Radar-absorbent materials (RAM) with various characteristics, such as broadband, oblique-incidence, and polarization characteristics, have been developed according to applications in recent years. This paper presents the optimized design method of two flat layers RAM with both broadband and oblique-incidence characteristics for the required RAM performance. The oblique-incidence characteristics mean that the RAM is possible to absorb radio waves continuously up to the maximum incidence angle. The index of the wave-absorption amount is 20dB, corresponding to an absorption rate of 99%. Because determination of the electrical material constant of each layer is the most important task with respect to the received frequency and the incidence angle, we optimized the values by using Non-dominated sorting genetic algorithm-II (NSGA-II). Two types of flat-layer RAM composed of dielectric and magnetic materials were designed and their characteristics were evaluated. Consequently, it was confirmed that oblique-incidence characteristics were better for the RAM composed of dielectric materials. The dielectric RAM achieved an incidence angle of up to 60° with broadband characteristics and a relative bandwidth of 77.01% at the transverse-magnetic (TM) wave incidence. In addition, the magnetic RAM could lower the minimum frequency of the system more than the dielectric RAM. The minimum frequency of the magnetic RAM was 1.38GHz with a relative bandwidth of 174.18% at TM-wave incidence and an incidence angle of 45°. We confirmed that it is possible to design RAM with broadband characteristics and continuous oblique-incidence characteristics by using the proposed method.

A 19.1-to-20.4 GHz sigma-delta fractional-N frequency synthesizer with two-point modulation (TPM) for frequency modulated continuous wave (FMCW) radar applications is presented. The FMCW synthesizer proposes a digital and voltage controlled oscillator (D/VCO) with large continuous frequency tuning range and small digital controlled oscillator (DCO) gain variation to support TPM. By using TPM technique, it avoids the correlation between loop bandwidth and chirp slope, which is beneficial to fast chirp, phase noise and linearity. The start frequency, bandwidth and slope of the FMCW signal are all reconfigurable independently. The FMCW synthesizer achieves a measured phase noise of -93.32 dBc/Hz at 1MHz offset from a 19.25 GHz carrier and less than 10 µs locking time. The root-mean-square (RMS) frequency error is only 112 kHz with 94 kHz/µs chirp slope, and 761 kHz with a fast slope of 9.725 MHz/µs respectively. Implemented in 65 nm CMOS process, the synthesizer consumes 74.3 mW with output buffer.

In this paper, we propose a simple algorithm for detecting a vehicle trapped in flooded urban area by using quad-polarimetric SAR data. The four-component scattering power decomposition and phase difference of HH-VV co-pol ratio are effectively used in the proposed algorithm. Here we carry out polarimetric scattering measurement for a scaled vehicle model surrounded by two buildings model in an anechoic chamber, to acquire the quad-polarimetric SAR data. It is confirmed from the results of the image analysis for the measured SAR data that the proposed algorithm for vehicle detection works well even under severe environment where the vehicle is set in the shadow of the building and/or the alignment of the vehicle or the buildings is obliquely oriented to direction of the radar line of sight.

In stepped FM radar, the transmitter intermittently transmits narrowband pulse trains of frequencies that are incremented in steps, and the receiver performs phase detection on each pulse and applies the inverse discrete Fourier transform (IDFT) to create ultra-short pulses in the time domain. Furthermore, since the transmitted signal consists of a narrowband pulse train of different frequencies, the transmitter can avoid arbitrary frequency bands while sending the pulse train (spectrum holes), allowing these systems to coexist with other narrowband wireless systems. However, spectrum holes cause degradation in the distance resolution and range sidelobe characteristics of wireless systems. In this paper, we propose a spectrum hole compensation method for stepped FM radars using Khatri-Rao product extended-phase processing to overcome the problem of spectrum holes and investigate the effectiveness of this method through experiments. Additionally, we demonstrate that the proposed method dramatically improves the range sidelobe and distance resolution characteristics.

We propose waveguide to microstrip line transitions for automotive millimeter wave radar modules. The transitions perpendicularly connect one waveguide and one or two microstrip lines. The configuration is simple because it consists of a waveguide and a dielectric substrate with copper foils. Additionally the transitions do not need via holes on the substrate. It leads to lower costs and improved reliability. We have already proposed a via-less transition by using multi-stage impedance transformers. The impedance transformers are used for suppressing undesirable radiation from the transition as well as impedance matching. In this paper, we propose a new transition with the microstrip lines on the long axis of the waveguide while most transitions place the microstrip lines on the minor axis (electric field direction) of the waveguide. Though our transition uses bend structures of microstrip lines, which basically cause radiation, our optimized configuration can keep small radiation. We also design a transition with a single microstrip line. The proposed transition with 2 microstrip lines can be modified to the 1 microstrip line version with minimum radiation loss. Electromagnetic simulations confirm the small radiation levels expected. Additionally we fabricate the transitions with back to back structure and determine the transmission and radiation performance. We also fabricates the transition for a patch array antenna. We confirm that the undesirable radiation from the proposed transition is small and the radiation pattern of the array antenna is not worsen by the transition.

