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Performance Analysis of Measurement Error Regression in Direct-Detection Laser Radar Imaging
Swedish Defence Research Agency, Department of Laser Systems, Sweden.ORCID iD: 0000-0002-4434-8055
Swedish Defence Research Agency, Department of Laser Systems, Sweden.
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
2003 (English)In: Proceedings of the 2003 IEEE Conference on Acoustics, Speech and Signal Processing, 2003, Vol. 6, 545-548 vol.6 p.Conference paper, Published paper (Refereed)
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.

Place, publisher, year, edition, pages
2003. Vol. 6, 545-548 vol.6 p.
Keyword [en]
Atmospheric turbulence, Electromagnetic wave reflection, Measurement errors, Laser radar, Parameter estimation, Cramer-Rao lower bound
National Category
Engineering and Technology Control Engineering
Identifiers
URN: urn:nbn:se:liu:diva-14123DOI: 10.1109/ICASSP.2003.1201739ISBN: 0-7803-7663-3 (print)OAI: oai:DiVA.org:liu-14123DiVA: diva2:22676
Conference
2003 IEEE Conference on Acoustics, Speech and Signal Processing, Hong Kong, China, April, 2003
Available from: 2006-11-06 Created: 2006-11-06 Last updated: 2016-08-31
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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