Electromagnetic scattering problems of canonical 2D structures can be analyzed with a high degree of accuracy by using the point matching method with mode expansion. In this paper, we will extend our previous method to 3D electromagnetic scattering problems and investigate the radar cross section of spherical shells and the computational accuracy.

A switchable microwave reflector, reflection of which is actively controlled using diodes was proposed. Pin diodes have large resistance and capacitance without DC bias and small resistance and inductance with DC bias in microwave band. The reflector was designed by using the characteristics. In this paper, effects of a periodic structure on the reflector were verified with simulation and equivalent circuit model. A prototype reflector was able to switch between about $-20$ dB and $-0.1$ dB reflection coefficient at 2 GHz.

Recent studies have focused on developing security systems using micro-Doppler radars to detect human bodies. However, the resolution of these conventional methods is unsuitable for identifying bodies and moreover, most of these conventional methods were designed for a solitary or sufficiently well-spaced targets. This paper proposes a solution to these problems with an image separation method for two closely spaced pedestrian targets. The proposed method first develops an image of the targets using ultra-wide-band (UWB) Doppler imaging radar. Next, the targets in the image are separated using a supervised learning-based separation method trained on a data set extracted using a range profile. We experimentally evaluated the performance of the image separation using some representative supervised separation methods and selected the most appropriate method. Finally, we reject false points caused by target interference based on the separation result. The experiment, assuming two pedestrians with a body separation of 0.44m, shows that our method accurately separates their images using a UWB Doppler radar with a nominal down-range resolution of 0.3m. We describe applications using various target positions, establish the performance, and derive optimal settings for our method.

Synthetic aperture radar (SAR) is an indispensable tool for low visibility ground surface measurement owing to its robustness against optically harsh environments such as adverse weather or darkness. As a leading-edge approach for SAR image processing, the coherent change detection (CCD) technique has been recently established; it detects a temporal change in the same region according to the phase interferometry of two complex SAR images. However, in the case of general damage assessment following an earthquake or mudslide, the technique requires not only the detection of surface change but also an assessment for height change quantity, such as occurs with a building collapse or road subsidence. While the interferometric SAR (InSAR) approach is suitable for height assessment, it is basically unable to detect change if only a single observation is made. To address this issue, we previously proposed a method of estimating height change according to phase interferometry of the coherence function obtained by dual band-divided SAR images. However, the accuracy of this method significantly degrades in noisy situations owing to the use of the phase difference. To resolve this problem, this paper proposes a novel height estimation method by exploiting the frequency characteristic of coherence phases obtained by each SAR image multiply band-divided. The results obtained from numerical simulations and experimental data demonstrate that our proposed method offers accurate height change estimation while avoiding degradation in the spatial resolution.

Polarimetric coherence strongly relates to the types and orientations of local scatterers. An optimization scheme is proposed to optimize the coherence between two polarimetric channels for polarimetric SAR (PolSAR) data. The coherence magnitude (correlation coefficient) is maximized by rotating a polarimetric coherence matrix in the rotation domain around the radar line of sight. L-band E-SAR and X-band Pi-SAR PolSAR data sets are used for demonstration and validation. The coherence of oriented manmade targets is significantly enhanced while that of forests remains relatively low. Therefore, the proposed technique can effectively discriminate these two land covers which are easily misinterpreted by the conventional model-based decomposition. Moreover, based on an optimized polarimetric coherence parameter and the total backscattered power, a simple manmade target extraction scheme is developed for application demonstration. This approach is applied with the Pi-SAR data. The experimental results validate the effectiveness of the proposed method.

In this letter, the orthogonal projection (OP) estimation of the direction of arrival (DOA) and direction of departure (DOD) of multiple targets for bistatic multiple-input multiple-output radars is addressed. First, a two-dimensional direction finding estimator based on OP technique with automatic pairing is developed. Second, this letter also presents a modified reduced-dimension estimator by utilizing the characteristic of Kronecker product, which only performs two one-dimensional angle estimates. Furthermore, the DOA and DOD pairing is given automatically. Finally, simulation results are presented to verify the efficiency of the proposed estimators.

