Weak target detection is a key problem in passive bistatic radar (PBR). Track-before-detect (TBD) is an effective solution which has drawn much attention recently. However, TBD has not been fully developed in PBR. In this paper, the transition function and the selection of parameters in dynamic programming are analyzed in PBR. Then a novel processing scheme of dynamic programming based TBD is proposed to reduce the computation complexity without severely decreasing the detection performance. Discussions including complexity, detection performance, threshold determination, selection of parameters and detection of multitarget, are presented in detail. The new method can provide fast implementation with only a slight performance penalty. In addition, good multitarget detection performance can be achieved by using this method. Simulations are carried out to present the performance of the proposed processing scheme.

In automotive frequency modulated continuous wave (FMCW) radar based on multiple ramps with different slope, an effective pairing algorithm is required to simultaneously detect the target range and velocity. That is, as finding beat-frequencies intersecting at a single point of the range-Doppler map, we extract the range and velocity of a target. Unlike the ideal case, however, in a real radar system, even though multiple beat frequencies are originated from the same target, these beat frequencies have many different intersection values, resulting in mismatch pairing during the pairing step. Moreover, this problem also reduces the detection accuracy and the radar detection performance. In this study, we found that mismatch pairing is caused by the round-off errors of the range-beat frequency and Doppler frequency, as well as their various combinations in the discrete frequency domain. We also investigated the effect of mismatch pairing on detection performance, and proposed a new approach to minimize this problem. First, we propose integer and half-integer frequency position-based pairing method during extraction of the range and Doppler frequencies in each ramp to increase detection accuracy. Second, we propose a window-based pairing method to identify the same target from range-Doppler frequencies extracted in the first step. We also find the appropriate window size to overcome pairing mismatch. Finally, we propose the method to obtain a higher accuracy of range and velocity by weighting the values determined in one window. To verify the detection performance of the proposed method by comparison with the typical method, simulations were conducted. Then, in a real field test using the developed radar prototype, the detection probability of the proposed algorithm showed more than 60% improvement in comparison with the conventional method.

We focus on forward-looking radar network systems for automotive usages. By using multiple radars, the radar network systems will achieve reliable detection and wide observation area. The forward-looking systems by cameras are famous. In order to realize more reliable safety, the cameras had better be used with other sensing devices such as the radar network. In the radar network, processing of the data, which is derived from the multiple receivers, is important because the processing decides the estimation performance. In this paper, we will introduce our estimation algorithm which focuses on target existence probability and virtual receivers. The performance will be evaluated by simulated targets which are both single point model and 3D target model.

A monolithic frequency synthesizer with wide tuning range, low phase noise and spurs was realized in 0.13,$mu$m CMOS technology. It consists of an analog PLL, a harmonic-rejection mixer and injection-locked frequency doublers to cover the whole 6--18,GHz frequency range. To achieve a low phase noise performance, a sub-sampling PLL with non-dividers was employed. The synthesizer can achieve phase noise $-$113.7,dBc/Hz@100,kHz in the best case and the reference spur is below $-$60,dBc. The core of the synthesizer consumes about 110,mA*1.2,V.

In recent years, there are many collision accidents between vehicles due to human errors. As one of countermeasures against the collision accidents, automotive radar systems have been supporting vehicle drivers. By the automotive radar mounted on the vehicle, it is possible to recognize the situation around the vehicle. The ranging with automotive infrared laser radar is very accurate, and able to understand the object existence in the observation around the vehicle. However, in order to grasp the situation around the vehicle, it is necessary to be aware of the attribute of the detected object. The information obtained by the automotive radar vehicle is only the direction and the distance of the object. Thus, the recognition of the attribute of the detected object is very difficult. In this paper, we propose a novel vehicle information acquisition method by using 2D reflector code. Through experiments, we show that the proposed method is able to detect 2D reflector code and is effective for vehicle information acquisition.

Radar systems using ultra-wideband (UWB) signals have definitive advantages in high range resolution. These are suitable for accurate 3-dimensional (3-D) sensing by rescue robots operating in disaster zone settings, where optical sensing is not applicable because of thick smog or high-density gas. For such applications, where no a priori information of target shape and position is given, an accurate method for 3-D imaging and motion estimation is strongly required for effective target recognition. In addressing this issue, we have already proposed a non-parametric 2-dimensional (2-D) imaging method for a target with arbitrary target shape and motion including rotation and translation being tracked using a multi-static radar system. This is based on matching target boundary points obtained using the range points migration (RPM) method extended to the multi-static radar system. Whereas this method accomplishes accurate imaging and motion estimation for single targets, accuracy is degraded severely for multiple targets, due to interference effects. For a solution of this difficulty, this paper proposes a method based on a novel matching scheme using not only target points but also normal vectors on the target boundary estimated by the Envelope method; interference effects are effectively suppressed when incorporating the RPM approach. Results from numerical simulations for both 2-D and 3-D models show that the proposed method simultaneously achieves accurate target imaging and motion tracking, even for multiple moving targets.

