liu.seSök publikationer i DiVA
Ändra sökning
Avgränsa sökresultatet
1 - 33 av 33
RefereraExporteraLänk till träfflistan
Permanent länk
Referera
Referensformat
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • oxford
  • Annat format
Fler format
Språk
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Annat språk
Fler språk
Utmatningsformat
  • html
  • text
  • asciidoc
  • rtf
Träffar per sida
  • 5
  • 10
  • 20
  • 50
  • 100
  • 250
Sortering
  • Standard (Relevans)
  • Författare A-Ö
  • Författare Ö-A
  • Titel A-Ö
  • Titel Ö-A
  • Publikationstyp A-Ö
  • Publikationstyp Ö-A
  • Äldst först
  • Nyast först
  • Skapad (Äldst först)
  • Skapad (Nyast först)
  • Senast uppdaterad (Äldst först)
  • Senast uppdaterad (Nyast först)
  • Disputationsdatum (tidigaste först)
  • Disputationsdatum (senaste först)
  • Standard (Relevans)
  • Författare A-Ö
  • Författare Ö-A
  • Titel A-Ö
  • Titel Ö-A
  • Publikationstyp A-Ö
  • Publikationstyp Ö-A
  • Äldst först
  • Nyast först
  • Skapad (Äldst först)
  • Skapad (Nyast först)
  • Senast uppdaterad (Äldst först)
  • Senast uppdaterad (Nyast först)
  • Disputationsdatum (tidigaste först)
  • Disputationsdatum (senaste först)
Markera
Maxantalet träffar du kan exportera från sökgränssnittet är 250. Vid större uttag använd dig av utsökningar.
  • 1.
    Ahlberg, Jörgen
    et al.
    Swedish Defence Research Agency, Sweden.
    Folkesson, Martin
    Swedish Defence Research Agency, Sweden.
    Grönwall, Christina
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
    Horney, Tobias
    Swedish Defence Research Agency, Sweden.
    Jungert, Erland
    Swedish Defence Research Agency, Sweden.
    Klasén, Lena
    Swedish Defence Research Agency, Sweden.
    Ulvklo, Morgan
    Swedish Defence Research Agency, Sweden.
    Ground Target Recognition in a Query-Based Multi-Sensor Information System2006Rapport (Övrigt vetenskapligt)
    Abstract [en]

    We present a system covering the complete process for automatic ground target recognition, from sensor data to the user interface, i.e., from low level image processing to high level situation analysis. The system is based on a query language and a query processor, and includes target detection, target recognition, data fusion, presentation and situation analysis. This paper focuses on target recognition and its interaction with the query processor. The target recognitionis executed in sensor nodes, each containing a sensor and the corresponding signal/image processing algorithms. New sensors and algorithms are easily added to the system. The processing of sensor data is performed in two steps; attribute estimation and matching. First, several attributes, like orientation and dimensions, are estimated from the (unknown but detected) targets. These estimates are used to select the models of interest in a matching step, where the targetis matched with a number of target models. Several methods and sensor data types are used in both steps, and data is fused after each step. Experiments have been performed using sensor data from laser radar, thermal and visual cameras. Promising results are reported, demonstrating the capabilities of the target recognition algorithms, the advantages of the two-level data fusion and the query-based system.

  • 2.
    Christina, Grönwall
    et al.
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska fakulteten. Swedish Defence Research Agency (Sweden).
    Tolt, Gustav
    Swedish Defence Research Agency (Sweden).
    Signal processing for imaging and mapping ladar: Invited paper2011Ingår i: Proceedings of SPIE, 2011, Vol. 8186Konferensbidrag (Refereegranskat)
    Abstract [en]

    The new generation laser-based FLASH 3D imaging sensors enable data collection at video rate. This opens up for realtime data analysis but also set demands on the signal processing. In this paper the possibilities and challenges with this new data type are discussed. The commonly used focal plane array based detectors produce range estimates that vary with the target's surface reflectance and target range, and our experience is that the built-in signal processing may not compensate fully for that. We propose a simple adjustment that can be used even if some sensor parameters are not known. The cost for the instantaneous image collection is, compared to scanning laser radar systems, lower range accuracy. By gathering range information from several frames the geometrical information of the target can be obtained. We also present an approach of how range data can be used to remove foreground clutter in front of a target. Further, we illustrate how range data enables target classification in near real-time and that the results can be improved if several frames are co-registered. Examples using data from forest and maritime scenes are shown.

  • 3.
    Grönwall, Christina
    et al.
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska fakulteten. FOI.
    Axelsson, Maria
    FOI.
    Follo, Peter
    FOI.
    Camera calibration using automated identification of checkerboard patterns2010Konferensbidrag (Övrigt vetenskapligt)
  • 4.
    Grönwall, Christina
    et al.
    Swedish Defence Research Agency, Department of Laser Systems, Sweden.
    Carlsson, Tomas
    Swedish Defence Research Agency, Department of Laser Systems, Sweden.
    Gustafsson, Fredrik
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
    Performance Analysis of Measurement Error Regression in Direct-Detection Laser Radar Imaging2003Ingår i: Proceedings of the 2003 IEEE Conference on Acoustics, Speech and Signal Processing, 2003, Vol. 6, s. 545-548 vol.6Konferensbidrag (Refereegranskat)
    Abstract [en]

    In this paper a tool for synthetic generation of scanning laser radar data is described and its performance is evaluated. By analyzing data from the system, we recognize objects on the ground. In the measurement system it is possible to add several design parameters, which make it possible to test an estimation scheme under different types of system design. The measurement system model includes laser characteristics, object geometry, reflection, speckles, atmospheric attenuation, turbulence and a direct detection receiver. A parametric method that estimates an object's size and orientation is described. There are measurement errors present and thus, the parameter estimation is based on a measurement error model. The parameter estimation accuracy is limited by the Cramer-Rao lower bound. Validations of both the measurement error model and the measurement system are shown. Data from both models generate parameter estimates that are close to the Cramer-Rao lower bound.

