A method for locating underground pipes from a pulse radar image is presented. The method employs the Laplacian of Gaussian filter to extract edges and employs the Hough transform to determine the depth of the pipes. A preliminary experiment showed its ability to detect deeply buried pipes with weak signal echoes.

A procedure for radar target discrimination is presented in this paper. The scheme includes an enhancement of late-time noisy scattering data based on a proposed signal processing algorithm and a decision procedure using previously known resonance annihilation filters. The signal processing stage is specifically adapted to scattering signals and makes use of the results of the singularity expansion method. It is based on a signal reconstruction using the SVD of a data matrix with a suitable choice of the number of singular vectors employed. To justify the inclusion of this stage, this procedure is shown to maintain the signal characteristics necessary to identify the scattered response. Simulation results clearly reveal a significant improvement due to the inclusion of the proposed stage. This improvement becomes especially important when the noise level is high or the targets to be discriminated (five regular polygonal loops) have a similar geometry.

This paper investigates a new class of pulse compression codes in which the phase rotates clockwise, and afterward, rotates anticlockwise (or rotates anticlockwise, and afterward, rotates clockwise). The spectrum energy then concentrates to the narrower band compared to the conventional code such as the Barker code and the pulse is compressed not to the width of a single subpulses, but to the width made by a collection of several subpulses. It is revealed that, using the new code, PSL (Peak Sidelobe Level) can be reduced to -25.6 dB (1/19) -25.1 dB (1/18), which is much smaller than using the Barker code and Frank code, when the compression ratio is about 10 or larger. Furthermore, the signal-to-noise ratio after compression, the appropriate IF bandwidth and Doppler tolerance for the new code are estimated by simulation.

This paper discusses the classification of targets buried in the underground by radar polarimetry. The subsurface radar is used for the detection of objects buried beneath the ground surface, such as gas pipes, cables and cavities, or in archeological exploration operation. In addition to target echo, the subsurface radar receives various other echoes, because the underground is inhomogeneous medium. Therefore, the subsurface radar needs to distinguish these echoes. In order to enhance the discrimination capability, we first applied the polarization anisotropy coefficient to distinguish echoes from isotropic targets (plate, sphere) versus anisotropic targets (wire, pipe). It is straightforward to find the man-made target buried in the underground using the polarization anisotropy coefficient. Second, we tried to classify targets using the polarimetric signature approach, in which the characteristic polarization state provides the orientation angle of an anisotropic target. All of these values contribute to the classification of a target. Field experiments using an ultra-wideband (250 MHz to 1 GHz) FM-CW polarimetric radar system were carried out to show the usefulness of radar polarimetry. In this paper, several detection and classification results are demonstrated. It is shown that these techniques improve the detection capability of buried target considerably.

This paper proposes two numerical methods to solve the optimal problem of contrast enhancement in the cross-pol and co-pol channels. For the cross-pol channel case, the contrast (power ratio) is expressed in a homogeneous form, which leads the polarimetric contrast optimization to a distinctive eigenvalue problem. For the co-pol channel case, this paper proposes a cross iterative method for optimization, based on the formula used in the matched-pol channel. Both these numerical methods can be proved as convergent algorithms, and they are effective for obtaining the optimum polarization state. Besides, one of the proposed methods is applied to solve the optimal problem of contrast enhancement for the time-independent targets case. To verify the proposed methods, this paper provides two numerical examples. The results of calculation are completely identical with other authors', showing the validity of the proposed methods.

In this paper, millimeter-wave radar cross section (RCS) characteristics for rough surface is investigated by means of an approximation method of the magnetic field integral equation and the feasibility of road condition sensing is discussed. The RCS measurement at 94 GHz is carried out in order to verify the numerical result, thereby the numerical results are in good agreement with the measured RCS. The dependence of RCS on the radar incidence angle and surface roughness is investigated where the cross-polarized RCS characteristic is also considered.

