This paper presents an interference suppression and signal restoration technique that can create the clean signals required by automotive frequency-modulated continuous wave radar systems. When a radar signal from another radar system interferes with own transmitted radar signal, the target detection performance is degraded. This is because the beat frequency corresponding to the target cannot be estimated owing to the increase in the noise floor. In this case, advanced weighted-envelope normalization or wavelet denoising can be used to mitigate the effect of the interference; however, these methods can also lead to the loss of the desired signal containing the range and velocity information of the target. Therefore, we propose a method based on an autoregressive model to restore a signal damaged by mutual interference. The method uses signals that are not influenced by the interference to restore the signal. In experiments conducted using two different automotive radar systems, our proposed method is demonstrated to effectively suppress the interference and restore the desired signal. As a result, the noise floor resulting from the mutual interference was lowered and the beat frequency corresponding to the desired target was accurately estimated.

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.

The design and performance evaluation is presented of a partially adaptive array that suppresses clutter from low elevation angles in atmospheric radar observations. The norm-constrained and directionally constrained minimization of power (NC-DCMP) algorithm has been widely used to suppress clutter in atmospheric radars, because it can limit the signal-to-noise ratio (SNR) loss to a designated amount, which is the most important design factor for atmospheric radars. To suppress clutter from low elevation angles, adding supplemental antennas that have high response to the incoming directions of clutter has been considered to be more efficient than to divide uniformly the high-gain main array. However, the proper handling of the gain differences of main and sub-arrays has not been well studied. We performed numerical simulations to show that using the proper gain weighting, the sub-array configuration has better clutter suppression capability per unit SNR loss than the uniformly divided arrays of the same size. The method developed is also applied to an actual observation dataset from the MU radar at Shigaraki, Japan. The properly gain-weighted NC-DCMP algorithm suppresses the ground clutter sufficiently with an average SNR loss of about 1 dB less than that of the uniform-gain configuration.

Ultra-wideband radar exhibits high range resolution, and excellent capability for penetrating dielectric media, especially when using lower frequency microwaves. Thus, it has a great potential for innovative non-destructive testing of aging roads or bridges or for non-invasive medical imaging applications. In this context, we have already proposed an accurate dielectric constant estimation method for a homogeneous dielectric medium, based on a geometrical optics (GO) approximation, where the dielectric boundary points and their normal vectors are directly reproduced using the range point migration (RPM) method. In addition, to compensate for the estimation error incurred by the GO approximation, a waveform compensation scheme employing the finite-difference time domain (FDTD) method was incorporated. This paper shows the experimental validation of this method, where a new approach for suppressing the creeping wave along the dielectric boundary is also introduced. The results from real observation data validate the effectiveness of the proposed method in terms of highly accurate dielectric constant estimation and embedded object boundary reconstruction.

Microwave ultra-wideband (UWB) radar systems are advantageous for their high-range resolution and ability to penetrate dielectric objects. Internal imaging of dielectric objects by UWB radar is a promising nondestructive method of testing aging roads and bridges and a noninvasive technique for human body examination. For these applications, we have already developed an accurate internal imaging approach based on the range points migration (RPM) method, combined with a method that efficiently estimates the dielectric constant. Although this approach accurately extracts the internal boundary, it is applicable only to highly conductive targets immersed in homogeneous dielectric media. It is not suitable for multi-layered dielectric structures such as human tissues or concrete objects. To remedy this limitation, we here propose a novel dielectric constant and boundary extraction method for double-layered materials. This new approach, which simply extends the Envelope method to boundary extraction of the inner layer, is evaluated in finite difference time domain (FDTD)-based simulations and laboratory experiments, assuming a double-layered concrete cylinder. These tests demonstrate that our proposed method accurately and simultaneously estimates the dielectric constants of both media and the layer boundaries.

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.

Ultra wideband radar is one of the most promising techniques for non-invasive imaging in a dielectric medium, which is suitable for both medical screening and non-destructive testing applications. A novel imaging method for such an application is proposed in this brief paper, which has been extended from the advanced range points migration method to a multi-static observation model with circular arrays. One notable feature of this method is that it is applicable to either arbitrary dielectric or internal object shapes, and it can also expand the reconstructible image region compared with that obtained using the mono-static model by employing received signals after penetrating various propagation paths in dielectric medium. Numerical results for the investigation of an elliptical object, surrounded by a random dielectric surface, show the remarkable advantages of the proposed method with respect to image expansion.