  • 5.
    Grönwall, Christina
    et al.
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska fakulteten.
    Gustafsson, David
    FOI.
    Tolt, Gustav
    FOI.
    Steinvall, Ove
    FOI.
    Experiences from long-range passive and active imaging2015Ingår i: Proceedins of SPIE, 2015, Vol. 9649, s. 96490J-1-96490J-13Konferensbidrag (Refereegranskat)
    Abstract [en]

    We present algorithm evaluations for ATR of small sea vessels. The targets are at km distance from the sensors, which means that the algorithms have to deal with images affected by turbulence and mirage phenomena. We evaluate previously developed algorithms for registration of 3D-generating laser radar data. The evaluations indicate that some robustness to turbulence and mirage induced uncertainties can be handled by our probabilistic-based registration method.

    We also assess methods for target classification and target recognition on these new 3D data. An algorithm for detecting moving vessels in infrared image sequences is presented; it is based on optical flow estimation. Detection of moving target with an unknown spectral signature in a maritime environment is a challenging

    problem due to camera motion, background clutter, turbulence and the presence of mirage. First, the optical flow caused by the camera motion is eliminated by estimating the global flow in the image. Second, connected regions containing significant motions that differ from camera motion is extracted. It is assumed that motion caused by a moving vessel is more temporally stable than motion caused by mirage or turbulence. Furthermore, it is assumed that the motion caused by the vessel is more homogenous with respect to both magnitude and orientation, than motion caused by mirage and turbulence. Sufficiently large connected regions with a flow of acceptable magnitude and orientation are considered target regions. The method is evaluated on newly collected sequences of SWIR and MWIR images, with varying targets, target ranges and background clutter.

    Finally we discuss a concept for combining passive and active imaging in an ATR process. The main steps are passive imaging for target detection, active imaging for target/background segmentation and a fusion of passive and active imaging for target recognition.

  • 6.
    Grönwall, Christina
    et al.
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
    Gustafsson, Fredrik
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
    3D Content-Based Model Matching using Geometric Features2006Rapport (Övrigt vetenskapligt)
    Abstract [en]

    We present an approach that utilizes efficient geometric feature extraction and a matching method that takes articulation into account. It is primarily applicable for man-made objects. First the object is analyzed to extract geometric features, dimensions and rotation are estimated and typical parts, so-called functional parts, are identified. Examples of functional parts are a box's lid, a building's chimney, or a battle tank's barrel. We assume a model library with full annotation. The geometric features are matched with the model descriptors, to gain fast and early rejection of non-relevant models. After this pruning the objectis matched with relevant, usually few, library models. We propose a sequential matching, where the number of functional parts increases in each iteration. The division into parts increases the possibility for correct matching result when several similar models are available. The approach is exemplifi…ed with an vehicle recognition application, where some vehicles have functional parts.

  • 7.
    Grönwall, Christina
    et al.
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
    Gustafsson, Fredrik
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
    Approaches to Object/Background Segmentation and Object Dimension Estimation2006Rapport (Övrigt vetenskapligt)
    Abstract [en]

    In this paper, optimization approaches for object/background segmentation and object dimension/orientation estimation are studied. The data sets are collected with a laser radar or are simulated laser radar data. Three cases are defined: 1) Segmentation of the data set into object and background data. When there are several objects present in the scene, data from each object is also separated into different clusters. Bayesian hypothesis testing of two classes is studied. 2) Estimation of the object’s dimensions and orientation using object data only. 3) Estimation of the object’s dimensions and orientation using both object and background data. The dimension and orientation estimation problem is formulated using non-convex optimization, least squares and, convex optimization expressions. The performance of the methods are investigated in simulations.

  • 8.
    Grönwall, Christina
    et al.
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
    Gustafsson, Fredrik
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
    Least Squares Fitting of Articulated Objects2005Ingår i: Proceedings of the 2005 IEEE Workshop on Advanced 3D Imaging for Safety and Security, 2005, s. 116-Konferensbidrag (Refereegranskat)
    Abstract [en]

    In safety and security applications, one issue is target recognition. In some recognition processes, for vehicle recognition, we must take into account that the target maybe articulated. Vehicles can easily change shape by opening of a door, adding of load etc.This change of shape can be moddled as an articulation. if the articluation of model the target also can be moddled, the mathcing with library modles can be improved. In this paper we propose a method for modular least squares fitting of two 3D point scatters with points correspondence. A method for least squares fitting of a 3D point scatter and a CAD (face) models is also proposed. An example pf modular leats squares fitting two #D point scatters,based on simulated data, is known.

  • 9.
    Grönwall, Christina
    et al.
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
    Gustafsson, Fredrik
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
    Modelling of Laser Radar Systems2006Rapport (Övrigt vetenskapligt)
    Abstract [en]

    In this report background material for some papers are stored. It concerns modelling of laser radar systems for hard targeting. The (returned) laser radar datais used for parameters estimation, where error-in-variables is assumed. The impulse response for some common (target) shapes are derived. The coordinate systems in output data is discussed. The system performance is analyzed using the Cramer-Rao lower bound. The models are developed for a scanning, monostatic system, but some are general enough for other type of systems.

  • 10.
    Grönwall, Christina
    et al.
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
    Gustafsson, Fredrik
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
    Millnert, Mille
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
    Ground Target Recognition using Rectangle Estimation2005Rapport (Övrigt vetenskapligt)
    Abstract [en]

    We propose a ground target recognition method based on 3-D laser radar data. The method handles general 3-D scattered data. It is based on the fact that man-made objects of complex shape can be decomposed to a set of rectangles. The ground target recognition method consists of four steps; 3-D size and orientation estimation, target segmentation into parts of approximately rectangular shape, identification of segments that represent the target's functional/main parts, and target matching with CAD models. The core in this approach is rectangle estimation. The performance of the rectangle estimation method is evaluated statistically using Monte Carlo simulations. A case study on tank recognition is shown, where 3-D data from four fundamentally different types of laser radar systems are used. Although the approach is tested on rather few examples, we believe that the approach is promising.

