Polarimetric SAR interferometry has been successful and attractive for forest parameters (tree height and canopy extinction) estimation. In this paper, we propose to use the ESPRIT algorithm to extract the interferometric phase of local scatterers with polarimetric and interferometric SAR data. Two or three local scattering waves can be extracted at each image patch when a fully polarimetric data set (HH, HV, VV) is available. Furthermore, the ESPRIT can estimate two dominant local scattering centers when only a dual polarimetric data set (e.g., VV and VH) is provided. In order to demonstrate effectiveness the proposed technqiue, we examined the relation between local scattering centers extracted by this method and complex coherence of the coherent scattering model for vegetation cover. The results show that the three-wave estimation can be more accurate than the two-wave case. The extracted interferometric phases with full and dual polarization data sets correspond to effective ground and canopy scattering centers. In this investigation, SIR-C/X-SAR data of the Tien Shan flight-pass are used.

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 presents an experimental result of polarimetric detection of objects buried in a sandy ground by a synthetic aperture FM-CW radar. Emphasis is placed on the reduction of surface clutter by the polarimetric radar, which takes account of full polarimetric scattering characteristics. First, the principle of full polarimetric imaging methodology is outlined based on the characteristic polarization states for a specific target together with a polarimetric enhancement factor which discriminates desired and undesired target echo. Then, the polarimetric filtering technique which minimizes a surface reflection is applied to detect a thin metallic plate embedded in a sandy ground, demonstrating the potential capability of reducing surface clutter which leads to an improvement of underground radar performance, and validating the usefulness of FM-CW radar polarimetry.

This paper presents a conifer and broad-leaf tree classification scheme that processes high resolution polarimetric synthetic aperture data above X-band. To validate the proposal, fully polarimetric measurements are conducted in a precisely controlled environment to examine the difference between the scattering mechanisms of conifer and broad-leaf trees at 15GHz. With 3.75cm range resolution, scattering matrices of two tree types were measured by a vector network analyzer. Polarimetric analyses using the 4-component scattering power decomposition and alpha-bar angle of eigenvalue decomposition yielded clear distinction between the two tree types. This scheme was also applied to an X-band Pi-SAR2 data set. The results confirm that it is possible to distinguish between tree types using fully polarimetric and high-resolution data above X-band.

A new superresolution technique is proposed for antenna pattern measurements. Unwanted reflected signals often impinge on the antenna when we measure it outdoors. A time-domain superresolution technique (a MUSIC algorithm) has been proposed to eliminate the unwanted signal for a narrow pass-band antenna. The MUSIC algorithm needs many snapshots to obtain a correlation matrix. This is not preferable for antenna pattern measurements because it takes a long time to obtain the data. In this paper, we propose to reduce a noise component (stochastic quantity) using the FFT and gating techniques before we apply the MUSIC. The new technique needs a few snapshots and saves the measurement time.

This paper describes an individual effect of soil moisture (mg) and surface roughness (hrms) of bare soil on the back scattering coefficient (σ0) at the X-band frequency. The study contributes to the design of an efficient microwave sensor. For this purpose, experimentally observed data was utilized to provide a composite σ0 equation model accounting for individual effect in regression analysis. The experimental data are compared with Small Perturbation Method. It is observed that the X-band gives better agreement up to incidence angle 50 for HH-polarization and 60 for VV-polarization as compared to the C-band. The lower angles of incidence give better results than the higher angles for observing mg at the X-band. The multiple and partial regression analyses have also carried out for predicting the dependence of scattering coefficient (σ0) on mg and hrms more accurately. The analyses suggest that the dependence of dielectric constant (i.e., mg) is much more significant in comparison to surface roughness at lower angles of incidence for both like polarizations. The results propose the suitable angle of incidence for observing bare surface roughness and soil moisture at the X-band. All these data can be used as a reference for satellite or spaceborne sensors.

