Thorsten Schultze

UWB material characterisation and object recognition with applications in fire and security

By means of UWB radar sensors the tasks of material characterisation and object recognition are performed on the basis of a previous imaging of the whole environment. A UWB version of the microwave ellipsometry method is applied for estimating the permittivity of homogenous objects. The object recognition task is performed using bistatic sensor nodes on the basis of Radar measurements. The simulation-based performance evaluations show a very robust behavior due to suitable pre-processing of Radar data. The applications comprise the detection of fire sources, the detection of metallic object hidden under clothing and the recognition of building structures.

Performance enhancement of UWB material characterization and object recognition for security robots

By means of UWB Radar sensors the tasks of material characterisation and object recognition can be performed on the basis of a previous imaging of the whole environment. A UWB version of the microwave ellipsometry method is applied for estimating the permittivity of homogenous objects. The object recognition task is performed using bistatic sensor nodes on the basis of Radar measurements. The simulation-based performance evaluations show a very robust behavior due to suitable preprocessing of Radar data. The applications comprise the detection of fire sources, the detection of metallic object hidden under clothing, and the recognition of building structures.

Super-resolution feature extraction imaging algorithm for complex objects

For the goal of an Object Recognition (OR) Radar system, a feature extraction algorithm is proposed in this paper. Conventional radar imaging method based on Kirchhoff Migration and the revised range point migration method are known to obtain fast and accurate images. However, these methods are not suitable for feature extraction as the Kirchhoff Migration method processes the whole evolution of the Radar data and the revised range point migration method extracts the coordinates of the target contour not features. Furthermore, the new proposed feature extraction algorithm is designed for a circular scanning trajectory, or a rotating target and a bi-static antenna configuration. The proposed algorithm calculates the target points from the a priori extracted wavefronts of the Object Under Test (OUT). A Polarimetric Dynamic Correlation Method (PDCM) is employed in the proposed algorithm for the extraction of the wavefronts. Experimental validations are performed with two complex OUT, a M-sequence Radar device (4.5 GHz-13.5 GHz) and compact dual-polarized Ultra-Wideband antennas.

UWB-radar based surface permittivity estimation in hostile and pathless security scenarios

Ultra-wideband radar analysis provides a high range resolution, which is not only important for ranging, but also for the material analysis of objects. This paper introduces a novel approach for a nondestructive and in-situ estimation of material characteristics. The developed technique was inspired by the already well established optical ellipsometry and is best suited for the remote inspection of hostile indoor scenarios with robots. The paper gives an overview about the technique and its current status of research and focuses on the realisation using only few mechanical components.

Cooperative Localization and Object Recognition in Autonomous UWB Sensor Networks

Ultra-wideband (UWB) radio sensor networks promise interesting perspectives for emitter and object position localization, object identification and imaging of environments in short range scenarios. Their fundamental advantage comes from the huge bandwidth which could be up to several GHz depending on the national regulation rules. Consequently, UWB technology allows unprecedented spatial resolution in the geo-localization of active UWB radio devices and high resolution in the detection, localization and tracking of passive objects.

Robust UWB Radar object recognition

This paper focuses on an emergency situation in which a network of ultra-wide-band (UWB) sensor nodes mounted on moveable platforms is moving in a room for purposes of recognition of objects. The recognition is accomplished between 2D canonical objects, which are scanned by UWB radar and a set of reference objects with same size which were analyzed by a ray-tracing method. The object recognition task is performed on the basis of RCS (radar cross section) measurements leading to corresponding radar-gram data. Here the objects characteristic geometric features are examined by using polar Fourier descriptors which are extended in a way that also provides for multiple reflections.

A Novel Approach for Material Characterization Based on a Retroreflector Wide Band Transceiver Radar

The non-destructive material characterization is not only an interesting field for the academic research but also of importance for different applications, e.g. security applications. In this paper a novel measurement set up for low-cost 60GHZ wideband FMCW-radar is introduced. This set-up replaces the bi-static antenna configuration that is needed for reflection based permittivity estimation. This technique is an advancement of the established Microwave Ellipsometry. The developed measurement technique and setup is called microwave retroreflector ellipsometry (MRE). The experimental validation is carried out with comparison with the well established delay time measurments (DTM) technique. Hence, different dieletric surfaces are examined. Finally the advantages of the MRE compared to the DTM are discussed.

A super-resolution polarimetric wavefront extraction algorithm for UWB-radar under massive interference conditions

To provide short-range super-resolution UWB Radar under multi-scattering conditions, a superior wavefront extraction algorithm is proposed in this paper. Conventional correlation based pulse separation methods based on SAGE, CLEAN or the previously introduced superior Dynamic Correlation Method (DCM) are revised, validated and compared. In this paper the DCM is improved significantly by applying the Pauli scattering matrix decomposition onto the Radar data. This novel wavefront extraction algorithm is called polarimetric DCM (PDCM) and is suitable to resolve several overlapping pulses which consist of both strong echoes and weak echoes which are masked by the strong ones. The performance of the PDCM and the comparison with alternative algorithms is carried out by a subsequent feature extraction algorithm for visual verification. Experimental validations are performed with two complex test objects, an M-sequence Radar device (4.5 GHz-13.5 GHz) and compact dual-polarized Ultra Wideband antennas.

Hybrid Ray Tracing FDTD UWB-Model for Object Recognition

In this paper an approach for object recognition by the backscattered UWB signals is presented. This approach is a part of an UWB imaging and localization concept for emergency scenarios, where fire and smoke prevent using optical systems. The proposed recognition method is particulary useful to asses the intactness of the building construction elements. As such elements are usually composed of different materials, often including a metallic core, the recognition of inner structures is of great interest. For effective optimization and application of the recognition approach reference data sets are necessary. These reference data sets are obtained by a hybrid ray tracing/FDTD method, which allows for the simulation of small complex and inhomogenous objects in realsitc indoor scenarios. Index Terms – UWB imaging, IBST, Channel modeling, Ray tracing, FDTD

Ultra-Wideband Radar Diffraction Approximation for Dielectric Edges

In this paper, a diffraction simulation for dielectric edges is introduced. The simulation is based on geometrical theory of diffraction (GTD) and is implemented as an improvement of the millimeter-wave surface characterization. This material characterization technique has been introduced in [1] and uses the microwave ellipsometry. The subject of current investigations is the usage of autonomous security robots for the detection of hot spots, the localization and characterization of objects. These robots should support fire brigades or disaster relief teams by millimeter-wave surface characterization. The developed technique was inspired by the established optical ellipsometry. The optical characterization technique does not consider the effect diffraction at the edges of the surface. Hence, the ellipsometry is limited to large surfaces where the diffraction effects can be neglected, but for the supposed application it is necessary to compensate these effects.