  • 11.
    Grönwall, Christina
    et al.
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
    Gustafsson, Fredrik
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
    Millnert, Mille
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
    Ground Target Recognition using Rectangle Estimation2006Rapport (Övrigt vetenskapligt)
    Abstract [en]

    We propose a ground target recognition method based on 3-D laser radar data. The method handles general 3-D scattered data. It is based on the fact that man-made objects of complex shape can be decomposed to a set of rectangles. The ground target recognition method consists of four steps; 3-D size and orientation estimation, target segmentation into parts of approximately rectangular shape, identification of segments that represent the target's functional/main parts, and target matching with CAD models. The core in this approach is rectangle estimation. The performance of the rectangle estimation method is evaluated statistically using Monte Carlo simulations. A case study on tank recognition is shown, where 3-D data from four fundamentally different types of laser radar systems are used. Although the approach is tested on rather few examples, we believe that the approach is promising.

  • 12.
    Grönwall, Christina
    et al.
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
    Gustafsson, Fredrik
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
    Millnert, Mille
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
    Ground Target Recognition using Rectangle Estimation2006Ingår i: IEEE Transactions on Image Processing, ISSN 1057-7149, E-ISSN 1941-0042, Vol. 15, nr 11, s. 3400-3408Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    We propose a ground target recognition method based on 3-D laser radar data. The method handles general 3-D scattered data. It is based on the fact that man-made objects of complex shape can be decomposed to a set of rectangles. The ground target recognition method consists of four steps; 3-D size and orientation estimation, target segmentation into parts of approximately rectangular shape, identification of segments that represent the target's functional/main parts, and target matching with CAD models. The core in this approach is rectangle estimation. The performance of the rectangle estimation method is evaluated statistically using Monte Carlo simulations. A case study on tank recognition is shown, where 3-D data from four fundamentally different types of laser radar systems are used. Although the approach is tested on rather few examples, we believe that the approach is promising.

  • 13.
    Grönwall, Christina
    et al.
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska fakulteten. FOI.
    Hendeby, Gustaf
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska fakulteten.
    Kristian, Sinivaara
    Cybercom Sweden AB (Sweden).
    A proposal for combining mapping, localization and target recognition2015Ingår i: ELECTRO-OPTICAL REMOTE SENSING, PHOTONIC TECHNOLOGIES, AND APPLICATIONS IX / [ed] Gary Kamerman; Ove Steinvall; Keith L. Lewis; John D. Gonglewski, SPIE - International Society for Optical Engineering, 2015, Vol. 9649Konferensbidrag (Refereegranskat)
    Abstract [en]

    Simultaneous localization and mapping (SLAM) is a well-known positioning approach in GPS-denied environments such as urban canyons and inside buildings. Autonomous/aided target detection and recognition (ATR) is commonly used in military application to detect threats and targets in outdoor environments. This papers present approaches to combine SLAM with ATR in ways that compensate for the drawbacks in each method. The methods use physical objects that are recognizable by ATR as unambiguous features in SLAM, while SLAM provides the ATR with better position estimates. Landmarks in the form of 3D point features based on normal aligned radial features (NARF) are used in conjunction with identified objects and 3D object models that replace landmarks when possible. This leads to a more compact map representation with fewer landmarks, which partly compensates for the introduced cost of the ATR. We analyze three approaches to combine SLAM and 3D-data; point-point matching ignoring NARF features, point-point matching using the set of points that are selected by NARF feature analysis, and matching of NARF features using nearest neighbor analysis. The first two approaches are is similar to the common iterative closest point (ICP). We propose an algorithm that combines EKF-SLAM and ATR based on rectangle estimation. The intended application is to improve the positioning of a first responder moving through an indoor environment, where the map offers localization and simultaneously helps locate people, furniture and potentially dangerous objects such as gas canisters.

  • 14.
    Grönwall, Christina
    et al.
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska fakulteten.
    Karlsson, Anders
    Bjärkefur, Jon
    Test of stereo and 3D imaging cameras for SLAM applications2011Konferensbidrag (Övrigt vetenskapligt)
  • 15.
    Grönwall, Christina
    et al.
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska fakulteten.
    Olsson, Henrik
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska fakulteten.
    Optimal sensor placement in critical situations2011Konferensbidrag (Övrigt vetenskapligt)
  • 16.
    Grönwall, Christina
    et al.
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska fakulteten.
    Rydell, Joakim
    FOI.
    Jouni, Rantakokko
    FOI.
    Accurate indoor positioning of first responders2011Konferensbidrag (Övrigt vetenskapligt)
  • 17.
    Grönwall, Christina
    et al.
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska fakulteten. Swedish Def Res Agcy FOI, Div C4ISR, Linkoping, Sweden.
    Rydell, Joakim
    Swedish Def Res Agcy FOI, Div C4ISR, Linkoping, Sweden.
    Tulldahl, Michael
    Swedish Def Res Agcy FOI, Div C4ISR, Linkoping, Sweden.
    Zhang, Erik
    Saab Aeronaut, Linkoping, Sweden.
    Bissmarck, Fredrik
    Swedish Def Res Agcy FOI, Div C4ISR, Linkoping, Sweden.
    Bilock, Erika
    Swedish Def Res Agcy FOI, Div C4ISR, Linkoping, Sweden.
    Two Imaging Systems for Positioning and Navigation2017Ingår i: 2017 WORKSHOP ON RESEARCH, EDUCATION AND DEVELOPMENT OF UNMANNED AERIAL SYSTEMS (RED-UAS), IEEE , 2017, s. 120-125Konferensbidrag (Refereegranskat)
    Abstract [en]

    We present two approaches for using imaging sensors on-board small unmanned aerial systems (UAS) for positioning and navigation. Two types of sensors are used; laser scanners and a camera operating in the visual wavelengths. The laser scanners produce sparse 3D data that are registered to produce a local map. For the images from the video camera the optical flow and height estimates are fused and then matched with a geo-referenced aerial image. Both approaches include data from the inertial navigation system. The approaches can be used for accurate ego-positioning, and thus for navigation. The approaches are GPS independent and can work in GPS denied conditions, for example urban canyons, indoor environments, forest areas or while jammed. Applications are primarily within societal security and military defense.

