In this paper, a super-compact ultra-wideband (UWB) metamaterial absorber (MMA) is presented. The absorber design consists of an inverted L-shaped structure and a diagonal rectangular-shaped structure. The capacitive coupling between these two structures not only provides UWB nature but also provides a super-compact absorber design. The dimension of the unit cell arrangement is 5 × 5 mm2 and printed on a low-cost FR-4 substrate of thickness 1.54 mm (0.061λlowest). The design absorber provides more than 97% absorptivity from 12 to 21 GHz for normal incidence electromagnetic (EM) wave. However, the proposed MMA has a full width at half maximum absorption bandwidth of 11.71 GHz from 10.34 to 22.05 GHz. Moreover, the surface current distributions have been analyzed to understand the absorption mechanism of the MMA. The stability of the proposed design is validated with different incident angles (for TE and TM modes) and different polarization angles. Finally, the absorber design is fabricated and verified experimentally. Furthermore, the UWB frequency range, high absorption, ease in design and fabrication, and cost-effective make it suitable for different quality applications in stealth technology, thermal imaging, radar detection, antenna systems, and other EM devices.

Sentinel-1A is a space-borne synthetic aperture radar (SAR) system developed in the frame of the Copernicus Program. The German Aerospace Center supported the radiometric and polarimetric calibration of Sentinel-1A by the analysis of point target responses of several acquisitions considering different modes, beams, and polarization channels. An elevation dependent bias, which had not been properly predicted by the used antenna model, was found for all investigated modes. Offsets of up to 2 dB were determined during the SAR instrument calibration phase, in particular, for low and high elevation angles. Therefore, in order to correct these elevation biases, a radiometric refinement was carried out by European Space Agency in November 2015. After that, Sentinel-1A radiometric accuracy and long-term stability were analyzed over a period of 1.5 years. For this period, the absolute calibration factor and the channel imbalance were determined for the main imaging mode. Moreover, a slight drift of the derived calibration factor was observed starting from July 2016. At the same time an anomaly was detected in the front-end affecting several transmit and receive modules in one tile. The radiometric behavior of Sentinel-1A should therefore be monitored for a longer period of time, especially to detect potential degradation effects of the SAR instrument.

Jamming of synthetic aperture radar (SAR) is more difficult than the conventional radars because of its high processing gain. The defocusing of fake or virtual scatterers is the main problem that any jamming technique needs to tackle. An algorithm based on fractional Fourier transform is proposed for the efficient jamming of SAR. The results show that the performance of proposed algorithm is better than conventional Range Doppler Algorithm.

In this contribution, fractal antenna arrays are analyzed for their applicability in multiple-input multiple-output (MIMO) radars. Array geometries based on the Fudgeflake fractal and the Gosper island fractal are investigated. In addition, a concept for the combination of both fractals is shown in order to increase the flexibility concerning the number of transmitting and receiving antennas. The presented fractal MIMO concepts can be utilized in order to improve the angular resolution and to reduce the sidelobe level for a given number of transmitting and receiving antennas. It is shown that a fractal MIMO concept with 21 transmitting antennas and 21 receiving antennas improves the angular resolution to 4.6 degrees and reduces side lobe level by 3.1 dB compared to a MIMO configuration based on two linear arrays with the same number of antenna elements. In addition, the results are experimentally validated by broadband radar measurements.

Air target recognition is a critical step in the radar processing chain and reliable features are necessary to make a decision. The number and position of jet engines are useful features to perform a pre-classification and give a list of possible targets. To extract these features, a sparse decomposition framework for inverse synthetic aperture radar (ISAR) images is presented. With this framework different components of the target can be detected, if signal models for these parts are available. To use it for the detection of jet engines, a review of a signal model for air intakes, which was developed by Borden, is given. This model is based on the common assumption that the propagation of electromagnetic waves inside jet engines has the same dispersive behavior as inside waveguides. With this model a decomposition of a real ISAR image, measured with the tracking and imaging radar system of Fraunhofer FHR, into point-like scattering centers and jet engines is presented.