This paper shows an analysis of electromagnetic scattering from an open-ended rectangular cylinder for a plane wave incidence. The internal region is separated into two areas by additional plates to investigate the cavity resonance in detail. The applied numerical technique is the point matching method taking account of the edge condition. As numerical examples, the radar cross section is presented for E - polarized case and H - polarized case. Physical meanings of the computational results are discussed with a view to the contribution of the iris.

In the ITS (Intelligent Transport Systems), it is an essential condition (mixed environment) that vehicles that have communication equipment and vehicles that do not have it simultaneously run in the same road. In this paper, a vehicular driving assistant system that is applicable to the mixed environment is proposed. The proposed system uses spread spectrum techniques and consists of several new systems such as a PN code assignment system, new vehicle position systems, and a vehicle map update system. In the proposed system, the wireless broadcast CDMA is used for inter-vehicle communications. This paper also shows preexaminations of the proposed system by using an autonomous traffic flow simulator including inter-vehicle communications. It is shown that the traffic safety can be improved by using inter-vehicle communications.

The phase and frequency commands of a rotating radar system, that utilizes the frequency scanning and phase shifters to steer the beam in the azimuth and elevation directions, respectively, are derived in terms of the angles of the ground based coordinate system. The frequency equation derived is approximated to a simple form to reduce the calculation time for real time multi-function radar systems. It is shown that the approximate frequency commands are in good agreement with the exact ones if the range of the azimuth scanning is not too wide.

A new radar system is presented, which consists of one main radar and cooperative plural transponders. The transponders are integrated in the respective retrodirective antennas which are arranged beyond the horizon in such a manner as they surround the main radar. An algorithm for determining the three-dimensional target position is given. Computer simulations have been made for different target positions by assuming measurement errors. A target whose monostatic radar cross section is small or has been specially reduced by absorbing materials could be detected by this system if it is properly constructed.

Huynen has already provided a method to decompose a Mueller matrix in order to retrieve detailed target information in a polarimetric radar system. However, this decomposition sometimes fails in the presence of small error or noise in the elements of a Mueller matrix. This paper attempts to improve Huynen's decomposition method. First, we give the definition of stable decomposition and present an example, showing a problem of Huynen's approach. Then two methods are proposed to carry out stable decompositions, based on the nonlinear least square method and the Newton's method. Stability means the decomposition is not sensitive to noise. The proposed methods overcomes the problems on the unstable decomposition of Mueller matrix, and provides correct information of a target.

Recently, studies and developments of Collision Warning System (CWS) have attracted widely a particular attention among various wave applications at 60 GHz frequency band. Major performance of the CWS is given by the maximum detection range, the minimum detectable width and accuracy of detection distance. Since the maximum detection range and the minimum detectable width depend on a size of a target, it is important to know Radar Cross Section (RCS) of the target. RCS data should be measured so-called far field condition (greater than a few hundreds meters), while CWS is usually used in the range of 20-100 m. Therefore, a measurement of the reflection characteristics in shorter distance should be necessarily known. In this study, we present reflection characteristics of a medium size truck and a passenger car measured in open field at 60 GHz frequency. It is concludingly described that the reflection characteristics of the passenger car and the medium size truck are 13-18 dBm2 and 15-32 dBm2, respectively, for a case of horizontal polarization.

This paper proposes and investigates a vehicular radar system that can measure the distance to, the relative speed of and the direction of arrival (DOA) of the reflected waves from multiple targets or vehicles using the direct-sequence spread spectrum (DS-SS) technique. In particular, we propose a DOA estimation scheme using a multi-beam antenna. In order to show that the proposed system can accurately measure the above mentioned quantities, the performance is evaluated numerically in a multipath environment. Moreover, optimal multi-beam pattern is derived to minimize error probability of DOA estimation.

