A MIMO radar imaging system at 360 GHz is presented as a part of the comprehensive approach of the European FP7 project TeraSCREEN, using multiple frequency bands for active and passive imaging. The MIMO system consists of 16 transmitter and 16 receiver antennas within one single array. Using a bandwidth of 30 GHz, a range resolution up to 5 mm is obtained. With the 16×16 MIMO system 256 different azimuth bins can be distinguished. Mechanical beam steering is used to measure 130 different elevation angles where the angular resolution is obtained by a focusing elliptical mirror. With this system a high resolution 3D image can be generated with 4 frames per second, each containing 16 million points. The principle of the system is presented starting from the functional structure, covering the hardware design and including the digital image generation. This is supported by simulated data and discussed using experimental results from a preliminary 90 GHz system underlining the feasibility of the approach.
This paper presents a rotating W band radar performing a full body scan of persons which are moving with constant
speed below the radar. The radar consists of a FMCW module sweeping the frequency between 96 GHz and 99 GHz by a
varactor tuned VCO. The transmit and receive modules are fabricated in split-block technology using 100 nm
metamorphic HEMT MMICs. The used 4 channel receiver operates between 84 GHz and 104 GHz and an average noise
figure of 3.5 dB. Polarimetric measurements are carried out for the detection of oblong objects such as explosive tubes.
Measuring many people within a short time is still a great challenge to scanners in security related areas, e.g. airports or
stations. A new approach for fast and high resolution scanning is presented, based on the so called "circular synthetic
aperture radar" (CSAR), applied to a walkway. Due to the circular movement, each of the receiving antennas creates a
circular synthetic aperture itself. By reconstructing the complex valued SAR-images for each receiver channel, the
ability to perform interferometric SAR-Analysis of a tested person is given. The screened persons do not have to stand
still, thus, a measurement in a passenger flow is possible.
This paper gives an overview about a new security concept on airports. Because single systems have not often the
desired reliability, the concept is based on the fusion of different sensors. Moreover, first measurements of a 94 GHz
person scanner with circular synthetic aperture are presented showing the capability to detect metallic as well as nonmetallic
objects without violating the personal privacy.
KEYWORDS: 3D modeling, 3D acquisition, 3D image processing, Infrared imaging, 3D image reconstruction, Clouds, Navigation systems, LIDAR, Sensors, Cameras
The successful mission of an autonomous airborne system like an unmanned aerial vehicle (UAV) strongly depends on an accurate target approach as well as the real time acquisition of detailed knowledge about the target area. An automatic 3D scene reconstruction of the overflown ground by a structure from motion system enables to interpret the scenario and to react on possible changes by optimization of flight path or adjustment of mission objectives. Additionally, detection of the target itself can be improved due to the analysis of the reconstructed 3D target scenario.
In this work a newly developed system for automatic 3D reconstruction of a scene from aerial infrared imagery is presented. For more accuracy in the reconstruction and to overcome the drawbacks of feature tracking in IR images, pose information given by an IMU (Inertial Measurement Unit) are used for computation of 3D structure. Detected 2D image features are tracked image by image to calculate corresponding 3D information. Each estimated 3D point is assessed by means of its covariance matrix which is associated with the respective uncertainty. Finally a non-linear optimization (Gauss-Newton iteration) of the reconstruction result yields the completed 3D point cloud. As possible applications, approaches for target recognition in fused IR images and 3D point clouds as well as registration of point clouds for image based navigation update are presented.
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