  • 18.
    Grönwall, Christina
    et al.
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
    Steinvall, Ove
    Swedish Defence Research Agency, Sweden.
    Gustafsson, Fredrik
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
    Chevalier, Tomas
    Swedish Defence Research Agency, Sweden.
    Influence of Laser Radar Sensor Parameters on Range Measurement and Shape Fitting Uncertainties2006Rapport (Övrigt vetenskapligt)
    Abstract [en]

    Inobject/target reconstruction and recognition based on laser radar data, the range value's accuracy is important. The range data accuracy depends on the accuracy in the laser radar's detector, especially the algorithm used for time-of-flight estimation. In this paper, a general direct-detection laser radar system applicable for hard-target measurements is modeled. The time- and range-dependent laser radar cross sections are derived for some simple geometric shapes (plane, cone, sphere, and paraboloid). The cross-section models are used, in simulations, to find the proper statistical distribution of uncertainties in time-of-flight range estimations. Three time-of-flight estimation algorithms are analyzed: peak detection, constant-fraction detection, and matched filter. The detection performance for various shape conditions and signal-to-noise ratios is analyzed. Two simple shape reconstruction examples are shown, and the detectors' performance is compared with the Cramér-Raolower bound. The performance of the peak detection and the constant-fraction detection is more dependent on the shape and noise level than that of the matched filter. For line fitting the matched filter performs close to the Cramér-Rao lower bound.

  • 19.
    Grönwall, Christina
    et al.
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
    Steinvall, Ove
    Swedish Defence Research Agency, Sweden.
    Gustafsson, Fredrik
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
    Chevalier, Tomas
    Swedish Defence Research Agency, Sweden.
    Influence of Laser Radar Sensor Parameters on Range Measurement and Shape Fitting Uncertainties2007Ingår i: Optical Engineering: The Journal of SPIE, ISSN 0091-3286, E-ISSN 1560-2303, Vol. 46, nr 10Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Inobject/target reconstruction and recognition based on laser radar data, the range value's accuracy is important. The range data accuracy depends on the accuracy in the laser radar's detector, especially the algorithm used for time-of-flight estimation. In this paper, a general direct-detection laser radar system applicable for hard-target measurements is modeled. The time- and range-dependent laser radar cross sections are derived for some simple geometric shapes (plane, cone, sphere, and paraboloid). The cross-section models are used, in simulations, to find the proper statistical distribution of uncertainties in time-of-flight range estimations. Three time-of-flight estimation algorithms are analyzed: peak detection, constant-fraction detection, and matched filter. The detection performance for various shape conditions and signal-to-noise ratios is analyzed. Two simple shape reconstruction examples are shown, and the detectors' performance is compared with the Cramér-Raolower bound. The performance of the peak detection and the constant-fraction detection is more dependent on the shape and noise level than that of the matched filter. For line fitting the matched filter performs close to the Cramér-Rao lower bound.

  • 20.
    Grönwall, Christina
    et al.
    FIO.
    Tolt, Gustav
    FOI.
    Chevalier, tomas
    FOI.
    Larsson, Håkan
    FOI.
    Spatial filtering for detection of partly occluded targets2011Ingår i: Optical Engineering: The Journal of SPIE, ISSN 0091-3286, E-ISSN 1560-2303, Vol. 50, nr 4, s. 047201-1-047201-13Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    A Bayesian approach for data reduction based on spatial filtering is proposed that enables detection of targets partly occluded by natural forest. The framework aims at creating a synergy between terrain mapping and target detection. It is demonstrates how spatial features can be extracted and combined in order to detect target samples in cluttered environments. In particular, it is illustrated how a priori scene information and assumptions about targets can be translated into algorithms for feature extraction. We also analyze the coupling between features and assumptions because it gives knowledge about which features are general enough to be useful in other environments and which are tailored for a specific situation. Two types of features are identified, nontarget indicators and target indicators. The filtering approach is based on a combination of several features. A theoretical framework for combining the features into a maximum likelihood classification scheme is presented. The approach is evaluated using data collected with a laser-based 3-D sensor in various forest environments with vehicles as targets. Over 70% of the target points are detected at a false-alarm rate of <1%. We also demonstrate how selecting different feature subsets influence the results.

  • 21.
    Grönwall, Christina
    et al.
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska fakulteten.
    Tolt, Gustav
    FOI.
    Larsson, Håkan
    FOI.
    Lif, Patrik
    FOI.
    Bissmarck, Fredrik
    FOI.
    Tulldahl, Michael
    FOI.
    Wikberg, Per
    FOI.
    Thorstensson, Mirko
    FOI.
    3D sensing and imaging for UAVs: Invited paper2015Ingår i: Proceesings of SPIE, 2015, Vol. 9649Konferensbidrag (Refereegranskat)
  • 22.
    Grönwall, Christina
    et al.
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska fakulteten.
    Törnqvist, David
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska fakulteten.
    Larsson, Håkan
    FOI.
    Engström, Philip
    FOI.
    Concurrent object recognition and localization for first responder applications2013Konferensbidrag (Övrigt vetenskapligt)
  • 23.
    Grönwall, Christna
    Linköpings universitet, Institutionen för systemteknik. Linköpings universitet, Tekniska högskolan.
    Ground Object Recognition using Laser Radar Data: Geometric Fitting, Performance Analysis, and Applications2006Doktorsavhandling, sammanläggning (Övrigt vetenskapligt)
    Abstract [en]

    This thesis concerns detection and recognition of ground object using data from laser radar systems. Typical ground objects are vehicles and land mines. For these objects, the orientation and articulation are unknown. The objects are placed in natural or urban areas where the background is unstructured and complex. The performance of laser radar systems is analyzed, to achieve models of the uncertainties in laser radar data.