Confocal microwave imaging for breast cancer detection relies on accurate knowledge of the average dielectric properties of the patient-specific breast. When accurately estimated, coherent addition will occur at the tumor site, producing a clear and sharp image thereof. Conversely, if the average dielectric properties are poorly estimated, a blurred, unfocused image will be reconstructed, potentially obscuring cancerous lesions. Several methods have been proposed to estimate the patient-specific average dielectric properties, for example, time-of-flight estimation. However, such methods are specific to the individual imaging hardware, can be susceptible to multipath propagation and assume the chosen paths are representative of the whole volume. In this paper, a novel method to estimate the patient-specific average dielectric properties is presented, based on focal quality metrics (FQMs); used historically to measure the clarity and focus of microscopic or digital photographic images. These FQMs are applied to confocal microwave breast images to assess their focus, and hence estimate the patient-specific average dielectric properties. In this way, FQMs can be used to generate the optimum microwave image of the breast. The performance and robustness of these FQMs for microwave breast imaging applications is examined in this paper and preliminary results are presented and discussed.

In this paper, we propose an effective waveform diversity scheme that can be applicable to synthetic aperture radar (SAR) operations affected by interfering signals. A novel approach is taken to achieve fully adaptive SAR waveform diversity that generates sufficient number of orthogonal signals with modest performance trade-off. To this purpose, multiple phased-code waveforms are arbitrarily generated with mutually low cross-correlations. They exhibit a highly flexible characteristic as their code lengths are not limited and Doppler tolerance is well preserved throughout SAR imaging. Various SAR jamming simulations are carried out to demonstrate that the proposed waveform diversity has a good potential for electronic counter-countermeasures applications.

In order to counter active jamming, an adaptive polarization cancellation method based on dual-polarization radar is proposed in the paper. First, respectively being obtained by vertical and horizontal polarization channels of dual-polarization radar, the signals from the real target and active jamming are analyzed in composition and characteristic. Then, the weight coefficient is timely derived in practical scene to adjust difference of amplitude and phase of active jamming signals respectively acquired by the two orthogonal polarization channels, so the method can completely eliminate active jamming, but just a little power change for the real target signal. Furthermore, a compensating method for the target signal is developed to improve the angle measuring accuracy of monopulse radars. And the influence factors of adaptive polarization cancellation are analyzed in detail by simulation. Finally, the experimental results prove that it is very effective on both active blanket jamming and active deception jamming.

A 4–8 GHz ultra wide band microstrip array antennas with improved gain for weather Radar applications was designed and fabricated. The microstrip radiating elements of the proposed array antennas are powered using a T-junction power divider with quarter wave-transformer impedance for a best matching. The design of this array antennas is based on the geometry of a linear array antennas well studied [ref (8)], which is based on minimizing of the electromagnetic (EM) coupling between the radiating elements and as decreasing the number of side lobes. The array antennas with dimension of (110 × 214 × 1.58 mm3) is fabricated on FR-4 epoxy dielectric with relative permittivity of 4.4 and thickness h = 1.58 mm, it is performed in the full-wave EM solver High Frequency Structure Simulator, CST and verified by measurement. The proposed broadband array antennas show a better performance than the references antennas in deferent parameter which cited after.

A new model is proposed on how to account for the inertia of scatterers in radar-based turbulence intensity retrieval techniques. Rain drop inertial parameters are derived from fundamental physical laws, which are gravity, the buoyancy force, and the drag force. The inertial distance is introduced, which is a typical distance at which a particle obtains the same wind velocity as its surroundings throughout its trajectory. For the measurement of turbulence intensity, either the Doppler spectral width or the variance of Doppler mean velocities is used. The relative scales of the inertial distance and the radar resolution volume determine whether the variance of velocities is increased or decreased for the same turbulence intensity. A decrease can be attributed to the effect that inertial particles are less responsive to the variations of wind velocities. An increase can be attributed to inertial particles that have wind velocities corresponding to an average of wind velocities over their backward trajectories, which extend outside the radar resolution volume. Simulations are done for the calculation of measured radar velocity variance, given a 3-D homogeneous isotropic turbulence field, which provides valuable insight in the correct tuning of parameters for the new model.

