Mr. Håkan Larsson Profile

Håkan Larsson

Senior Research Engineer at Swedish Defence Research Agency

SPIE Involvement:

Author

Publications (32)

SPIE Journal Paper | 27 September 2016

Continuously scanning time-correlated single-photon-counting single-pixel 3-D lidar

Markus Henriksson, Håkan Larsson, Christina Grönwall, Gustav Tolt

OE, Vol. 56, Issue 03, 031204, (September 2016) https://doi.org/10.1117/12.10.1117/1.OE.56.3.031204

KEYWORDS: Sensors, LIDAR, Pulsed laser operation, 3D acquisition, Clouds, Vegetation, Signal processing, Detector arrays, Distance measurement, Eye

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Proceedings Article | 13 May 2016 Paper

Application and capabilities of lidar from small UAV

Michael Tulldahl, Håkan Larsson, Gustav Tolt, Fredrik Bissmarck, Christina Grönwall, Jonas Nordlöf

Proceedings Volume 9832, 98320V (2016) https://doi.org/10.1117/12.2224258

KEYWORDS: LIDAR, Unmanned aerial vehicles, Clouds, 3D acquisition, 3D image processing, Target detection, Target recognition, Roads, 3D metrology, Vegetation

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Proceedings Article | 16 October 2015 Paper

3D sensing and imaging for UAVs

Christina Grönwall, Gustav Tolt, Patrik Lif, Håkan Larsson, Fredrik Bissmarck, Michael Tulldahl, Markus Henriksson, Per Wikberg, Mirko Thorstensson

Proceedings Volume 9649, 96490C (2015) https://doi.org/10.1117/12.2192834

KEYWORDS: Unmanned aerial vehicles, Sensors, LIDAR, 3D modeling, 3D acquisition, Visualization, Target detection, Clouds, Signal processing, Data modeling

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Proceedings Article | 16 October 2015 Paper

Passive and active EO sensing of small surface vessels

Ove Steinvall, Folke Berglund, Lars Allard, Johan Öhgren, Håkan Larsson, Elias Amselem, Frank Gustafsson, Endre Repasi, Peter Lutzmann, Benjamin Göhler, Marcus Hammer, Kennedy McEwen, Ken McEwan

Proceedings Volume 9649, 96490I (2015) https://doi.org/10.1117/12.2195320

KEYWORDS: Sensors, Cameras, Mid-IR, Visibility, Short wave infrared radiation, Profiling, Infrared cameras, Target detection, Imaging systems, Clouds

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Proceedings Article | 16 October 2015 Paper

Accuracy evaluation of 3D lidar data from small UAV

H. Tulldahl, Fredrik Bissmarck, Håkan Larsson, Christina Grönwall, Gustav Tolt

Proceedings Volume 9649, 964903 (2015) https://doi.org/10.1117/12.2194508

KEYWORDS: LIDAR, Calibration, Unmanned aerial vehicles, Clouds, Sensors, Microelectromechanical systems, Data processing, Neodymium, Ions, Data modeling

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Proceedings Article | 19 May 2015 Paper

Active and passive EO sensing for the detection of humans and handheld objects

Ove Steinvall, Håkan Larsson, Magnus Petterson

Proceedings Volume 9465, 946507 (2015) https://doi.org/10.1117/12.2177076

KEYWORDS: Short wave infrared radiation, Near infrared, Sensors, Weapons, Cameras, Picosecond phenomena, Firearms, Active remote sensing, Reflectivity, Visibility

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Proceedings Article | 13 October 2014 Paper

Lidar on small UAV for 3D mapping

H. Michael Tulldahl, Håkan Larsson

Proceedings Volume 9250, 925009 (2014) https://doi.org/10.1117/12.2068448

KEYWORDS: LIDAR, Calibration, Unmanned aerial vehicles, Clouds, Sensors, Reflectivity, Laser scanners, Data processing, 3D acquisition, Scanners

