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In classical radar imaging, such as in Earth remote sensing, electromagnetic waves are usually assumed to propagate in free space. However, in numerous applications, such as ground penetrating radar or non-destructive testing, this assumption no longer holds. When there is a multi-material background, the subsurface image reconstruction becomes considerably more complex. Imaging can be performed in the spatial domain or, equivalently, in the wavenumber domain (k-space). In subsurface imaging, to date, objects with a non-planar surface are commonly reconstructed in the spatial domain, by the Backprojection algorithm combined with ray tracing, which is computationally demanding. On the other hand, objects with a planar surface can be reconstructed more efficiently in k-space. However, many non-planar surfaces are partly planar. Therefore, in this paper, a novel concept is introduced that makes use of the efficient k-space-based reconstruction algorithms for partly planar scenarios, too. The proposed algorithm forms an image from superposing sub-images where as many image parts as possible are reconstructed in the wavenumber domain, and only as many as necessary are reconstructed in the spatial domain. For this, a segmentation scheme is developed to determine which parts of the image volume can be reconstructed in the wavenumber domain. The novel concept is verified by measurements, both from monostatic synthetic aperture radar data and multiple-input–multiple-output radar data. It is shown that the computational efficiency for imaging irregularly shaped geometries can be significantly augmented when applying the proposed concept. [ABSTRACT FROM AUTHOR]

The increasing interest in the radar detection of low-elevation and small-size targets in complicated ground environments (such as urban, suburban, and mixed country areas) calls for a precise quantification of the radar detection capabilities in those areas. Hence, a set of procedures is devised and tested, both theoretically and experimentally, using a commercial X-band radar, to (i) calibrate the radar sensor (with an online evaluation of its losses) using standard scatterers, (ii) measure the multipath effect and compensate for it, and (iii) create “true radar cross section” maps of the area of interest for both point and distributed clutter. The above methods and the related field results are aimed at future qualification procedures and practical usage of small, cheap, and easily moveable radars for the detection of low-observable air targets, such as unmanned air vehicles/systems (UAV/UAS), in difficult ground areas. A significant set of experimental results as discussed in the paper confirms the great relevance of multipath in ground-based radar detection, with the need for correcting measures. [ABSTRACT FROM AUTHOR]

A non-contact heartbeat/respiratory rate monitoring system was designed using narrow beam millimeter wave radar. Equipped with a special low sidelobe and small-sized antenna lens at the front end of the receiving and transmitting antennas in the 120 GHz band of frequency-modulated continuous-wave (FMCW) system, this sensor system realizes the narrow beam control of radar, reduces the interference caused by the reflection of other objects in the measurement background, improves the signal-to-clutter ratio (SCR) of the intermediate frequency signal (IF), and reduces the complexity of the subsequent signal processing. In order to solve the problem that the accuracy of heart rate is easy to be interfered with by respiratory harmonics, an adaptive notch filter was applied to filter respiratory harmonics. Meanwhile, the heart rate obtained by fast Fourier transform (FFT) was modified by using the ratio of adjacent elements, which helped to improve the accuracy of heart rate detection. The experimental results show that when the monitoring system is 1 m away from the human body, the probability of respiratory rate detection error within ±2 times for eight volunteers can reach 90.48%, and the detection accuracy of the heart rate can reach 90.54%. Finally, short-term heart rate measurement was realized by means of improved empirical mode decomposition and fast independent component analysis algorithm. [ABSTRACT FROM AUTHOR]

In this study, we further develop the processing of ground-based interferometric radar measurements for the application of bridge monitoring. Applying ground-based radar in such complex setups or long measurement durations requires advanced processing steps to receive accurate measurements. These steps involve removing external influences from the measurement and evaluating the measurement uncertainty during processing. External influences include disturbances caused by objects moving through the signal, static clutter from additional scatterers, and changes in atmospheric properties. After removing these influences, the line-of-sight displacement vectors, measured by multiple ground-based radars, are decomposed into three-dimensional displacement components. The advanced processing steps are applied exemplarily on measurements with two sensors at a prestressed concrete bridge near Coburg (Germany). The external influences are successfully removed, and two components of the three-dimensional displacement vector are determined. A measurement uncertainty of less than 0.1 mm is achieved for the discussed application. [ABSTRACT FROM AUTHOR]

A radar system is made of many elemental and hard/software technologies. Further, short-distance radar technology is essential for car sensors in autonomous driving systems. 10.3390/electronics8030287 23 Pan J., Hu P., Zhu Q., Bao Q., Chen Z. Feasibility Study of Passive Bistatic Radar Based on Phased Array Radar Signals. [Extracted from the article]

Full waveform inversion (FWI) can yield high resolution images and has been applied in Ground Penetrating Radar (GPR) for around 20 years. However, appropriate selection of the initial models is important in FWI because such an inversion is highly nonlinear. The conventional way to obtain the initial models for GPR FWI is ray-based tomogram inversion which suffers from several inherent shortcomings. In this paper, we develop a Laplace domain waveform inversion to obtain initial models for the time domain FWI. The gradient expression of the Laplace domain waveform inversion is deduced via the derivation of a logarithmic object function. Permittivity and conductivity are updated by using the conjugate gradient method. Using synthetic examples, we found that the value of the damping constant in the inversion cannot be too large or too small compared to the dominant frequency of the radar data. The synthetic examples demonstrate that the Laplace domain waveform inversion provide slightly better initial models for the time domain FWI than the ray-based inversion. Finally, we successfully applied the algorithm to one field data set, and the inverted results of the Laplace-based FWI show more details than that of the ray-based FWI. [ABSTRACT FROM AUTHOR]