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Ground Target Recognition in a Query-Based Multi-Sensor Information System
Swedish Defence Research Agency, Sweden.ORCID iD: 0000-0002-6763-5487
Swedish Defence Research Agency, Sweden.
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.
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2006 (English)Report (Other academic)
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.

Place, publisher, year, edition, pages
Linköping, Sweden: Department of Electrical Engineering , 2006. , 29 p.
LiTH-ISY-R, ISSN 1400-3902 ; 2748
Keyword [en]
Multi-sensor fusion, Query languages, Infrared sensors, Laser radar, Range data, Target recognition, Target detection
National Category
Control Engineering
URN: urn:nbn:se:liu:diva-14124ISRN: LiTH-ISY-R-2748OAI: diva2:22677
Available from: 2006-11-06 Created: 2006-11-06 Last updated: 2016-08-31Bibliographically approved
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
Linköping Studies in Science and Technology. Dissertations, ISSN 0345-7524 ; 1055
Laser radar, object detection, object recognition, performance, least squares, ICP, Cramér-Rao
National Category
Signal Processing
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)
Available from: 2006-11-06 Created: 2006-11-06 Last updated: 2016-08-31

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