The backscatter from radar object carries Doppler information of scatterers on the object determined by the radial velocity of scattering points and the radar transmitted frequency. For a rotating object this information is contained in the frequency characteristics over varying aspect angle. Frequency characteristics are used to create projections for Doppler radar tomographic imaging. This paper presents a method for high resolution imaging of a rotating target using a time-frequency transform of a returned signal as tomographic projections. The resolution of a tomographic image depends not only on radar system parameters but also depends on the resolution of input projections. The reassigned spectrogram is proposed for building of tomographic projections, due to its possibility of squeezing of frequency spread. The reassigned spectrogram is sensitive to noise so the denoising procedure in the time-frequency domain must be performed before the reassignment procedure. The denoising is performed by removing Short Time Fourier Transform (STFT) noise coefficients below the appropriate threshold. The STFT is a linear time-frequency transform and coefficients, which belong to the signal and coefficients which belong to noise can be analyzed separately. The efficiency of the proposed idea of imaging is supported by results of numerical experiments.

Recent works have demonstrated the feasibility of microwave imaging using compressive techniques, exempting the use of active delay lines, phase shifters, or moving parts to achieve beamforming. With this method, waves are coded in a passive way by a compressive device to reduce the complexity of the transmitter and/or receiver chains of the telecommunication and radar systems requiring beamsteering. Such a technique is based on the exploitation of the frequency diversity, implying that a reduction of the compressive device's volume imposes a diminution of the number of driven antennas. In this paper, the improvement brought by simultaneous excitations of the compressive device is presented. Adapting a new mathematical formulation, it is shown that M inputs can send independent waveforms allowing the beamsteering of an N-elements antenna array, while maintaining N > M.

High-resolution imaging with an airborne synthetic aperture radar (SAR) calls for precise trajectory measurements that can hardly be achieved with common navigation systems. In this paper, an efficient method called the local-quadratic map-drift autofocus is developed for the estimation of residual (uncompensated) motion errors directly from the received radar data. The map-drift autofocus is applied locally on short time intervals to estimate the cross-track components of the aircraft acceleration. The estimated acceleration is then integrated to evaluate the residual trajectory errors on the whole data frame interval. The method has been successfully tested with an X-band airborne SAR system.

Active electronically scanned array (AESA) radar has large number of transmit/Receive (T/R) modules which require multiple microwave and digital signals. Distribution of these signals through conventional method such as coaxial cable, twisted pair, etc. not only introduces engineering complexities and signal loss but also have limitation of bandwidth, data rate, transmission distance, etc. This paper addresses design and implementation of microwave photonic network for distribution of microwave and digital signals over single optical fiber using wavelength division multiplexing for AESA radars. The design challenge is to limit the variation in output radio frequency power within ±1 dB over full operational band of radar from 2 to 4 GHz and functionality under hostile military environment. Optical amplifiers have been used in all channels to stabilize optical output independent of wavelength with automatic light control. The optical signal is split into 64 identical parts to feed multiplexed signal into different digital receivers physically spread across the antenna array. It is an additional challenge to normalize performance as all 64 receivers show variation in output in spite of identical electronic circuitry. Experimental results validate the feasibility of microwave photonic network for wide branching distribution of multiple microwave and digital signals for AESA radar.

