Three-dimensional (3-D) scattering center models use a finite number of point scatterers to efficiently represent complex radar target signature. Using the CLEAN algorithm, 3-D scattering center model is extracted from the inverse synthetic aperture radar (ISAR) image, which is generated based on the shooting and bouncing ray (SBR) technique. The conventional CLEAN extracts the strongest peak iteratively based on the assumption that the scattering centers are isolated. In a realistic target, however, both interference from the closely spaced points and additive noise distort the extraction process. This paper proposes a matched filter-based CLEAN algorithm to improve accuracy efficiently. Using the matched filtering of which impulse response is the known point spread function (PSF), a point most correlated with the PSF is extracted. Thus, the proposed method optimally enhances the accuracy in the presence of massive distortions. Numerical simulations using canonical and realistic targets demonstrate that the extraction accuracy is improved without loss of time-efficiency compared with the existing CLEAN algorithms.

This paper reports the development of a landmine visualization system based on complex-valued self-organizing map (CSOM) by employing one-dimensional (1-D) array of taper-walled tapered slot antennas (TSAs). Previously we constructed a high-density two-dimensional array system to observe and classify complex-amplitude texture of scattered wave. The system has superiority in its adaptive distinction ability between landmines and other clutters. However, it used so many (144) antenna elements with many mechanical radio-frequency (RF) switches and cables that it has difficulty in its maintenance and also requires long measurement time. The 1-D array system proposed here uses only 12 antennas and adopts electronic RF switches, resulting in easy maintenance and 1/4 measurement time. Though we observe stripe noise specific to this 1-D system, we succeed in visualization with effective solutions.

In this paper, we propose a received signal interpolation method for enhancing the performance of multiple signal classification (MUSIC) algorithm. In general, the performance of the conventional MUSIC algorithm is very sensitive to signal-to-noise ratio (SNR) of the received signal. When array elements receive the signals with nonuniform SNR values, the resolution performance is degraded compared to elements receiving the signals with uniform SNR values. Hence, we propose a signal calibration technique for improving the resolution of the algorithm. First, based on original signals, rough direction of arrival (DOA) estimation is conducted. In this stage, using frequency-domain received signals, SNR values of each antenna element in the array are estimated. Then, a deteriorated element that has a relatively lower SNR value than those of the other elements is selected by our proposed scheme. Next, the received signal of the selected element is spatially interpolated based on the signals received from the neighboring elements and the DOA information extracted from the rough estimation. Finally, fine DOA estimation is performed again with the calibrated signal. Simulation results show that the angular resolution of the proposed method is better than that of the conventional MUSIC algorithm. Also, we apply the proposed scheme to actual data measured in the testing ground, and it gives us more enhanced DOA estimation result.

This paper presents a calibration method for RF switch channels of a near-range multistatic linear array radar. The method allows calibration of the channel transfer functions of the RF switches and antenna transfer functions in frequency domain data, without disconnecting the antennas from the radar system. In addition, the calibration of the channels is independent of the directivities of the transmitting and receiving antennas. We applied the calibration method to a 3D imaging step-frequency radar system at 10-20GHz suitable for the nondestructive inspection of the walls of wooden houses. The measurement range of the radar is limited to 0-240mm, shorter than the antenna array length 480mm. This radar system allows acquiring 3D imaging data with a single scan. Using synthetic aperture radar processing, the structural health of braces inside the walls of wooden houses can be evaluated from the obtained 3D volume images. Based on experiment results, we confirmed that the proposed calibration method significantly improves the subsurface 3D imaging quality. Low intensity ghost images behind the brace target were suppressed, deformations of the target in the volume image were rectified and errors the range distance were corrected.

Transient scattering by a metal cylinder covered with inhomogeneous lossy material is analyzed for application of radar systems to nondestructive testing of reinforced concrete structures. First, inhomogeneous lossy material that is a model of corrosion by rust is approximated by a cylindrical multilayered medium, and analytic solution of a scattered field in frequency domain is derived. Next, time domain scattering response is calculated from the frequency domain data by using the inverse Fourier transform. Numerical results of pulse responses indicate that corrosion rate of the concrete can be evaluated by checking the waveform distortion of the pulse responses.

This paper describes a parametric representation of ultra-wideband radar signatures and its physical interpretation. Under the scattering theory of electromagnetic waves, a transfer function of radar scattering is factorized into three elementary parts and a radar signature with three parameters is derived. To use these parameters for radar target classification and identification, the relation between them and the response waveform is analytically revealed and numerically checked. The result indicates that distortion of the response waveform is sensitive to these parameters, and thus they can be expected to be used as features for radar target classification and identification.