    A ground object recognition method is presented. It handles general, noisy 3D point cloud data. The approach is based on the fact that man-made objects on a large scale can be considered be of rectangular shape or can be decomposed to a set of rectangles. Several approaches to rectangle fitting are presented and evaluated in Monte Carlo simulations. There are error-in-variables present and thus, geometric fitting is used. The objects can have parts that are subject to articulation. A modular least squares method with outlier rejection, that can handle articulated objects, is proposed. This method falls within the iterative closest point framework. Recognition when several similar models are available is discussed.

    The recognition method is applied in a query-based multi-sensor system. The system covers the process from sensor data to the user interface, i.e., from low level image processing to high level situation analysis.

    In object detection and recognition based on laser radar data, the range value’s accuracy is important. A general direct-detection laser radar system applicable for hard-target measurements is modeled. Three time-of-flight estimation algorithms are analyzed; peak detection, constant fraction detection, and matched filter. The statistical distribution of uncertainties in time-of-flight range estimations is determined. The detection performance for various shape conditions and signal-tonoise ratios are analyzed. Those results are used to model the properties of the range estimation error. The detector’s performances are compared with the Cramér-Rao lower bound.

    The performance of a tool for synthetic generation of scanning laser radar data is evaluated. In the measurement system model, it is possible to add several design parameters, which makes it possible to test an estimation scheme under different types of system design. A parametric method, based on measurement error regression, that estimates an object’s size and orientation is described. Validations of both the measurement system model and the measurement error model, with respect to the Cramér-Rao lower bound, are presented.

    Delarbeten
    1. Ground Target Recognition using Rectangle Estimation
    Öppna denna publikation i ny flik eller fönster >>Ground Target Recognition using Rectangle Estimation
    2006 (Engelska)Ingår i: IEEE Transactions on Image Processing, ISSN 1057-7149, E-ISSN 1941-0042, Vol. 15, nr 11, s. 3400-3408Artikel i tidskrift (Refereegranskat) Published
    Abstract [en]

    We propose a ground target recognition method based on 3-D laser radar data. The method handles general 3-D scattered data. It is based on the fact that man-made objects of complex shape can be decomposed to a set of rectangles. The ground target recognition method consists of four steps; 3-D size and orientation estimation, target segmentation into parts of approximately rectangular shape, identification of segments that represent the target's functional/main parts, and target matching with CAD models. The core in this approach is rectangle estimation. The performance of the rectangle estimation method is evaluated statistically using Monte Carlo simulations. A case study on tank recognition is shown, where 3-D data from four fundamentally different types of laser radar systems are used. Although the approach is tested on rather few examples, we believe that the approach is promising.

    Ort, förlag, år, upplaga, sidor
    IEEE Signal Processing Society, 2006
    Nyckelord
    Automatic target recognition, Laser radar, Rectangle estimation
    Nationell ämneskategori
    Reglerteknik
    Identifikatorer
    urn:nbn:se:liu:diva-14120 (URN)10.1109/TIP.2006.881965 (DOI)
    Tillgänglig från: 2006-11-06 Skapad: 2006-11-06 Senast uppdaterad: 2017-12-13
    2. 3D Content-Based Model Matching using Geometric Features
    Öppna denna publikation i ny flik eller fönster >>3D Content-Based Model Matching using Geometric Features
    2006 (Engelska)Rapport (Övrigt vetenskapligt)
    Abstract [en]

    We present an approach that utilizes efficient geometric feature extraction and a matching method that takes articulation into account. It is primarily applicable for man-made objects. First the object is analyzed to extract geometric features, dimensions and rotation are estimated and typical parts, so-called functional parts, are identified. Examples of functional parts are a box's lid, a building's chimney, or a battle tank's barrel. We assume a model library with full annotation. The geometric features are matched with the model descriptors, to gain fast and early rejection of non-relevant models. After this pruning the objectis matched with relevant, usually few, library models. We propose a sequential matching, where the number of functional parts increases in each iteration. The division into parts increases the possibility for correct matching result when several similar models are available. The approach is exemplifi…ed with an vehicle recognition application, where some vehicles have functional parts.

    Ort, förlag, år, upplaga, sidor
    Linköping: Linköping University Electronic Press, 2006. s. 8
    Serie
    LiTH-ISY-R, ISSN 1400-3902 ; 2726
    Nyckelord
    Geometric features, Early rejection, Content-based matching, Least squares
    Nationell ämneskategori
    Reglerteknik
    Identifikatorer
    urn:nbn:se:liu:diva-14121 (URN)LITH-ISY-R-2726 (ISRN)
    Tillgänglig från: 2006-11-06 Skapad: 2006-11-06 Senast uppdaterad: 2016-08-31Bibliografiskt granskad
    3. Influence of Laser Radar Sensor Parameters on Range Measurement and Shape Fitting Uncertainties
    Öppna denna publikation i ny flik eller fönster >>Influence of Laser Radar Sensor Parameters on Range Measurement and Shape Fitting Uncertainties
    2007 (Engelska)Ingår i: Optical Engineering: The Journal of SPIE, ISSN 0091-3286, E-ISSN 1560-2303, Vol. 46, nr 10Artikel i tidskrift (Refereegranskat) Published
    Abstract [en]

    Inobject/target reconstruction and recognition based on laser radar data, the range value's accuracy is important. The range data accuracy depends on the accuracy in the laser radar's detector, especially the algorithm used for time-of-flight estimation. In this paper, a general direct-detection laser radar system applicable for hard-target measurements is modeled. The time- and range-dependent laser radar cross sections are derived for some simple geometric shapes (plane, cone, sphere, and paraboloid). The cross-section models are used, in simulations, to find the proper statistical distribution of uncertainties in time-of-flight range estimations. Three time-of-flight estimation algorithms are analyzed: peak detection, constant-fraction detection, and matched filter. The detection performance for various shape conditions and signal-to-noise ratios is analyzed. Two simple shape reconstruction examples are shown, and the detectors' performance is compared with the Cramér-Raolower bound. The performance of the peak detection and the constant-fraction detection is more dependent on the shape and noise level than that of the matched filter. For line fitting the matched filter performs close to the Cramér-Rao lower bound.