Nyquist folding receiver (NYFR) is a novel reconnaissance receiving architecture and it can realize wideband receiving with small amount of equipment. As a tradeoff of non-cooperative wideband receiving, the NYFR output will add an unknown key parameter that is called Nyquist zone (NZ) index. In this letter, we concentrate on the NZ index estimation of the NYFR output. Focusing on the basic pulse radar signals, the constant frequency signal, the binary phase coded signal and the linear frequency modulation signal are considered. The matching component function is proposed to estimate the NZ indexes of the NYFR outputs without the prior information of the signal modulation type. In addition, the relations between the matching component function and the parameters of the NYFR are discussed. Simulation results demonstrate the efficacy of the proposed method.

To improve detection performance for a reconnaissance receiver, which is designed to detect the non-cooperative MIMO-LFM radar signal under low SNR condition, this letter proposed a novel signal detection method. This method is based on Fractional Fourier Transform with entropy weight (FRFTE) and autocorrelation algorithm. In addition, the flow chart and feasibility of the proposed algorithm are analyzed. Finally, applying our method to Wigner Hough Transform (WHT), we demonstrate the superiority of this method by simulation results.

This letter proposes a track before detect scheme embedded in coherent repeated interference with the aid of frequency diversity array. The unmatched properties between echo and interferences are firstly discussed from both signal processing and data processing standpoints. Afterward, the interference suppression algorithm with virtual channel weighting at continue sampling stage is proposed, followed with kinematics constraint correspondingly. Further, the evaluations of the interference suppression performance are carried out through simulations which illustrate the feasibility and validity of the proposed algorithm.

In order to obtain road information, we propose an information acquisition method using infrared laser radar by detecting 3D reflector code on roadside. The infrared laser radar on vehicle scans the 3D reflector code on guardrail. Through experiments, we show that the proposed method is able to obtain road information by detecting 3D reflector code on guardrail.

In small-aperture high frequency surface wave radar, the main-lobe clutter all can be seen as a more severe space spread clutter under the influence of the smaller array aperture. It compromises the detection performance of moving vessels, especially when the target is submerged in the clutter. To tackle this issue, an improved spread clutter estimated canceller, combining spread clutter estimated canceller, adaptive selection strategy of the optimal training samples and rotating spatial beam method, is presented to suppress main-lobe clutter in both angle domain and range domain. According to the experimental results, the proposed algorithm is shown to have far superior clutter suppression performance based on the real data.

A triangular decomposition-based multipath super-resolution method is proposed to improve the range resolution of small unmanned aerial vehicle (UAV) radar altimeters that use a single channel with continuous direct spread waveform. In the engineering applications of small UAV radar altimeter, multipath scenarios are quite common. When the conventional matched filtering process is used under these environments, it is difficult to identify multiple targets in the same range cell due to the overlap between echoes. To improve the performance, we decompose the overlapped peaks yielded by matched filtering into a series of basic triangular waveforms to identify various targets with different time-shifted correlations of the pseudo-noise (PN) sequence. Shifting the time scale enables targets in the same range resolution unit to be identified. Both theoretical analysis and experiments show that the range resolution can be improved significantly, as it outperforms traditional matched filtering processes.

Real-time weather radar imaging technology is required for generating short-time weather forecasts. Moreover, such technology plays an important role in critical-weather warning systems that are based on vast Doppler weather radar data. In this study, we propose a weather radar imaging method that uses multi-layer contour detection and segmentation based on MAP-MRF estimation. The proposed method consists of three major steps. The first step involves generating reflectivity and velocity data using the Doppler radar in the form of raw data images of sweep unit in the polar coordinate system. Then, contour lines are detected on multi-layers using the adaptive median filter and modified Canny's detector based on curvature consistency. The second step interpolates contours on the Cartesian coordinate system using 3D scattered data interpolation and then segments the contours based on MAP-MRF prediction and the metropolis algorithm for each layer. The final step involves integrating the segmented contour layers and generating PPI images in sweep units. Experimental results show that the proposed method produces a visually improved PPI image in 45% of the time as compared to that for conventional methods.

The fifth generation (5G) system using millimeter waves is considered for application to high traffic areas with a dense population of pedestrians. In such an environment, the effects of shadowing and scattering of radio waves by human bodies (HBs) on propagation channels cannot be ignored. In this paper, we clarify based on measurement the characteristics of waves scattered by the HB for typical non-line-of-sight scenarios in street canyon environments. In these scenarios, there are street intersections with pedestrians, and the angles that are formed by the transmission point, HB, and reception point are nearly equal to 90 degrees. We use a wide-band channel sounder for the 67-GHz band with a 1-GHz bandwidth and horn antennas in the measurements. The distance parameter between antennas and the HB is changed in the measurements. Moreover, the direction of the HB is changed from 0 to 360 degrees. The evaluation results show that the radar cross section (RCS) of the HB fluctuates randomly over the range of approximately 20dB. Moreover, the distribution of the RCS of the HB is a Gaussian distribution with a mean value of -9.4dBsm and the standard deviation of 4.2dBsm.