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Small UAV:s (Unmanned Aerial Vehicles) are currently in an explosive technical development phase. The performance of UAV-system components such as inertial navigation sensors, propulsion, control processors and algorithms are gradually improving. Simultaneously, lidar technologies are continuously developing in terms of reliability, accuracy, as well as speed of data collection, storage and processing. The lidar development towards miniature systems with high data rates has, together with recent UAV development, a great potential for new three dimensional (3D) mapping capabilities. Compared to lidar mapping from manned full-size aircraft a small unmanned aircraft can be cost efficient over small areas and more flexible for deployment. An advantage with high resolution lidar compared to 3D mapping from passive (multi angle) photogrammetry is the ability to penetrate through vegetation and detect partially obscured targets. Another advantage is the ability to obtain 3D data over the whole survey area, without the limited performance of passive photogrammetry in low contrast areas. The purpose of our work is to demonstrate 3D lidar mapping capability from a small multirotor UAV. We present the first experimental results and the mechanical and electrical integration of the Velodyne HDL-32E lidar on a six-rotor aircraft with a total weight of 7 kg. The rotating lidar is mounted at an angle of 20 degrees from the horizontal plane giving a vertical field-of-view of 10-50 degrees below the horizon in the aircraft forward directions. For absolute positioning of the 3D data, accurate positioning and orientation of the lidar sensor is of high importance. We evaluate the lidar data position accuracy both based on inertial navigation system (INS) data, and on INS data combined with lidar data. The INS sensors consist of accelerometers, gyroscopes, GPS, magnetometers, and a pressure sensor for altimetry. The lidar range resolution and accuracy is documented as well as the capability for target surface reflectivity estimation based on measurements on calibration standards. Initial results of the general mapping capability including the detection through partly obscured environments is demonstrated through field data collection and analysis.

Proceedings Article | 29 May 2014 Paper

Ladar-based IED detection

Philip Engström, Håkan Larsson, Dietmar Letalick

Proceedings Volume 9072, 907216 (2014) https://doi.org/10.1117/12.2049524

KEYWORDS: LIDAR, Improvised explosive devices, Roads, Improvised explosive device detection, Scanners, Sensors, Imaging systems, Cameras, Clouds, Global Positioning System

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Proceedings Article | 15 October 2013 Paper

Geometric calibration of thermal cameras

Philip Engström, Håkan Larsson, Joakim Rydell

Proceedings Volume 8897, 88970C (2013) https://doi.org/10.1117/12.2030952

KEYWORDS: Calibration, Cameras, Aluminum, Visualization, Thermography, Distortion, Image visualization, Sensors, Reflectivity, Infrared cameras

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There exist several tools and methods for camera resectioning, i.e. geometric calibration for the purpose of estimating intrinsic and extrinsic parameters. The intrinsic parameters represent the internal properties of the camera such as focal length, principal point and distortion coefficients. The extrinsic parameters relate the cameras position to the world, i.e. how is the camera positioned and oriented in the world. With both sets of parameters known it is possible to relate a pixel in one camera to the world or to another camera. This is important in many applications, for example in stereo vision. The existing methods work well for standard visual cameras in most situations. Intrinsic parameters are usually estimated by imaging a well-defined pattern from different angles and distances. Checkerboard patterns are very often used for calibration since it is a well-defined pattern with easily detectable features. The intersections between the black and white squares form high contrast points which can be estimated with sub pixel accuracy. Knowing the precise dimension and structure of the pattern makes enables calculation of the intrinsic parameters. Extrinsic calibration can be performed in a similar manner if the exact position and orientation of the pattern is known. A common method is to distribute markers in the scene and to measure their exact locations. The key to good calibration is well-defined points and accurate measurements. Thermal cameras are a subset of infrared cameras that work with long wavelengths, usually between 9 and 14 microns. At these wavelengths all objects above absolute zero temperature emit radiation making it ideal for passive imaging in complete darkness and widely used in military applications. The issue that arises when trying to perform a geometric calibration of a thermal camera is that the checkerboard emits more or less the same amount of radiation in the black squares as in the white. In other words, the calibration board that is optimal for calibration of visual cameras might be completely useless for thermal cameras. A calibration board for thermal cameras should ideally be a checkerboard with high contrast in thermal wavelengths. (It is of course possible to use other sorts of objects or patterns but since most tools and software expect a checkerboard pattern this is by far the most straightforward solution.) Depending on the application it should also be more or less portable and work booth in indoor and outdoor scenarios. In this paper we present several years of experience with calibration of thermal cameras in various scenarios. Checkerboards with high contrast both for indoor and outdoor scenarios are presented as well as different markers suitable for extrinsic calibration.