    Ort, förlag, år, upplaga, sidor
    SPIE - International Society for Optical Engineering, 2007
    Nyckelord
    Range error, Laser radar, Time of flight, Peak detection, Matched filter, Performance
    Nationell ämneskategori
    Reglerteknik
    Identifikatorer
    urn:nbn:se:liu:diva-14122 (URN)10.1117/1.2789654 (DOI)
    Tillgänglig från: 2006-11-06 Skapad: 2006-11-06 Senast uppdaterad: 2017-12-13
    4. Performance Analysis of Measurement Error Regression in Direct-Detection Laser Radar Imaging
    Öppna denna publikation i ny flik eller fönster >>Performance Analysis of Measurement Error Regression in Direct-Detection Laser Radar Imaging
    2003 (Engelska)Ingår i: Proceedings of the 2003 IEEE Conference on Acoustics, Speech and Signal Processing, 2003, Vol. 6, s. 545-548 vol.6Konferensbidrag, Publicerat paper (Refereegranskat)
    Abstract [en]

    In this paper a tool for synthetic generation of scanning laser radar data is described and its performance is evaluated. By analyzing data from the system, we recognize objects on the ground. In the measurement system it is possible to add several design parameters, which make it possible to test an estimation scheme under different types of system design. The measurement system model includes laser characteristics, object geometry, reflection, speckles, atmospheric attenuation, turbulence and a direct detection receiver. A parametric method that estimates an object's size and orientation is described. There are measurement errors present and thus, the parameter estimation is based on a measurement error model. The parameter estimation accuracy is limited by the Cramer-Rao lower bound. Validations of both the measurement error model and the measurement system are shown. Data from both models generate parameter estimates that are close to the Cramer-Rao lower bound.

    Nyckelord
    Atmospheric turbulence, Electromagnetic wave reflection, Measurement errors, Laser radar, Parameter estimation, Cramer-Rao lower bound
    Nationell ämneskategori
    Teknik och teknologier Reglerteknik
    Identifikatorer
    urn:nbn:se:liu:diva-14123 (URN)10.1109/ICASSP.2003.1201739 (DOI)0-7803-7663-3 (ISBN)
    Konferens
    2003 IEEE Conference on Acoustics, Speech and Signal Processing, Hong Kong, China, April, 2003
    Tillgänglig från: 2006-11-06 Skapad: 2006-11-06 Senast uppdaterad: 2016-08-31
    5. Ground Target Recognition in a Query-Based Multi-Sensor Information System
    Öppna denna publikation i ny flik eller fönster >>Ground Target Recognition in a Query-Based Multi-Sensor Information System
    Visa övriga...
    2006 (Engelska)Rapport (Övrigt vetenskapligt)
    Abstract [en]

    We present a system covering the complete process for automatic ground target recognition, from sensor data to the user interface, i.e., from low level image processing to high level situation analysis. The system is based on a query language and a query processor, and includes target detection, target recognition, data fusion, presentation and situation analysis. This paper focuses on target recognition and its interaction with the query processor. The target recognitionis executed in sensor nodes, each containing a sensor and the corresponding signal/image processing algorithms. New sensors and algorithms are easily added to the system. The processing of sensor data is performed in two steps; attribute estimation and matching. First, several attributes, like orientation and dimensions, are estimated from the (unknown but detected) targets. These estimates are used to select the models of interest in a matching step, where the targetis matched with a number of target models. Several methods and sensor data types are used in both steps, and data is fused after each step. Experiments have been performed using sensor data from laser radar, thermal and visual cameras. Promising results are reported, demonstrating the capabilities of the target recognition algorithms, the advantages of the two-level data fusion and the query-based system.

    Ort, förlag, år, upplaga, sidor
    Linköping, Sweden: Department of Electrical Engineering, 2006. s. 29
    Serie
    LiTH-ISY-R, ISSN 1400-3902 ; 2748
    Nyckelord
    Multi-sensor fusion, Query languages, Infrared sensors, Laser radar, Range data, Target recognition, Target detection
    Nationell ämneskategori
    Reglerteknik
    Identifikatorer
    urn:nbn:se:liu:diva-14124 (URN)LiTH-ISY-R-2748 (ISRN)
    Tillgänglig från: 2006-11-06 Skapad: 2006-11-06 Senast uppdaterad: 2016-08-31Bibliografiskt granskad
    6. Approaches to Object/Background Segmentation and Object Dimension Estimation
    Öppna denna publikation i ny flik eller fönster >>Approaches to Object/Background Segmentation and Object Dimension Estimation
    2006 (Engelska)Rapport (Övrigt vetenskapligt)
    Abstract [en]

    In this paper, optimization approaches for object/background segmentation and object dimension/orientation estimation are studied. The data sets are collected with a laser radar or are simulated laser radar data. Three cases are defined: 1) Segmentation of the data set into object and background data. When there are several objects present in the scene, data from each object is also separated into different clusters. Bayesian hypothesis testing of two classes is studied. 2) Estimation of the object’s dimensions and orientation using object data only. 3) Estimation of the object’s dimensions and orientation using both object and background data. The dimension and orientation estimation problem is formulated using non-convex optimization, least squares and, convex optimization expressions. The performance of the methods are investigated in simulations.