This letter presents a novel phase synchronization algorithm for a MIMO radar system in order to overcome the limitation of the existing algorithms relying on channel reciprocity, or line-of-sight, assumption between radar elements. The proposed algorithm is capable of synchronizing local oscillator phases among radar elements even if line-of-sight communication links are not available. Furthermore, the proposed algorithm exhibits robust MSE performance in the presence of frequency estimation error. The performance of the proposed algorithm was analyzed theoretically and verified by simulations.

In this paper, a new method is proposed for unsupervised speckle level estimation in synthetic aperture radar (SAR) images. It is assumed that fully developed speckle intensity has a Gamma distribution. Based on this assumption, estimation of the equivalent number of looks (ENL) is transformed into noise variance estimation in the logarithmic SAR image domain. In order to improve estimation accuracy, texture analysis is also applied to exclude areas where speckle is not fully developed (e.g., urban areas). Finally, the noise variance is estimated by a 2-dimensional autoregressive (AR) model. The effectiveness of the proposed method is verified with several SAR images from different SAR systems and simulated images.

Detection of human respiration and heartbeat is an essential demand in medical monitoring, healthcare vigilance, as well as in rescue activities after earthquakes. Radar is an important tool to detect human respiration and heartbeat. Compared to body-attached sensors, radar has the advantage of conducting detection without contacting the subject, which is favorable in practical usage. In this paper, we conduct fundamental studies on ultra-wideband (UWB) radar for detection of the respiration and heartbeat by computer simulations. The main achievement of our work is the development of a UWB radar simulation system. Using the developed simulation system, three UWB frequency bands, i.e., 3.4-4.8GHz, 7.25-10.25GHz, as well as 3.1-10.6GHz, are compared in terms of their respiration and heartbeat detection performance. Our results show that the first two bands present identical performance, while the third one presents much better performance. The effects of using multiple antennas are also evaluated. Our results show that increasing the number of antennas can steadily increase the detection ability.

The conventional covariance matrix technique based subspace methods, such as the 2-D Capon algorithm and computationally efficient ESPRIT-type algorithms, are invalid with a single snapshot in a bistatic MIMO radar. A novel matrix pencil method is proposed for the direction of departures (DODs) and direction of arrivals estimation (DOAs) estimation. The proposed method constructs an enhanced matrix from the direct sampled data, and then utilizes the matrix pencil approach to estimate DOAs and DODs, which are paired automatically. The proposed method is able to provide favorable and unambiguous angle estimation performance with a single snapshot. Simulation results are presented to verify the effectiveness of the proposed method.

A covariance-based algorithm is proposed to find a barrage jammer suppression filter for surveillance radar with an adaptive array. The conventional adaptive beamformer (ABF) or adaptive sidelobe canceller (ASLC) with auxiliary antennas can be used successfully in sidelobe jammer rejection. When a jammer shares the same bearing with the target of interest, however, those methods inherently cancel the target in their attempt to null the jammer. By exploiting the jammer multipath scattered returns incident from other angles, the proposed algorithm uses only the auto-covariance matrix of the sample data produced by stacking range cell returns in a pulse repetition interval (PRI). It does not require estimation of direction of arrival (DOA) or time difference of arrival (TDOA) of multipath propagation, thus making it applicable to electronic countermeasure (ECM) environments with high power barrage jammers and it provides the victim radar with the ability to null both the sidelobe (sidebeam) and mainlobe (mainbeam) jammers simultaneously. Numeric simulations are provided to evaluate the performance of this filter in the presence of an intensive barrage jammer with jammer-to-signal ratio (JSR) greater than 30dB, and the achieved signal-to-jammer-plus-noise ratio (SJNR) improvement factor (IF) exceeds 46dB.