Ultra-wide band (UWB) pulse radar with high range resolution and dielectric permeability is promising as an internal imaging technique for non-destructive testing or breast cancer detection. Various imaging algorithms for buried objects within a dielectric medium have been proposed, such as aperture synthesis, the time reversal approach and the space-time beamforming algorithm. However, these algorithms mostly require a priori knowledge of the dielectric medium boundary in image focusing, and often suffer from inadequate accuracy to identify the detailed structure of buried targets, such as an edge or specular surface owing to employing the waveform focusing scheme. To overcome these difficulties, this paper proposes an accurate and non-parametric (i.e. using an arbitrary shape without target modeling) imaging algorithm for targets buried in a homogeneous dielectric medium by advancing the RPM (Range Points Migration) algorithm to internal imaging issues, which has been demonstrated to provide an accurate image even for complex-shaped objects in free-space measurement. Numerical simulations, including those for two-dimensional (2-D) and three-dimensional (3-D) cases, verify that the proposed algorithm enhances the imaging accuracy by less than 1/10 of the wavelength and significantly reduces the computational cost by specifying boundary extraction compared with the conventional SAR-based algorithm.

Ultra-wideband (UWB) pulse radars have a definite advantage in high-range resolution imaging, and are suitable for short-range measurements, particularly at disaster sites or security scenes where optical sensors are rarely suitable because of dust or strong backlighting. Although we have already proposed an accurate imaging algorithm called Range Points Migration (RPM), its reconstructible area is too small to identify the shape of an object if it is far from the radar and the size of the aperture is inadequate. To resolve this problem, this paper proposes a novel image expansion method based on ellipse extrapolation; it enhances extrapolation accuracy by deriving direct estimates of the observed range points distributed in the data space. Numerical validation shows that the proposed method accurately extrapolates part of the target boundary, even if an extremely small region of the target boundary is obtained by RPM.

Ultra-wide band (UWB) pulse radar has high range resolution, and is thus applicable to imaging sensors for a household robot. To enhance the imaging region of UWB radar, especially for multiple objects with complex shapes, an imaging algorithm based on aperture synthesis for multiple scattered waves has been proposed. However, this algorithm has difficulty realizing in real-time processing because its computation time is long. To overcome this difficulty, this letter proposes a fast accurate algorithm for shadow region imaging by incorporating the Range Points Migration (RPM) algorithm. The results of the numerical simulation show that, while the proposed algorithm affects the performance of the shadow region imaging slightly, it does not cause significant accuracy degradation and significantly decreases the computation time by a factor of 100 compared to the conventional algorithm.

The applicability in harsh optical environments, such as dark smog, or strong backlight of ultra-wide band (UWB) pulse radar has a definite advantage over optical ranging techniques. We have already proposed the extended Synthetic Aperture Radar (SAR) algorithm employing double scattered waves, which aimed at enhancing the reconstructible region of the target boundary including shadow region. However, it still suffers from the shadow area for the target that has a sharp inclination or deep concave boundary, because it assumes a mono-static model, whose real aperture size is, in general, small. To resolve this issue, this study proposes an extension algorithm of the double scattered SAR based on a multi-static configuration. While this extension is quite simple, the effectiveness of the proposed method is nontrivial with regard to the expansion of the imaging range. The results from numerical simulations verify that our method significantly enhances the visible range of the target surfaces without a priori knowledge of the target shapes or any preliminary observation of its surroundings.

In this paper, the inherent problem of the Hough transform when applied to search radars is considered. This problem makes the detection probability of a target depend on the length of the target line in the data space in addition to the received SNR from it. It is shown that this problem results in a non-uniform distribution of noise power in the parameter space. In other words, noise power in some regions of the parameter space is greater than in others. Therefore, the detection probability of the targets covered by these regions will decrease. Our solution is to modify the Hough detector to remove the problem. This modification uses non-uniform quantization in the parameter space based on the Maximum Entropy Quantization method. The details of implementing the modified Hough detector in a search radar are presented according to this quantization method. Then, it is shown that by using this method the detection performance of the target will not depend on its length in the data space. The performance of the modified Hough detector is also compared with the standard Hough detector by considering their probability of detection and probability of false alarm. This comparison shows the performance improvement of the modified detector.