The problem of E-polarized plane wave diffraction by a thin material strip is analyzed using the Wiener-Hopf technique together with approximate boundary conditions. Exact and high-frequency asymptotic solutions are obtained. Our final solution is valid for the case where the strip thickness is small and the strip width is large in comparison to the wavelength. The scattered field is evaluated asymptotically based on the saddle point method and a far field expression is derived. Numerical examples on the radar cross section (RCS) are presented for various physical parameters and the scattering characteristics of the strip are discussed in detail.

Microwave imaging techniques, in particular, synthetic aperture radar (SAR), are promising tools for terrain surface measurement, irrespective of weather conditions. The coherent change detection (CCD) method is being widely applied to detect surface changes by comparing multiple complex SAR images captured from the same scanning orbit. However, in the case of a general damage assessment after a natural disaster such as an earthquake or mudslide, additional about surface change, such as surface height change, is strongly required. Given this background, the current study proposes a novel height change estimation method using a CCD model based on the Pauli decomposition of fully polarimetric SAR images. The notable feature of this method is that it can offer accurate height change beyond the assumed wavelength, by introducing the frequency band-divided approach, and so is significantly better than InSAR based approaches. Experiments in an anechoic chamber on a 1/100 scaled model of the X-band SAR system, show that our proposed method outputs more accurate height change estimates than a similar method that uses single polarimetric data, even if the height change amount is over the assumed wavelength.

In this paper, we present the roles played by millimeter-waves in the realization of an Internet of Things (IoT) society. Millimeter-waves are becoming essential frequency resources, enabling ultra-high-speed wireless networks supporting massive data traffic and high-resolution sensor devices. Multiple antenna technologies such as phased arrays, sector antennas, and MIMO signal processing are key technologies for putting these into practical use. In this paper, various examples of integration of multi-antenna systems are shown, as well as demonstration on 60GHz-band millimeter-wave wireless access and 79GHz-band high-resolution radar. We also propose applications to ITS for an IoT society, combining millimeter-wave wireless access and radar sensors, and discuss technical issues to be solved in the future.

Range resolution is one of the metrics of radar performance. Synthetic bandwidth radar has been proposed for high-range-resolution. The transmitted frequency and down-conversion frequency of this type of radar are shifted by fixed amounts from pulse to pulse. Received signals are synthesized by taking IFFT for high-range-resolution. However, this type of radar has a problem with second-time-around echoes since multiple pulses are utilized. Moreover, a range shift occurs due to Doppler velocity. Thus second-time-around echo suppression and Doppler velocity compensation are required for accurate target range measurement. We show in this paper a Doppler velocity measurement method with second-time-around echo suppression for synthetic bandwidth radars. Our proposed method interleaves the transmission of ascending and descending frequency sequences. The Doppler velocity is measured by using a Fourier transform of the multiplication of the signals received using both sequences. The transmitted frequency difference of the adjacent pulses is wider than the bandwidth of the matched filter, so the second-time-around echoes are down-converted to the outside band of the matched filter and suppressed. We verify the principle of the proposed method using numerical simulations and experiments. The results show that second-time-around echoes were suppressed by 7.8dB, the Doppler velocity could be obtained and the range shift due to Doppler velocity was reduced by 7.37 times compared to the conventional SBR.

A fast parameter estimation method with a coarse estimation and a fine estimation for polyphase P coded signals is proposed. For a received signal with N sampling points, the proposed method has an improved performance when the signal-to-noise ratio (SNR) is larger than 2dB and a lower computational complexity O(N logs N) compared with the latest time-frequency rate estimation method whose computational complexity is O(N2).

Recent research on the assessment of low probability of interception (LPI) radar waveforms is mainly based on limiting spectral properties of Wigner matrices. As the dimension of actual operating data is constrained by the sampling frequency, it is very urgent and necessary to research the finite theory of Wigner matrices. This paper derives a closed-form expression of the spectral cumulative distribution function (CDF) for Wigner matrices of finite sizes. The expression does not involve any derivatives and integrals, and therefore can be easily computed. Then we apply it to quantifying the LPI performance of radar waveforms, and the Kullback-Leibler divergence (KLD) is also used in the process of quantification. Simulation results show that the proposed LPI metric which considers the finite sample size and signal-to-noise ratio is more effective and practical.