Proceedings Article | 15 October 2013 Paper

Measurements and analysis of active/passive multispectral imaging

Christina Grönwall, Dominique Hamoir, Ove Steinvall, Håkan Larsson, Elias Amselem, Peter Lutzmann, Endre Repasi, Benjamin Göhler, Stéphane Barbé, Olivier Vaudelin, Michel Fracès, Bernard Tanguy, Emmanuelle Thouin

Proceedings Volume 8897, 889705 (2013) https://doi.org/10.1117/12.2028647

KEYWORDS: Sensors, Near infrared, Reflectivity, Short wave infrared radiation, Multispectral imaging, Turbulence, Long wavelength infrared, Transmission electron microscopy, Visualization, Target recognition

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Proceedings Article | 20 May 2013 Paper

Military forensic use of handheld 3D camera

Håkan Larsson, Dietmar Letalick

Proceedings Volume 8731, 873111 (2013) https://doi.org/10.1117/12.2015233

KEYWORDS: Forensic science, Sensors, 3D metrology, Cameras, 3D modeling, Improvised explosive devices, Stereoscopic cameras, 3D vision, Video, Clouds

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Proceedings Article | 19 November 2012 Paper

A decade of experience from commercial 3D laser range sensors for ground applications

Håkan Larsson

Proceedings Volume 8542, 854202 (2012) https://doi.org/10.1117/12.2009524

KEYWORDS: Sensors, LIDAR, 3D acquisition, Laser applications, 3D image processing, Clouds, 3D scanning, 3D metrology, Laser scanners, 3D modeling

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Proceedings Article | 6 October 2011 Paper

Results of ACTIM: an EDA study on spectral laser imaging

Dominique Hamoir, Laurent Hespel, Philippe Déliot, Yannick Boucher, Ove Steinvall, Jörgen Ahlberg, Hakan Larsson, Dietmar Letalick, Peter Lutzmann, Endre Repasi, Gunnar Ritt

Proceedings Volume 8186, 81860M (2011) https://doi.org/10.1117/12.903672

KEYWORDS: Sensors, Signal to noise ratio, Laser imaging, LIDAR, Reflectivity, Imaging systems, Target detection, Interference (communication), Polarization, 3D modeling

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Proceedings Article | 5 October 2011 Paper

See around the corner using active imaging

Ove Steinvall, Magnus Elmqvist, Håkan Larsson

Proceedings Volume 8186, 818605 (2011) https://doi.org/10.1117/12.893605

KEYWORDS: Reflection, Reflectivity, Mirrors, Sensors, Imaging systems, Glasses, Receivers, Cameras, Buildings, Radar

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SPIE Journal Paper | 1 April 2011

Spatial filtering for detection of partly occluded targets

Christina Grönwall, Gustav Tolt, Tomas Chevalier, Håkan Larsson

OE, Vol. 50, Issue 04, 047201, (April 2011) https://doi.org/10.1117/12.10.1117/1.3560262

KEYWORDS: Target detection, Sensors, Spatial filters, Target recognition, Image segmentation, Feature extraction, LIDAR, Detection and tracking algorithms, Optical engineering, Data modeling

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Proceedings Article | 9 October 2010 Paper

ACTIM: an EDA initiated study on spectral active imaging

O. Steinvall, I. Renhorn, J. Ahlberg, H. Larsson, D. Letalick, E. Repasi, P. Lutzmann, G. Anstett, D. Hamoir, L. Hespel, Y. Boucher

Proceedings Volume 7835, 78350C (2010) https://doi.org/10.1117/12.865041

KEYWORDS: Imaging systems, LIDAR, Sensors, Target detection, Imaging spectroscopy, Reflectivity, Hyperspectral imaging, 3D acquisition, Polarization, Semiconductor lasers

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Proceedings Article | 9 October 2010 Paper

High range resolution laser scanner with full waveform recording

Dietmar Letalick, Håkan Larsson, Gustav Tolt, Lars Allard, Erika Wollner, Folke Berglund

Proceedings Volume 7835, 783505 (2010) https://doi.org/10.1117/12.864554

KEYWORDS: Sensors, Laser scanners, Pulsed laser operation, Oscilloscopes, LIDAR, Polarization, Picosecond phenomena, Signal processing, Clouds, Vegetation

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Proceedings Article | 29 April 2010 Paper

Scene-based algorithm for range/intensity estimation correction for the flash 3D ladar system

Steven Jordan, Ernest Armstrong, Håkan Larsson, Matthew Gebhardt, Ove Steinvall

Proceedings Volume 7684, 76840Q (2010) https://doi.org/10.1117/12.849734

KEYWORDS: Reflectivity, LIDAR, Sensors, Cameras, Error analysis, Optical filtering, Calibration, Detection and tracking algorithms, Pulsed laser operation, Principal component analysis

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Proceedings Article | 29 April 2010 Paper