Ultra-wideband pulse radar exhibits high range resolution, and excellent capability in penetrating dielectric media. With that, it has great potential as an innovative non-destructive inspection technique for objects such as human body or concrete walls. For suitability in such applications, we have already proposed an accurate permittivity estimation method for a 2-dimensional dielectric object of arbitrarily shape and clear boundary. In this method, the propagation path estimation inside the dielectric object is calculated, based on the geometrical optics (GO) approximation, where the dielectric boundary points and its normal vectors are directly reproduced by the range point migration (RPM) method. In addition, to compensate for the estimation error incurred using the GO approximation, a waveform compensation scheme employing the finite-difference time domain (FDTD) method was incorporated, where an initial guess of the relative permittivity and dielectric boundary are employed for data regeneration. This study introduces the 3-dimensional extension of the above permittivity estimation method, aimed at practical uses, where only the transmissive data are effectively extracted, based on quantitative criteria that considers the spatial relationship between antenna locations and the dielectric object position. Results from a numerical simulation verify that our proposed method accomplishes accurate permittivity estimations even for 3-dimensional dielectric medium of wavelength size.

In this paper, a multi-temporal analysis of polarimetric synthetic aperture radar (Pol-SAR) data over the sandbank and oyster farm area is presented. Specifically, a four-component scattering model, being able to identify single bounce, double bounce, volume, and helix scattering power contributions, has been employed to retrieve information. Decomposition results of a time series RADARSAT Pol-SAR images acquired over the western Taiwan coast indicate that the coastal tide level plays a key role in the sandbank and oyster farm monitoring. At high tide levels, the underlying sandbank creates a shallow area with an increased roughness of the above sea surface, leading to an enhanced surface scattering power as compared to the ambient water. Contrarily, at low tide levels, the exposed sandbank appears to be a smooth scatterer, generating decreased backscattering power than the surrounding area. On the other hand, the double-bounce scattering power is shown to be highly correlated with the tide level in the oyster farms due to their vertical structures. This also demonstrates a promising potential of the four-component scattering power decomposition for coastal tide level monitoring applications.

A microwave mammography setup for clinical testing was developed and used to successfully carry out an initial clinical test. The equipment is based on multistatic ultra wideband (UWB) radar, which features a multistatic microwave imaging via space time (MS-MIST) algorithm for high resolution and a conformal array with an aspirator for fixing the breast in place. In this paper, an outline of the equipment, a numerical simulation, and clinical test results are presented.

The classification of human motion is an important aspect of monitoring pedestrian traffic. This requires the development of advanced surveillance and monitoring systems. Methods to achieve this have been proposed using micro-Doppler radars. However, reliable long-term data and/or complicated procedures are needed to classify motion accurately with these conventional methods because their accuracy and real-time capabilities are invariably inadequate. This paper proposes an accurate and real-time method for classifying the movements of pedestrians using ultra wide-band (UWB) Doppler radar to overcome these problems. The classification of various movements is achieved by extracting feature parameters based on UWB Doppler radar images and their radial velocity distributions. Experiments were carried out assuming six types of pedestrian movements (pedestrians swinging both arms, swinging only one arm, swinging no arms, on crutches, pushing wheelchairs, and seated in wheelchairs). We found they could be classified using the proposed feature parameters and a k-nearest neighbor algorithm. A classification accuracy of 96% was achieved with a mean calculation time of 0.55s. Moreover, the classification accuracy was 99% using our proposed method for classifying three groups of pedestrian movements (normal walkers, those on crutches, and those in wheelchairs).

Ocean surface current radar is a Doppler radar to observe oceanographic information using the Bragg scattering resonance mechanism. In this paper, we consider angular resolution improvement of the radar. The radar employs an antenna array with FMICW operation, then it can resolve angular distribution by Digital Beam Forming (DBF) and distance by Fourier transform of the beat signal obtained by the FMICW radar. In order to obtain sufficient angular resolution, large array length or aperture with increasing the number of elements is needed, that is often difficult to realize in the HF/VHF ocean surface current radar. In this paper we propose to apply the Khatri-Rao (KR) product array processing to the radar. To verify effectiveness of the KR product array processing in angular resolution enhancement for the ocean surface current radar, we apply the KR product array to actual experimental data set of the radar, and show that the method is available to angular resolution enhancement and Doppler spectrum improvement.