This paper presents a method for land cover classification using the SIR-C/X-SAR imagery based on the maximum likelihood method and the polarimetric filtering. The main feature is to use polarimetric enhanced image information in the pre-processing stage for the classification of SAR imagery. First, polarimetric filtered images are created where a specific target is enhanced versus another, then the image data are incorporated into the feature vector which is essential for the maximum likelihood classification. Specific target classes within the SAR image are categorized according to the maximum likelihood method using the wavelet transform. Addition of polarimetric enhanced image in the preprocessing stage contributes to the increase of classification accuracy. It is shown that the use of polarimetric enhanced images serves efficient classifications of land cover.

A rigorous radar cross section (RCS) analysis is carried out for two-dimensional rectangular and circular cavities with double-layer material loading by means of the Wiener-Hopf (WH) technique and the Riemann-Hilbert problem (RHP) technique, respectively. Both E and H polarizations are treated. The WH solution for the rectangular cavity and the RHP solution for the circular cavity involve numerical inversion of matrix equations. Since both methods take into account the edge condition explicitly, the convergence of the WH and RHP solutions is rapid and the final results are valid over a broad frequency range. Illustrative numerical examples on the monostatic and bistatic RCS are presented for various physical parameters and the far field scattering characteristics are discussed in detail. It is shown that the double-layer lossy meterial loading inside the cavities leads to the significant RCS reduction.

Fractals provide a good description of natural scenes and objects based on their statistically self-similar property. They are also used to discriminate natural or man-made objects because natural objects have a better fitting to the fractional Brownian motion (fBm) model than artificial objects. Sea clutter as natural phenomena well fit to the fBm to induce little error. On the other hand, targets as man-made objects induce much more error because they frequently deviate from the fBm model. Therefore, the fractal error has a good characteristic to detect targets buried in clutter. We modified the fractal error defined by Cooper to be suitable for radar image processing. For the X-band radar image, the performance of our proposed method is comparable to that of the Cooper's method. For the millimeter wave (MMW) radar images, our method is better than the Cooper's one.

In this paper we propose a new far-field RCS prediction method using cylindrical or planar near-field RCS data. First we derive the relation between RCS and the scattering coefficient using physical optics technique. The far-field RCS prediction algorithm is obtained by approximating the relation using the condition of Fresnel region and the paraxial constraint of scanning angle in the case of cylindrical or planar scanning. Finally we predict the far-field RCS using measured or calculated near-field RCS data of the conducting rectangular prism or plate. The validity of the proposed algorithm is demonstrated.

One of the polarimetric radar applications is classification or identification of targets making use of the scattering matrix. This paper presents a decomposition scheme of a scattering matrix into three elementary scattering matrices in the circular polarization basis. The elementary components are a sphere, a diplane (dihedral corner reflector), and a helix. Since a synthetic aperture FM-CW radar provides scattering matrix through a polarimetric measurement, this decomposition scheme was applied to the actual raw data, although the matrix is resulted from a swept frequency measurement. Radar imaging experiments at the Ku band (14.5-15.5GHz) were carried out to obtain a total of 6464 scattering matrices in an imaging plane, using flat plates, corner reflectors and wires as elementary radar targets for classification. It is shown that the decomposition scheme has been successfully carried out to distinguish these targets and that the determination of rotation angle of line target is possible if the scattering matrix is classified as a wire.

For the completely polarized wave case, this paper presents the explicit formulae of the characteristic polarization states in the co-polarized radar channel, from which one can obtain the CO-POL Max, the CO-POL Saddle and the CO-POL Nulls in the Stokes vector form. Then the problem on the polarimetric contrast optimization is discussed, and the explicit formula of the optimal polarization state for contrast enhancement is presented in the Stokes vector form for the first time. To verify these formulae, we give some numerical examples. The results are completely identical with other authors', which shows the validity of the presented method.

A radio propagation experiment at the Okinawa Radio Observatory of the Communications Research Laboratory is investigating the feasibility of calibrating the spaceborne precipitation radar onboard the Tropical Rainfall Measuring Mission by using the path-averaged rainfall rate estimated from rain attenuation. Because this estimated rainfall rate has errors due to the spatial inhomogeneity of rainfall rate and the variability of raindrop size distribution, we used distrometer data to evaluate both of these errors by computer simulation.