The combined linear frequency modulation continuous wave (LFMCW) and inverse synthetic aperture radar (ISAR) can be used for imaging long-distance targets because of its long-distance and high resolution imaging abilities. In this paper, we find and study the dechirp distortion phenomenon (DDP) for imaging long-distance targets by a dechirp-on-receive LFMCW radar. If the targets are very far from the radar, the maximum delay-time is not much smaller than a single sweep duration, and the dechirp distortion is triggered since the distance of the target is unknown in a LFMCW-ISAR system. DDP cannot be ignored in long-distance imaging because double images of a target appear in the frequency domain, which reduces resolution and degrades image quality. A novel LFMCW-ISAR signal model is established to analyze DDP and its negative effects on long-distance target imaging. Using the proportionately distributed energy of double images, the authors propose a method to correct dechirp distortion. In addition, the applicable scope of the proposed method is also discussed. Simulation results validate the theoretical analysis and the effectiveness of the proposed method.

Soil moisture retrieval from polarimetric synthetic aperture radar (SAR) imagery over forested terrain is quite a challenging problem, because the radar backscatter is affected by not only the moisture content, but also by large vegetation structures such as the trunks and branches. Although a large number of algorithms which exploit radar backscatter to infer soil moisture have been developed, most of them are limited to the case of bare soil or little vegetation cover that an incident wave can easily reach the soil surface without serious disturbance. However, natural land surfaces are rarely free from vegetation, and the disturbance in radar backscatter must be properly compensated to achieve accurate soil moisture measurement in a diversity of terrain surfaces. In this paper, a simple polarimetric parameter, co-polarized backscattering ratio, is shown to be a criterion to infer moisture content of forested terrain, from both a theoretical forest scattering simulation and an appropriate experimental validation under well-controlled condition. Though modeling of forested terrain requires a number of scattering mechanisms to be taken into account, it is essential to isolate them one by one to better understand how soil moisture affects a specific and principal scattering component. For this purpose, we consider a simplified microwave scattering model for forested terrain, which consists of a cloud of dielectric cylinders as a representative of trunks, vertically stood on a flat dielectric soil surface. This simplified model can be considered a simple boreal forest model, and it is revealed that the co-polarization ratio in the ground-trunk double-bounce backscattering can be an useful index to monitor the relative variation in the moisture content of the boreal forest.

Recently, radar resource management of multifunction radar is a challenging issue in electronically scanned array radar technology. This paper deals with radar beam scheduling, which is a core issue of radar resource management. This paper proposed stochastic scheduler algorithm using Simulated Annealing (SA) and Hybrid scheduler algorithm which automatically selects two different types of schedulers according to the radar load: Rule based scheduler using modified Butler algorithm for underload situations and SA based scheduler for overload situations. The proposed algorithms are evaluated in terms of scheduling latency, the number of scheduled tasks, and time complexity. The simulation results show that the performance of rule based scheduler is seriously degraded in overload situation. However, SA based scheduler and Hybrid scheduler have graceful performance degradation in overload situation. Compared with rule based scheduler, SA based scheduler and Hybrid scheduler can schedule many more tasks on time for the same operation duration in the overload situation. Even though their time complex is relatively high, it can be applied to real applications if the parameters are properly controlled. Especially, Hybrid scheduler has an advantage of low time complexity with good performance.

Ultra-wide band (UWB) radar has a great advantage for range resolution, and is suitable for 3-dimensional (3-D) imaging sensor, such as for rescue robots or surveillance systems, where an accurate 3-dimensional measurement, impervious to optical environments, is indispensable. However, in indoor sensing situations, an available aperture size is severely limited by obstacles such as collapsed furniture or rubles. Thus, an estimated region of target image often becomes too small to identify whether it is a human body or other object. To address this issue, we previously proposed the image expansion method based on the ellipse extrapolation, where the fitting space is converted from real space to data space defined by range points to enhance the extrapolation accuracy. Although this method achieves an accurate image expansion for some cases, by exploiting the feature of the efficient imaging method as range points migration (RPM), there are still many cases, where it cannot maintain sufficient extrapolation accuracy because it only employs the single scattered component for imaging. For more accurate extrapolation, this paper extends the above image expansion method by exploiting double-scattered signals between the target and the wall in an indoor environment. The results from numerical simulation validate that the proposed method significantly expands the extrapolated region for multiple elliptical objects, compared with that obtained using only single scattered signal.

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.

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.

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.

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.

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.

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 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.

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.

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.

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.