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Influence of Laser Radar Sensor Parameters on Range Measurement and Shape Fitting Uncertainties
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.ORCID iD: 0000-0002-4434-8055
Swedish Defence Research Agency, Sweden.
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
Swedish Defence Research Agency, Sweden.
2007 (English)In: Optical Engineering: The Journal of SPIE, ISSN 0091-3286, E-ISSN 1560-2303, Vol. 46, no 10Article in journal (Refereed) 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.

Place, publisher, year, edition, pages
SPIE - International Society for Optical Engineering, 2007. Vol. 46, no 10
Keyword [en]
Range error, Laser radar, Time of flight, Peak detection, Matched filter, Performance
National Category
Control Engineering
Identifiers
URN: urn:nbn:se:liu:diva-14122DOI: 10.1117/1.2789654OAI: oai:DiVA.org:liu-14122DiVA: diva2:22675
Available from: 2006-11-06 Created: 2006-11-06 Last updated: 2017-12-13
In thesis
1. Ground Object Recognition using Laser Radar Data: Geometric Fitting, Performance Analysis, and Applications
Open this publication in new window or tab >>Ground Object Recognition using Laser Radar Data: Geometric Fitting, Performance Analysis, and Applications
2006 (English)Doctoral thesis, comprehensive summary (Other academic)
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.

Place, publisher, year, edition, pages
Institutionen för systemteknik, 2006
Series
Linköping Studies in Science and Technology. Dissertations, ISSN 0345-7524 ; 1055
Keyword
Laser radar, object detection, object recognition, performance, least squares, ICP, Cramér-Rao
National Category
Signal Processing
Identifiers
urn:nbn:se:liu:diva-7685 (URN)91-85643-53-X (ISBN)
Public defence
2006-11-17, BL32-Nobel, Campus Valla, Linköpings universitet, Linköping, 13:15 (English)
Opponent
Supervisors
Available from: 2006-11-06 Created: 2006-11-06 Last updated: 2016-08-31

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Grönwall, ChristinaGustafsson, Fredrik

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