    Ort, förlag, år, upplaga, sidor
    Linköping: Linköping University Electronic Press, 2006. s. 25
    Serie
    LiTH-ISY-R, ISSN 1400-3902 ; 2746
    Nyckelord
    Segmentation, Bayes, Rectangle estimation, Least squares, Optimization
    Nationell ämneskategori
    Reglerteknik
    Identifikatorer
    urn:nbn:se:liu:diva-14125 (URN)LiTH-ISY-R-2746 (ISRN)
    Tillgänglig från: 2006-11-06 Skapad: 2006-11-06 Senast uppdaterad: 2016-08-31Bibliografiskt granskad
  • 24.
    Gustafsson, Fredrik
    et al.
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
    Grönwall, Christina
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
    A Cramer-Rao Lower Bound Expression for a Scanning Laser Radar System2002Ingår i: Proceedings of Reglermöte 2002, 2002, s. 126-129Konferensbidrag (Övrigt vetenskapligt)
  • 25.
    Henriksson, Markus
    et al.
    FOI.
    Olofsson, Tomas
    FOI.
    Grönwall, Christina
    FOI.
    Brännlund, Carl
    FOI.
    Sjöqvist, Lars
    FOI.
    Optical reflectance tomography using TCSPC laser radar2012Ingår i: Proc. SPIE, 2012, Vol. 8542Konferensbidrag (Refereegranskat)
    Abstract [en]

    Tomographic signal processing is used to transform multiple one-dimensional range profiles of a target from different angles to a two-dimensional image of the object. The range profiles are measured by a time-correlated single-photon counting (TCSPC) laser radar system with approximately 50 ps range resolution and a field of view that is wide compared to the measured objects. Measurements were performed in a lab environment with the targets mounted on a rotation stage. We show successful reconstruction of 2D-projections along the rotation axis of a boat model and removal of artefacts using a mask based on the convex hull. The independence of spatial resolution and the high sensitivity at a first glance makes this an interesting technology for very long range identification of passing objects such as high altitude UAVs and orbiting satellites but also the opposite problem of ship identification from high altitude platforms. To obtain an image with useful information measurements from a large angular sector around the object is needed, which is hard to obtain in practice. Examples of reconstructions using 90 and 150° sectors are given. In addition, the projection of the final image is along the rotation axis for the measurement and if this is not aligned with a major axis of the target the image information is limited. There are also practical problems to solve, for example that the distance from the sensor to the rotation centre needs to be known with an accuracy corresponding to the measurement resolution. The conclusion is that that laser radar tomography is useful only when the sensor is fixed and the target rotates around its own axis. © (2012) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.

  • 26.
    Horney, Tobias
    et al.
    Swedish Defence Research Agency, Sweden.
    Ahlberg, Jörgen
    Swedish Defence Research Agency, Sweden.
    Grönwall, Christina
    Swedish Defence Research Agency, Sweden.
    Folkesson, Martin
    Swedish Defence Research Agency, Sweden.
    Silvervarg, Karin
    Swedish Defence Research Agency, Sweden.
    Fransson, Jörgen
    Swedish Defence Research Agency, Sweden.
    Klasén, Lena
    Swedish Defence Research Agency, Sweden.
    Jungert, Erland
    Swedish Defence Research Agency, Sweden.
    Lantz, Fredrik
    Swedish Defence Research Agency, Sweden.
    Ulvklo, Morgan
    Swedish Defence Research Agency, Sweden.
    An information system for target recognition2004Ingår i: Volume 5434 Multisensor, Multisource Information Fusion: Architectures, Algorithms, and Applications / [ed] Belur V. Dasarathy, SPIE - International Society for Optical Engineering, 2004, s. 163-175Konferensbidrag (Refereegranskat)
    Abstract [en]

    We present an approach to a general decision support system. The aim is to cover the complete process for automatic target recognition, from sensor data to the user interface. The approach is based on a query-based information system, and include tasks like feature extraction from sensor data, data association, data fusion and situation analysis. Currently, we are working with data from laser radar, infrared cameras, and visual cameras, studying target recognition from cooperating sensors on one or several platforms. The sensors are typically airborne and at low altitude. The processing of sensor data is performed in two steps. First, several attributes are estimated from the (unknown but detected) target. The attributes include orientation, size, speed, temperature etc. These estimates are used to select the models of interest in the matching step, where the target is matched with a number of target models, returning a likelihood value for each model. Several methods and sensor data types are used in both steps. The user communicates with the system via a visual user interface, where, for instance, the user can mark an area on a map and ask for hostile vehicles in the chosen area. The user input is converted to a query in ΣQL, a query language developed for this type of applications, and an ontological system decides which algorithms should be invoked and which sensor data should be used. The output from the sensors is fused by a fusion module and answers are given back to the user. The user does not need to have any detailed technical knowledge about the sensors (or which sensors that are available), and new sensors and algorithms can easily be plugged into the system.

  • 27.
    Jon, Bjärkefur
    et al.
    Swedish Defence Research Agency (Sweden).
    Anders, Karlsson
    Swedish Defence Research Agency (Sweden).
    Grönwall, Christina
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska fakulteten. Swedish Defence Research Agency (Sweden).
    Rydell, Joakim
    Swedish Defence Research Agency (Sweden).
    Submap joining smoothing and mapping for camera-based indoor localization and mapping2011Konferensbidrag (Refereegranskat)
    Abstract [en]

    Personnel positioning is important for safety in e.g. emergency response operations. In GPS-denied environments, possible positioning solutions include systems based on radio frequency communication, inertial sensors, and cameras. Many camera-based systems create a map and localize themselves relative to that. The computational complexity of most such solutions grows rapidly with the size of the map. One way to reduce the complexity is to divide the visited region into submaps. This paper presents a novel method for merging conditionally independent submaps (generated using e.g. EKF-SLAM) by the use of smoothing. Using this approach it is possible to build large maps in close to linear time. The method is demonstrated in two indoor scenarios, where data was collected with a trolley-mounted stereo vision camera.