Laser imaging of small surface vessels and people at sea

Ove Steinvall, Magnus Elmqvist, Kjell Karlsson, Håkan Larsson, Maria Axelsson

Proceedings Volume 7684, 768417 (2010) https://doi.org/10.1117/12.849388

KEYWORDS: Reflectivity, Target recognition, Image segmentation, Target detection, Imaging systems, Cameras, Infrared imaging, Sensors, Laser range finders, Turbulence

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Proceedings Article | 1 October 2009 Paper

Characterization measurements of ASC FLASH 3D ladar

Håkan Larsson, Frank Gustafsson, Bruce Johnson, Richard Richmond, Ernest Armstrong

Proceedings Volume 7482, 748207 (2009) https://doi.org/10.1117/12.829964

KEYWORDS: Reflectivity, Sensors, Optical spheres, Algorithm development, Detection and tracking algorithms, 3D acquisition, Error analysis, LIDAR, Spherical lenses, 3D metrology

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Proceedings Article | 7 November 2007 Paper

Waveform analysis of lidar data for targets in cluttered environments

Gustav Tolt, Håkan Larsson

Proceedings Volume 6739, 67390A (2007) https://doi.org/10.1117/12.737237

KEYWORDS: Deconvolution, Signal detection, Mining, Pulsed laser operation, Target detection, LIDAR, Sensors, Laser scanners, Vegetation, Land mines

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Proceedings Article | 4 May 2007 Paper

Performance of laser penetration through forest vegetation

Tomas Chevalier, Ove Steinvall, Håkan Larsson

Proceedings Volume 6550, 65500Q (2007) https://doi.org/10.1117/12.717722

KEYWORDS: Vegetation, Sensors, LIDAR, Laser scanners, 3D acquisition, 3D image processing, Laser systems engineering, Optoelectronics, Clouds, Camouflage

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SPIE Journal Paper | 1 November 2006

Characterizing laser radar snow reflection for the wavelengths 0.9 and 1.5 μm

Håkan Larsson, Ove Steinvall, Tomas Chevalier, Frank Gustafsson

OE, Vol. 45, Issue 11, 116201, (November 2006) https://doi.org/10.1117/12.10.1117/1.2386026

KEYWORDS: Reflectivity, LIDAR, Reflection, Optical engineering, Clouds, Calibration, Bidirectional reflectance transmission function, Humidity, Laser scanners, Roads

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Proceedings Article | 5 October 2006 Paper

MOMS: multi-optical mine detection system: project overview

Anna Linderhed, Stefan Sjökvist, Ove Steinvall, Dietmar Letalick, Gustav Tolt, Tomas Chevalier, Sten Nyberg, Håkan Larsson, Magnus Uppsäll, Dennis Menning

Proceedings Volume 6395, 639503 (2006) https://doi.org/10.1117/12.690379

KEYWORDS: Land mines, Mining, Sensors, LIDAR, Vegetation, Luminescence, Thermography, Reflectivity, Target detection, Reflection

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Proceedings Article | 5 October 2006 Paper

Registration and change detection techniques using 3D laser radar data from natural environments

Gustav Tolt, Anders Wiklund, Pierre Andersson, Tomas Chevalier, Christina Grönwall, Frank Gustafsson, Håkan Larsson

Proceedings Volume 6396, 63960A (2006) https://doi.org/10.1117/12.690189

KEYWORDS: LIDAR, Data acquisition, Environmental sensing, Clouds, 3D acquisition, Sensors, Automatic target recognition, Image registration, Laser systems engineering, Defense and security

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Proceedings Article | 16 May 2006 Paper

Multi-optical mine detection: results from a field trial

Dietmar Letalick, Gustav Tolt, Stefan Sjökvist, Sten Nyberg, Christina Grönwall, Pierre Andersson, Anna Linderhed, Göran Forssell, Håkan Larsson, Magnus Uppsäll

Proceedings Volume 6217, 62170D (2006) https://doi.org/10.1117/12.665517

KEYWORDS: Sensors, Reflectivity, Land mines, LIDAR, Polarization, Target detection, Cameras, Mining, Optical filters, Optical sensors

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Proceedings Article | 5 May 2006 Paper

Data collection and simulation of high range resolution laser radar for surface mine detection

Ove Steinvall, Tomas Chevalier, Håkan Larsson

Proceedings Volume 6214, 62140B (2006) https://doi.org/10.1117/12.665443

KEYWORDS: Mining, LIDAR, Land mines, Sensors, Deconvolution, Reflectivity, Clouds, Vegetation, Pulsed laser operation, Optical simulations