We proposed a new architecture of antenna, transmitter and receiver feeding configuration for small synthetic aperture radar (SAR) that is compatible with 100kg class satellite. Promising applications are constellations of earth observations together with optical sensors, and responsive, disaster monitoring missions. The SAR antenna is a deployable, passive, honeycomb panel antenna with slot array that can be stowed compactly. RF (radio frequency) instruments are in a satellite body and RF signal is fed to a deployable antenna through non-contacting choke flanges at deployable hinges. This paper describes its development strategy and the present development status of the small spaceborne SAR based on this architecture.

Ultra-wideband millimeter wave radars significantly enhance the capabilities of three-dimensional (3D) imaging sensors, making them suitable for short-range surveillance and security purposes. For such applications, developed the range point migration (RPM) method, which achieves highly accurate surface extraction by using a range-point focusing scheme. However, this method is inaccurate and incurs great computation cost for complicated-shape targets with many reflection points, such as the human body. As an essential solution to this problem, we introduce herein a range-point clustering algorithm that exploits, the RPM feature. Results from numerical simulations assuming 140-GHz millimeter wavelength radar verify that the proposed method achieves remarkably accurate 3D imaging without sacrificing computational efficiency.

A novel real-valued ESPRIT (RV-ESPRIT) algorithm is proposed to estimate the direction of arrival (DOA) and direction of departure (DOD) for noncircular signals in bistatic MIMO radar. By exploiting the property of signal noncircularity and Euler's formula, a new virtual array data of bistatic MIMO radar, which is twice that of the MIMO virtual array data, is established with real-valued sine and cosine data. Then the receiving/transmitting selective matrices are constructed to obtain the receiving/transmitting rotationally invariant factors. Compared to the existing angle estimation methods, the proposed algorithm has lower computational load. Simulation results confirm the effectiveness of the RV-ESPRIT.

In this paper, we proposed a method for radar modulation identification based on the measurement of inequality in the frequency domain. Gini's coefficient was used to exploit the inequality in the powers of spectral components. The maximum likelihood classifier was used to classify the detected radar signal into four types of modulations: unmodulated signal (UM), linear frequency modulation (LFM), non-linear frequency modulation (NLFM), and frequency shift keying (FSK). The simulation results demonstrated that the proposed method achieves an overall identification accuracy of 98.61% at a signal-to-noise ratio (SNR) of -6dB without a priori information such as carrier frequency, pulse arrival times or pulse width.

The problem of radar constant-modulus (CM) waveform design for the detection of multiple targets is considered in this paper. The CM constraint is imposed from the perspective of hardware realization and full utilization of the transmitter's power. Two types of CM waveforms — the arbitrary-phase waveform and the quadrature phase shift keying waveform — are obtained by maximizing the minimum of the signal-to-clutter-plus-noise ratios of the various targets. Numerical results show that the designed CM waveforms perform satisfactorily, even when compared with their counterparts without constraints on the peak-to-average ratio.

This paper presents a method to accelerate target recognition processing in advanced driver assistance systems (ADAS). A histogram of oriented gradients (HOG) is an effective descriptor for object recognition in computer vision and image processing. The HOG is expected to replace conventional descriptors, e.g., template-matching, in ADAS. However, the HOG does not consider the occurrences of gradient orientation on objects when localized portions of an image, i.e., a region of interest (ROI), are not set precisely. The size and position of the ROI should be set precisely for each frame in an automotive environment where the target distance changes dynamically. We use radar to determine the size and position of the ROI in a HOG and propose a radar and camera sensor fusion algorithm. Experimental results are discussed.

In this paper, we propose an efficient clutter suppression algorithm for automotive radar systems in iron-tunnel environments. In general, the clutters in iron tunnels makes it highly likely that automotive radar systems will fail to detect targets. In order to overcome this drawback, we first analyze the cepstral characteristic of the iron tunnel clutter to determine the periodic properties of the clutters in the frequency domain. Based on this observation, we suggest for removing the periodic components induced by the clutters in iron tunnels in the cepstral domain by using the cepstrum editing process. To verify the clutter suppression of the proposed method experimentally, we performed measurements by using 77GHz frequency modulated continuous waveform radar sensors for an adaptive cruise control (ACC) system. Experimental results show that the proposed method is effective to suppress the clutters in iron-tunnel environments in the sense that it improves the early target detection performance for ACC significantly.

The diffraction by a thin material strip is analyzed for the H-polarized plane wave incidence using the Wiener-Hopf technique together with approximate boundary conditions. An asymptotic solution is obtained for the case where the thickness and the width of the strip are small and large compared with the wavelength, respectively. The scattered field is evaluated asymptotically based on the saddle point method and a far field expression is derived. Scattering characteristics are discussed in detail via numerical results of the radar cross section.