  • 28.
    Sjöqvist, Lars
    et al.
    FOI.
    Henriksson, Markus
    FOI.
    Grönwall, Christina
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska fakulteten.
    Jonsson, Per
    FOI.
    Olofsson, Tomas
    Steinvall, Ove
    FOI.
    High resolution TCSPC range-profiling and tomography in remote sensing applications2013Konferensbidrag (Övrigt vetenskapligt)
  • 29.
    Sjöqvist, Lars
    et al.
    Swedish Defence Research Agency (Sweden).
    Henriksson, Markus
    Swedish Defence Research Agency (Sweden).
    Grönwall, Christina
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska fakulteten. Swedish Defence Research Agency (Sweden).
    Steinvall, Ove
    Swedish Defence Research Agency (Sweden).
    High Resolution Time-Correlated Single-Photon Laser Radar for Security Applications2011Konferensbidrag (Övrigt vetenskapligt)
  • 30.
    Steinvall, Ove
    et al.
    FOI.
    Chevalier, Tomas
    FOI.
    Grönwall, Christina
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska fakulteten.
    Simulating the performance of laser imaging and range profiling of small surface vessels2013Ingår i: Proceedings of SPIE, 2013, Vol. 8731Konferensbidrag (Refereegranskat)
    Abstract [en]

    The detection and classification of small surface targets at long ranges is a growing need for naval security. This paper will discuss simulations of a laser radar at 1.5 μm aimed for search, detect and recognition of small maritime targets.

    The data for the laser radar system will be based on present and realistic future technology. The simulations will incorporate typical target movements at different sea states, vessel courses, effects of the atmosphere and for given laser system parameters also include different beam jitter. The laser pulse energy, repetition rate as well as the receiver and detector parameters have not been changed during the simulations.

    A discussion of the classification potential based on information in 1D, 2D and 3D data separately and in combination will be made vs. different environmental conditions and system parameters. System issues when combining the laser radar with IR/TV and a range-Doppler radar will also be commented.

  • 31.
    Steinvall, Ove
    et al.
    FOI.
    Chevalier, Tomas
    FOI.
    Grönwall, Christina
    FOI.
    Simulation and modeling of laser range profiling and imaging of small surface vessels2014Ingår i: Optical Engineering: The Journal of SPIE, ISSN 0091-3286, E-ISSN 1560-2303, Vol. 53, nr 1, s. 013109-1-013109-16Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    The detection and classification of small surface targets at long ranges is a growing need for naval security. Simulations of a laser radar at 1.5 μm aimed for search, detect, and recognition of small maritime targets will be discussed. The data for the laser radar system will be based on present and realistic future technology. The simulated data generate signal waveforms for every pixel in the sensor field-of-view. From these we can also generate two-dimensional (2-D) and three-dimensional (3-D) range and intensity images. The simulations will incorporate typical target movements at different sea states, vessel courses, effects of the atmospheric turbulence and also include different beam jitter. The laser pulse energy, repetition rate as well as the receiver and detector parameters have been the same during the simulations. We have also used a high resolution (sub centimeter) laser radar based on time correlated single photon counting to acquire examples of range profiles from different small model ships. The collected waveforms are compared with simulated wave forms based on 3-D models of the ships. A discussion of the classification potential based on information in 1-D, 2-D, and 3-D data separately and in combination is made versus different environmental conditions and system parameters.        

  • 32.
    Tolt, Gustav
    et al.
    FOI.
    Chevalier, Tomas
    FOI.
    Engström, Philip
    FOI.
    Grönwall, Christina
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska fakulteten.
    Applications of 3D occupancy grids in a target analysis context2012Ingår i: Proceedings of SPIE, 2012, Vol. 8379Konferensbidrag (Refereegranskat)
    Abstract [en]

    The new generation of laser-based imaging sensors enables collection of range images at video rate at the expense of somewhat low spatial and range resolution. Combining several successive range images, instead of having to analyze each image separately, is a way to improve the performance of feature extraction and target classification. In the robotics community, occupancy grids are commonly used as a framework for combining sensor readings into a representation that indicates passable (free) and non-passable (occupied) parts of the environment. In this paper we demonstrate how 3D occupancy grids can be used for outlier removal, registration quality assessment and measuring the degree of unexplored space around a target, which may improve target detection and classification. Examples using data from amaritime scene, acquired with a 3D FLASH sensor, are shown.

  • 33.
    Tolt, Gustav
    et al.
    FOI Swedish Def Res Agcy, Linkoping, Sweden.
    Grönwall, Christina
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska fakulteten. Swedish Def Res Agcy FOI, Sensor Informat Grp, Linkoping, Sweden.
    Henriksson, Markus
    FOI Swedish Def Res Agcy, Linkoping, Sweden.
    Peak detection approaches for time-correlated single-photon counting three-dimensional lidar systems2018Ingår i: Optical Engineering: The Journal of SPIE, ISSN 0091-3286, E-ISSN 1560-2303, Vol. 57, nr 3, artikel-id 031306Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Time-correlated single-photon counting lidar provides very high-resolution range measurements, making the technology interesting for 3D imaging of objects behind foliage or other obscuration. We study six peak detection approaches and compare their performance from several perspectives: detection of double surfaces within the instantaneous field of view, range accuracy, performance under sparse sampling, and the number of outliers. The results presented are based on reference measurements of a characterization target. Special consideration is given to the possibility of resolving two surfaces closely separated in range within the field of view of a single pixel. An approach based on fitting a linear combination of impulse response functions to the collected data showed the best overall performance. (c) 2018 Society of Photo-Optical Instrumentation Engineers (SPIE).

1 - 33 av 33
RefereraExporteraLänk till träfflistan
Permanent länk
Referera
Referensformat
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • oxford
  • Annat format
Fler format
Språk
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Annat språk
Fler språk
Utmatningsformat
  • html
  • text
  • asciidoc
  • rtf