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Proceedings Article | 1 June 2005 Paper

Performance of 3D laser radar through vegetation and camouflage

Ove Steinvall, Hakan Larsson, Frank Gustafsson, Dietmar Letalick, Tomas Chevalier, Asa Persson, Pierre Andersson

Proceedings Volume 5792, (2005) https://doi.org/10.1117/12.603546

KEYWORDS: LIDAR, Vegetation, Camouflage, 3D image processing, 3D acquisition, Visualization, Reflectivity, Stereoscopy, Pulsed laser operation, Clouds

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Proceedings Article | 19 May 2005 Paper

Characterizing laser radar snow reflection for the wavelengths 0.9 and 1.5 micrometer

Hakan Larsson, Ove Steinvall, Tomas Chevalier, Frank Gustafsson, Asa Persson, Pierre Andersson

Proceedings Volume 5791, (2005) https://doi.org/10.1117/12.603573

KEYWORDS: Reflectivity, LIDAR, Reflection, Bidirectional reflectance transmission function, Clouds, Laser scanners, Calibration, Eye, Humidity, Roads

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Proceedings Article | 8 December 2004 Paper

Characterizing targets and backgrounds for 3D laser radars

Ove Steinvall, Hakan Larsson, Frank Gustafsson, Tomas Chevalier, Asa Persson, Lena Klasen

Proceedings Volume 5613, (2004) https://doi.org/10.1117/12.578821

KEYWORDS: Target detection, LIDAR, Vegetation, Reflection, Reflectivity, Sensors, Staring arrays, Eye, Visualization, Associative arrays

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Proceedings Article | 13 September 2004 Paper

3D laser sensing at FOI: overview and a system perspective

Ove Steinvall, Lena Klasen, Christina Gronwall, Ulf Soderman, Simon Ahlberg, Asa Persson, Magnus Elmqvist, Hakan Larsson, Dietmar Letalick, Pierre Andersson, Tomas Carlsson, Markus Henriksson

Proceedings Volume 5412, (2004) https://doi.org/10.1117/12.553808

KEYWORDS: Sensors, LIDAR, Target recognition, Target detection, 3D modeling, Staring arrays, Laser systems engineering, Weapons, Eye, Environmental sensing

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Proceedings Article | 13 September 2004 Paper

Aided target recognition from 3D laser radar data

Lena Klasen, Pierre Andersson, Hakan Larsson, Tomas Chevalier, Ove Steinvall

Proceedings Volume 5412, (2004) https://doi.org/10.1117/12.542434

KEYWORDS: 3D acquisition, Target recognition, LIDAR, Sensors, 3D image processing, 3D modeling, Laser systems engineering, Data modeling, Imaging systems, Clouds

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This paper presents our ongoing research activities on target recognition from data generated by 3-D imaging laser radar. In particular, we focus on future full flash imaging 3-D sensors. Several techniques for laser range imaging are applied for modelling and simulation of data from this kind of 3-D sensor systems. Firstly, data from an experimental gated viewing system is used. Processed data from this system is useful in assisting an operator in the target recognition task. Our recent work on target identification at long ranges, using range data from the gated viewing system, provides techniques to handle turbulence, platform motion and illumination variances from scintillation and speckle noise. Moreover, the range data is expanded into 3-D by using a gating technique that provides reconstruction of the target surface structure. This is shown at distances out to 7 km. Secondly, 3-D target data is achieved at short ranges by using different scanning laser radar systems. This provides high-resolution 3-D data from scanning a target from one single view. However, several scans from multiple viewing angles can also quite easily be merged for more detailed target representations. This is, for example, very useful for recognizing targets in vegetation. Hereby, we achieve simulated 3-D sensor data from both short and long ranges (100 meters out to 7 km) at various spatial resolutions. Thirdly, real data from the 3-D flash imaging system by US Air Force Research Lab (AFRL/SNJM), Wright Patterson Air Force Base, has recently been made available to FOI and also used as input in the development of aided target recognition methods. High-resolution 3-D target models are used in the identification process and compared to the 3-D target data (point cloud) from the various laser radar systems. Finally, we give some examples from our work that clearly show that future 3-D laser radar systems in cooperation with signal- and image analysis techniques have a great potential in the non-cooperative target recognition task and will provide several new and interesting capabilities, for example, to reveal targets hidden in vegetation.

Showing 5 of 32 publications

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