This paper reports an advanced millimeter-wave radar system to enable detection of vehicles and pedestrians in wide areas around the radar site such as an intersection. We focus on a pulse coding scheme using complementary codes to reduce range sidelobe for discriminating vehicles from pedestrians with high accuracy. In order to suppress sidelobe increase created by RF circuit imperfections, a π/2 shift pulse modulation method with a complementary code pair cycle is presented. Moreover, in order to improve the angular resolution, a high-resolution direction of arrival estimation involving Tx beam scanning is presented. Experiments on a prototype confirm its range sidelobe suppression exceeds 40dB and its angular resolution is 5° for two human's separation at the distance of about 10m in an anechoic chamber. In a trial intersection experiment, a pedestrian detection rate of 95% was achieved at the false alarm rate of 10% in the range from 5m to 40m. The results prove the system's feasibility for future automotive safety application.

In order to execute coherent Doppler processing in a high range-rate scenario, whether it is for detection, estimation or imaging, range walk embedded in target return should be compensated first. In case of a bistatic radar geometry where a transmitter, a receiver and a target can be all moving, the extent of range walk depends on their relative positions and velocities. This paper presents a coherent Doppler processing algorithm to achieve target detection and Doppler frequency estimation of a target under a bistatic radar geometry. This algorithm is based on the assumption that a target has constant Doppler frequency during a coherent processing interval (CPI). Thus, we first show under what condition the assumption could be valid. We next develop an algorithm, along with its implementation procedures where the region of range walk, called a window, is manipulated. Finally, the performance of a proposed algorithm is examined through simulations.

Ultra-wideband pulse radar is a promising technology for the imaging sensors of rescue robots operating in disaster scenarios, where optical sensors are not applicable because of thick smog or high-density gas. For the above application, while one promising ultra-wideband radar imaging algorithm for a target with arbitrary motion has already been proposed with a compact observation model, it is based on an ellipsoidal approximation of the target boundary, and is difficult to apply to complex target shapes. To tackle the above problem, this paper proposes a non-parametric and robust imaging algorithm for a target with arbitrary motion including rotation and translation being observed by multi-static radar, which is based on the matching of target boundary points obtained by the range points migration (RPM) algorithm extended to the multi-static radar model. To enhance the imaging accuracy in situations having lower signal-to-noise ratios, the proposed method also adopts an integration scheme for the obtained range points, the antenna location part of which is correctly compensated for the estimated target motion. Results from numerical simulations show that the proposed method accurately extracts the surface of a moving target, and estimates the motion of the target, without any target or motion model.

The optimization of polarimetric contract enhancement (OPCE) is one of the important problems in radar polarimetry since it provides a substantial benefit for target enhancement. Considering different scattering mechanisms between the desired targets and the undesired targets, Yang et al. extended the OPCE model to the generalized OPCE (GOPCE) problem. Based on a modified GOPCE model and the linear discriminant analysis, a ship detector is proposed in this paper to improve the detection performance for polarimetric Synthetic Aperture Radar (SAR) imagery. In the proposed method, we modify the combination form of the three polarimetric parameters (i.e., the plane scattering similarity parameter, the diplane scattering similarity parameter and the Cloude entropy), then use an optimization function resembling the classical Fisher criterion to optimize the optimal polarization states corresponding to the radar received power and the fusion vector corresponding to the polarimetric parameters. The principle of the optimization detailed in this paper lies in maximizing the difference between the desired targets and sea clutter, and minimizing the clutter variance at the same time. RADARSAT-2 polarimetric SAR data acquired over Tanggu Port (Tianjin, China) on June 23, 2011 are used for validation. The experimental results show that the proposed method improves the contrast of the targets and sea clutter and meanwhile reduces the clutter variance. In comparison to another GOPCE based ship detector and the classical polarimetric whitening filter (PWF), the proposed method shows a better performance for weak targets. In addition, we also use the RADARSAT-2 data acquired over San-Francisco on April 9, 2008 to further demonstrate the improvement of this method for target contrast.