Compact Radar Cross-Section Measurement Setup and Performance Evaluation

Radar cross-section measurements require the background reflections to be much lower than the reflections of the device under test. Although, anechoic chambers with special target holders meet this requirement, they are expensive and still have imperfections. To further reduce background reflections or to measure in environments where an anechoic chamber is not suitable, digital signal processing can be used to reduce background reflections. In this paper, a complete signal processing chain realized in Matlab is proposed, involving time gating of the measured target response and a background subtraction technique. Furthermore, the proposed signal processing includes a calibration procedure with either a single known calibration target or multiple known targets to improve measurement uncertainties. A compact measurement setup, consisting of a vector network analyzer and two horn antennas, is used to evaluate the overall performance and the advantages of a multiple known target calibration in a practical manner. The calibrated setup is able to measure the radar cross-section in a frequency range from 2 to 12 GHz with a mean error of less than 0.2 dB for both, VV and HH polarization combinations. It could also be shown, that a multi target calibration can result in an improvement of the measurement uncertainty by about 2.5 %.

Analysis of a Dynamic Calibration Target for Through-Wall and Through-Rubble Motion Sensing Doppler Radar

Through-wall and through-barrier motion-sensing systems are becoming increasingly important tools to locate humans concealed behind barriers and under rubble. The sensing performance of these systems is best determined with appropriately designed calibration targets, which are ones that can emulate human motion. The effectiveness of various dynamic calibration targets that emulate human respiration, heart rate, and other body motions were analyzed. Moreover, these targets should be amenable to field deployment and not manifest angular or orientation dependences. The three targets examined in this thesis possess spherical polyhedral geometries. Spherical geometries were selected due to their isotropic radar cross-sectional characteristics, which provide for consistent radar returns independent of the orientation of the radar transceiver relative to the test target. The aspect-independence of a sphere allows for more accurate and repeatable calibration of a radar than using a nonspherical calibration artifact. In addition, the radar cross section (RCS) for scattering spheres is well known and can be calculated using far-field approximations. For Doppler radar testing, it is desired to apply these calibration advantages to a dynamically expanding-and-contracting sphere-like device that can emulate motions of the human body. Monostatic RCS simulations at 3.6 GHz were documented for each geometry. The results provide a visual way of representing the effectiveness of each design as a dynamic calibration target for human detection purposes.

Conic tangents based high precision extraction method of concentric circle centers and its application in camera parameters calibration

A high-precision camera intrinsic parameters calibration method based on concentric circles was proposed. Different from Zhang’s method, its feature points are the centers of concentric circles. First, the collinearity of the projection of the center of concentric circles and the centers of two ellipses which are imaged from the concentric circles was proved. Subsequently, a straight line passing through the center of concentric circles was determined with four tangent lines of concentric circles. Finally, the projection of the center of concentric circles was extracted with the intersection of the straight line and the line determined by the two ellipse centers. Simulation and physical experiments are carried out to analyze the factors affecting the accuracy of circle center coordinate extraction and the results show that the accuracy of the proposed method is higher. On this basis, several key parameters of the calibration target design are determined through simulation experiments and then the calibration target is printed to calibrate a binocular system. The results show that the total reprojection error of the left camera is reduced by 17.66% and that of the right camera is reduced by 21.58% compared with those of Zhang’s method. Therefore, the proposed calibration method has higher accuracy.

Point Cloud Hand–Object Segmentation Using Multimodal Imaging with Thermal and Color Data for Safe Robotic Object Handover

This paper presents an application of neural networks operating on multimodal 3D data (3D point cloud, RGB, thermal) to effectively and precisely segment human hands and objects held in hand to realize a safe human–robot object handover. We discuss the problems encountered in building a multimodal sensor system, while the focus is on the calibration and alignment of a set of cameras including RGB, thermal, and NIR cameras. We propose the use of a copper–plastic chessboard calibration target with an internal active light source (near-infrared and visible light). By brief heating, the calibration target could be simultaneously and legibly captured by all cameras. Based on the multimodal dataset captured by our sensor system, PointNet, PointNet++, and RandLA-Net are utilized to verify the effectiveness of applying multimodal point cloud data for hand–object segmentation. These networks were trained on various data modes (XYZ, XYZ-T, XYZ-RGB, and XYZ-RGB-T). The experimental results show a significant improvement in the segmentation performance of XYZ-RGB-T (mean Intersection over Union: 82.8% by RandLA-Net) compared with the other three modes (77.3% by XYZ-RGB, 35.7% by XYZ-T, 35.7% by XYZ), in which it is worth mentioning that the Intersection over Union for the single class of hand achieves 92.6%.

novel method to accurately align the laser sheet for planar and stereoscopic PIV

Several techniques including two-dimensional (2D) and three-dimensional (3D) calibration are used for the calibration of two-component two-dimensional (2C-2D) particle image velocimetry (PIV) and three-component two-dimensional (3C-2D) stereoscopic PIV (SPIV) systems. A major requirement of these techniques is to keep the calibration target exactly at the position of the laser sheet within the field of view (FOV), which is very difficult to achieve (Raffel et al., 2018). In 3C-2D SPIV, several methods offer different correction schemes based on the disparity between the FOV of two stereo cameras produced due to misalignment, to account for the misalignment error. These techniques adjust the calibration or the measured displacement field in different ways to reduce the error which may introduce an unintended error in the measurement position and/or velocity such as a bias in the measured three-component 3C displacements. This paper introduces a novel method to align the laser sheet with the calibration target so that the uncertainty in displacement measurements is minimal. Ideally, it should be of the order of the uncertainty associated with PIV measurement so that no ad hoc post-correction scheme is required.

A method for estimating pedestrian critical gap using microsimulation

Estimating critical gap is crucial for modelling pedestrian level of service at crossings. Critical gap modelling becomes more challenging in signalized crossings because the proportion of pedestrians seeking gaps during red is usually unknown. Besides, the willingness – or lack of it – to cross during red signal indication varies by pedestrian and local characteristics, which makes gap acceptance modelling even more challenging. The main objective of this study is to propose a method for estimating pedestrian critical gap at signalized crossings using Vissim. The method considers that all pedestrians seek for gaps on red, and the critical gap parameter is calibrated for each pedestrian type having delay as calibration target. The results showed MAPE values of 2% and 9% for the two studied crossings. This method was compared to three existing methods of critical gap estimation. The results showed that the proposed method yielded the best estimations of delay, followed by the HCM’s.