This paper presents a position gauging system of welding joints. While the principle measurement concept was already introduced by Schrattenecker et al. in 2014, here it is focused on different types of practically used welding materials. The sensor used is based on the frequency-modulated continuous-wave principle operating in the W-band. Position estimation (PoE) of different welding geometries is carried out with polarimetric scattering effects introduced by geometrical discontinuities. For the real-time calculation of the signal models a field simulation tool we developed is used. Aside from a variety of geometries, we introduce a geometrical optimization approach that increases the achievable accuracy of the measurement concept. The optimization and PoE of the different welding materials were examined in various simulations and the results were verified by measurements in the laboratory and in an industrial environment. Simulation and measurement were in good agreement.

Null steering has been a challenge in radar communications for the past few decades. In this paper, a novel cognitive null steering technique in frequency diverse array radars using frequency offset selection is presented. The proposed system is a complete implementable framework that provides precise and deep null placement in the range and angle locations of the interference source. The proposed system is cognitive such that the transmitter and receiver are connected via a feedback loop. System extracts interference source location parameters from the radar scene using Multiple Signal Classification, a super resolution direction of arrival estimation technique. Neural networks known for minimum computation time, and good non-linear and non-parametric approximation have been utilized for prediction of next location of the interference source. Simulation results validate the proposed frequency offset selection by demonstrating precise and deep nulls at the desired locations.

To provide short-range super-resolution ultra-wideband (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 dynamic correlation method (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, a maximum length sequence radar device (4.5–13.5 GHz) and compact dual-polarized UWB antennas.

The radar micro-Doppler signature of a target is determined by parts of the target moving or rotating in addition to the main body motion. The relative motion of these parts is characteristic for different classes of targets, e.g. the flapping motion of a bird's wings versus the spinning of propeller blades. In the present study, the micro-Doppler signature is exploited to discriminate birds and small unmanned aerial vehicles (UAVs). Emphasis is on micro-Doppler features that can be extracted from spectrograms and cepstrograms, enabling the human eye or indeed automatic classification algorithms to make a quick distinction between man-made objects and bio-life. In addition, in case of man-made objects, it is desired to further characterize the type of mini-UAV to aid the threat assessment. Also this characterization is done on the basis of micro-Doppler features.

The paper is devoted to coherent radiometric imaging systems. The investigated systems may be considered as a version of bistatic noise waveform passive radar with synthetic aperture having external reference. Reference signal in this imaging system is received from the investigated emitting object using auxiliary receiver. Although a number of theoretical studies on aperture synthesis imaging algorithms exist, relatively few of them deal with experimental investigation. In particular, no information concerning range-azimuth coherent radiometric imaging has been found. In this paper, an experimental investigation of possibility to generate coherent radiometric images using two antennas with beam synthesizing is carried out. Indoor radiometric imaging has been validated using absorbers as the emitting objects. These experiments enabled to estimate range resolution of the radiometric system achieved by focusing antennas with beam synthesizing for range span limited by means about bistatic baseline.

Pedestrian Collision Mitigation Systems (PCMS) are already in the market for some years. Due to continuously evolving EuroNCAP regulations their presence will increase. Visual sensors, already capable of pedestrian classification, provide functional benefits, because the reaction behavior can be optimized when the imminent collision object is recognized as pedestrian or cyclist. Nevertheless their performance will suffer under adverse environmental conditions like darkness, fog, rain or backlight. Even in such unfavorable situations the performance of radar sensors is not significantly deteriorated. Enabling classification capability to automotive radar will further improve road safety and will lower PCMS's overall costs. In this paper, a multi-reflection-point pedestrian target model based on motion analysis is presented. Together with an appropriate sensor model, pedestrian radar signal responses can be provided for a wide range of accident scenarios. Additionally velocity separation requirements that are needed for classification of pedestrians are derived from the simulations. Besides determination of classification features, the model discloses the limits of classical radar signal processing and further offers the opportunity to evaluate parametric spectral analysis. Based on simulated and measured baseband radar signals of pedestrians one of these techniques is deeper analyzed and its enhancement especially on the velocity separation capability is evaluated.