Pulse radars with UWB signals are promising as a high-resolution imaging technique that can be used for the non-destructive measurement of surface details in industrial products such as antennas and aircraft. We have already proposed a fast 3-D imaging algorithm, SEABED, that utilizes a reversible transform between the time delay and the target boundary. However, data acquisition is time-consuming when obtaining an accurate image because it assumes a mono-static radar with 2-D scanning of an antenna. In this paper, we utilize linear array antennas and propose a fast and accurate imaging algorithm. We extend the reversible transform for mono-static radars to apply to bi-static radars to reduce the data acquisition time. The effectiveness of the proposed method is verified with numerical simulations and experiments.

Target shape estimation with UWB pulse radars is a promising imaging technique for household robots. We have already proposed a fast imaging algorithm, SEABED, that is based on a reversible transform BST (Boundary Scattering Transform) between the received signals and the target shape. However, the target image obtained by SEABED deteriorates in a noisy environment because it utilizes a derivative of received data. In this paper, we propose a robust imaging method with an envelope of circles. We clarify by numerical simulation that the proposed method can realize a level of robust and fast imaging that cannot be achieved by the original SEABED.

UWB pulse radars enable us to measure a target location with high range-resolution, and so are applicable for measurement systems for robots and automobile. We have already proposed a robust and fast imaging algorithm with an envelope of circles, which is suitable for these applications. In this method, we determine time delays from received signals with the matched filter for a transmitted waveform. However, scattered waveforms are different from transmitted one depending on the target shape. Therefore, the resolution of the target edges deteriorates due to these waveform distortions. In this paper, a high-resolution imaging algorithm for convex targets is proposed by iteration of the shape and waveform estimation. We show application examples with numerical simulations and experiments, and confirm its capability to detect edges of an object.

Expressions are presented for the probability of target detection and the measurement accuracy of the detection, taking into account the effects of antenna beam-pointing error. Evaluation of these expressions requires numerical integration, which is computationally expensive. Approximate but analytic and efficient expressions are also presented. Numerical examples are given to present the relative accuracy of our analytic approximations.

A microstrip array antenna with 45-degree inclined linear polarization is proposed for automotive radars. The proposed antenna has the advantages of high aperture efficiency, low profile and ease of manufacture. The rectangular radiating elements inclined at 45 degrees to the straight microstrip line are directly connected to it at their corners in the proposed array antenna. The radiating element has a feature that radiation conductance for co-polarization is controlled widely enough to set desired amplitude distribution keeping excited mode for cross-polarization negligibly small. The feed line loss of the linear array antenna having 15 wavelengths is estimated 0.9 dB in the design taking the loss of the microstrip line into account. The performance of two types of developed antennas, for electrical and mechanical scanning radars, is presented. The fan beam subarray antenna for electrical scanning radars has an aperture efficiency of 53% with gain of 22.5 dBi at 76.5 GHz. For mechanical scanning radars, the two-stage series feeding circuit is also proposed for lower feed line loss and setting desired amplitude distribution. The pencil beam array antenna has an aperture efficiency of 39% with gain of 32.2 dBi at 76.5 GHz.

Many previous works state that a multiple Sidelobe canceller (MSLC) with two auxiliary antennas is successful in suppressing two interference signals received simultaneously by sidelobes of a main antenna. In this paper, we show that the MSLC does not always guarantee such capability in three dimensional applications where the incident direction of interference signals is defined by two angles (elevation and azimuth). We show the singularity of the autocorrelation matrix for the auxiliary channel signals induces the degradation of the capability by analyzing characteristics of MSLC's in three dimensional applications from the view point of the eigenvalue problem. To overcome this singularity, we propose a novel MSLC controlling the placement of auxiliary antennas by means of switching over three antennas arranged triangularly. Some simulations are conducted to show the effectiveness of the proposed MSLC.