, which covered a variety of slant ranges and viewing angles, over man-made and natural lunar-like terrains. The collected data were analyzed to assess the performance of the sensor and the performance of two algorithms: Hazard Detection (HD) and Hazard Relative Navigation (HRN). The collected flash lidar data were also used to validate a high fidelity flash lidar software model used in ALHAT Monte Carlo simulations. The field test results, combined with prior simulation results, advanced the technology readiness level of the HD algorithm to TRL 5 and the HRN algorithm to TRL 4. 12

show abstract

“…Of special interest is the development of 3-D focal plane arrays [2,3,4] and new range gated cameras [5, 6 ,7, 8] which can provide high resolution 3-D image information during one or a few short laser pulses. Which ever technical scheme these 3-D imaging devices will adopt, they will all be able to enhance the capability for seeing through vegetation, camouflage and windows by adding the 3rd dimension.…”

Section: Introductionmentioning

confidence: 99%

Performance of 3D laser radar through vegetation and camouflage

Steinvall

Larsson

Gustafsson

et al. 2005

Laser Source and System Technology for Defense and Security

View full text Add to dashboard Cite

One of the more exciting capabilities foreseen for future 3-D imaging laser radars is to see through vegetation and camouflage nettings. We have used ground based and airborne scanning laser radars to collect data of various types of terrain and vegetation. On some occasions reference targets were used to collect data on reflectivity and to evaluate penetration. The data contains reflectivity and range distributions and were collected at 1.5 and 1.06 µm wavelength with range accuracies in the 1-10 cm range. The seasonal variations for different types of vegetation have been studied. A preliminary evaluation of part of the data set was recently presented at another SPIE conference.Since then the data have been analyzed in more detail with emphasis on testing algorithms and future system performance by simulation of different sensors and scenarios. Evaluation methods will be discussed and some examples of data sets will be presented.

show abstract

Eye-safe laser radar 3D imaging

Cited by 38 publications

References 0 publications

Runway obstacle detection using onboard sensors: Modeling and simulation analysis

Runway obstacle detection using onboard sensors: Modeling and simulation analysis

Analysis of flash lidar field test data for safe lunar landing

Performance of 3D laser radar through vegetation and camouflage

Contact Info

Product

Resources

About