There is a strong demand for super-resolution time of arrival (TOA) estimation techniques for radar applications that can that can exceed the theoretical limits on range resolution set by frequency bandwidth. One of the most promising solutions is the use of compressed sensing (CS) algorithms, which assume only the sparseness of the target distribution but can achieve super-resolution. To preserve the reconstruction accuracy of CS under highly correlated and noisy conditions, we introduce a random resampling approach to process the received signal and thus reduce the coherent index, where the frequency-domain-based CS algorithm is used as noise reduction preprocessing. Numerical simulations demonstrate that our proposed method can achieve super-resolution TOA estimation performance not possible with conventional CS methods.

This paper proposes multiple-input multiple-output (MIMO) radar waveforms consisting of Doppler-offset orthogonal complementary codes (DO-OCC) for raising the Doppler resilience of MIMO radar systems. The DO-OCC waveforms have low cross-correlation among multiplexed waves and a low autocorrelation peak sidelobe level (PSL) even in the Doppler shift condition. They are verified by computer simulations and measurements. Computer simulations show that the peak sidelobe ratio (PSR) of the DO-OCC exceeds over 60dB and the desired to undesired signal power ratio (DUR) is over 60dB in the case that the Doppler shift is 0.048 rad per pulse repetition interval (PRI). And through the experimental measurements, it has been verified that the PSR of the DO-OCC is over 40dB and the DUR is over 50dB in the case that Doppler shift is 0.05 rad per PRI and that The DO-OCC waveforms enable to maintain the direction of arrival (DOA) estimation accuracy for moving targets as almost same as the one for static targets. The results prove the effectiveness of the proposed MIMO waveforms in achieving Doppler tolerance while maintaining orthogonality and autocorrelation properties.

The issue of robust multi-input multi-output (MIMO) radar waveform design is investigated in the presence of imperfect clutter prior knowledge to improve the worst-case detection performance of space-time adaptive processing (STAP). Robust design is needed because waveform design is often sensitive to uncertainties in the initial parameter estimates. Following the min-max approach, a robust waveform covariance matrix (WCM) design is formulated in this work with the criterion of maximization of the worst-case output signal-interference-noise-ratio (SINR) under the constraint of the initial parameter estimation errors to ease this sensitivity systematically and thus improve the robustness of the detection performance to the uncertainties in the initial parameter estimates. To tackle the resultant complicated and nonlinear robust waveform optimization issue, a new diagonal loading (DL) based iterative approach is developed, in which the inner and outer optimization problems can be relaxed to convex problems by using DL method, and hence both of them can be solved very effectively. As compared to the non-robust method and uncorrelated waveforms, numerical simulations show that the proposed method can improve the robustness of the detection performance of STAP.

Radar is expected in advanced driver-assistance systems for environmentally robust measurements. In this paper, we propose a novel radar signal segmentation method by using a complex-valued fully convolutional network (CvFCN) that comprises complex-valued layers, real-valued layers, and a bidirectional conversion layer between them. We also propose an efficient automatic annotation system for dataset generation. We apply the CvFCN to two-dimensional (2D) complex-valued radar signal maps (r-maps) that comprise angle and distance axes. An r-maps is a 2D complex-valued matrix that is generated from raw radar signals by 2D Fourier transformation. We annotate the r-maps automatically using LiDAR measurements. In our experiment, we semantically segment r-map signals into pedestrian and background regions, achieving accuracy of 99.7% for the background and 96.2% for pedestrians.

The existing methods to estimate satellite attitude by using radar cross section (RCS) sequence suffer from problems such as low precision, computation complexity, etc. To overcome these problems, a novel model of satellite attitude estimation by the local maximum points of the RCS sequence is established and can reduce the computational time by downscaling the dimension of the feature vector. Moreover, a particle swarm optimization method is adopted to improve efficiency of computation. Numerical simulations show that the proposed method is robust and efficient.

In this paper, we propose an automotive radar sensor compensation method improving direction of arrival (DOA) and preventing target split tracking. Amplitude and phase mismatching and mutual coupling between radar sensor arrays cause an inaccuracy problem in DOA estimation. By quantifying amplitude and phase distortion levels for each angle, we compensate the sensor distortion. Applying the proposed method to Bartlett, Capon and multiple signal classification (MUSIC) algorithms, we experimentally demonstrate the performance improvement using both experimental data from the chamber and real data obtained in actual road.

A method is proposed for improving the accuracy of the characteristic basis function method (CBFM) using the multilevel approach. With this technique, CBFs taking into account multiple scattering calculated for each block (IP-CBFs; improved primary CBFs) are applied to CBFM using a multilevel approach. By using IP-CBFs, the interaction between blocks is taken into account, and thus it is possible to reduce the number of CBFs while maintaining accuracy, even if the multilevel approach is used. The radar cross section (RCS) of a cube, a cavity, and a dielectric sphere were analyzed using the proposed CBFs, and as a result it was found that accuracy is improved over the conventional method, despite no major change in the number of CBFs.