SAR tomography is one of the methods that can perform 3-dimensional (3-D) imaging with multiple SAR datasets by using the Direction-of-arrival (DOA) estimation technique to estimate the height distribution of scatterers. Several reports on SAR tomography have been issued. However, experimental results of the SAR tomography by the Pi-SAR2-X, Japanese airborne SAR operated by the NICT, have not been reported yet. This paper is the first to report the results of experiments on the Japanese SAR platform. High-resolution 2-dimensional image can be obtained by the X-band SAR. However the image is generated by projecting 3-D objects in to a 2-D image plane, hence the target responses having the same slant-range distance locate at the same image pixel. This is well known as the layover problem. When we employ the X-band SAR tomography, we can obtain 3-D high-resolution images without the layover and also foreshortening problem. It will be useful for disaster damage monitoring, especially in urban areas. The main difficulty of the SAR tomography comes from the phase error caused by inaccurate flight-path data. In many cases, the dataset are preprocessed and compensated so as to parallelize their flight-path to carry out the phase calibration and the DOA estimation easily. However, it is often difficult for common users to obtain such preprocessed datasets. In this paper, we propose a simple calibration method by using a flat-surface area with known altitude. Experiments show that the proposed method is effective for the Pi-SAR2-X standard products without parallelized preprocessing or precise flight-path information.

A new superresolution technique is proposed for high-resolution estimation of the scattering analysis. For complicated multipath propagation environment, it is not enough to estimate only the delay-times of the signals. Some other information should be required to identify the signal path. The proposed method can estimate the frequency characteristic of each signal in addition to its delay-time. One method called modified (Root) MUSIC algorithm is known as a technique that can treat both of the parameters (frequency characteristic and delay-time). However, the method is based on some approximations in the signal decorrelation, that sometimes make problems. Therefore, further modification should be needed to apply the method to the complicated scattering analysis. In this paper, we propose to apply a time-domain null filtering scheme to reduce some of the dominant signal components. It can be shown by a simple experiment that the new technique can enhance estimation accuracy of the frequency characteristic in the Root-MUSIC algorithm.

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.

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.

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.

In this paper, we examine the polarimetric characteristics and the potential of the coherent decomposition in polarimetric synthetic aperture radar (SAR) interferometry. Coherent scattering decomposition based on the coherence optimization can separate effective phase center of different scattering mechanisms and can be used to generate canopy digital elevation model (DEM). This decomposition is applied to a simplified stochastic scattering model such as forest canopy. However, since the polarimetric characteristics are not well understood when the decomposition is carried out, we investigate its characteristics and potential using polarimetric entropy-alpha and three-component scattering matrix decomposition. The results show that the first and third components correspond to the lower and upper layer, respectively, in ideal case. In this investigation, SIR-C/X-SAR data of the Tien Shan flight-pass are used.

The periodicity of a target scattering matrix is studied when the target is rotated about the sight line of a monostatic radar. Except for the periodicity and invariance of the scattering matrix diag(a,a), it is proved that only helixes have the quasi-invariance, and that only N-targets have the quasi-periodicity, demonstrating that a target with some angle rotation symmetry also has the scattering matrix form diag(a,a). From this result, we conclude that it is impossible to extract the shape characteristics of a complex target from its scattering matrix or its Kennaugh matrix.

The multistage Wiener filter (MWF) outperforms the full rank Wiener filter in low sample support environments. However, the MWF adaptive process should be stopped at an optimum stage to get the best performance. There are two methods to stop the MWF adaptive process. One method is to calculate until the final full-stage, and the second method is to terminate at r-stage less than full-stage. The computational load is smaller in the latter method, however, a performance degradation is caused by an additional or subtractive stage calculation. Therefore, it is very important for the r-stage calculation to stop an adaptive process at the optimum stage. In this paper, we propose a simple method based on a cross-correlation coefficient to stop the MWF adaptive process. Because its coefficient is calculated by the MWF forward recursion, the optimum stage is determined automatically and additional calculations are avoided. The performance was evaluated by simulation examples, demonstrating the superiority of the proposed method.

Classification of terrain is one of the most important applications of Polarimetric Synthetic Aperture Radar (POLSAR) image analysis. This paper presents a simple method to classify terrain by the use of the correlation coefficients in the circular polarization basis together with the total power of the scattering matrix in the X-band. The reflection symmetry condition that the co-polarized and the cross-polarized correlations are close to zero for natural distributed scatterers is utilized to extract characteristic parameters of small forests or cluster of trees, and oriented urban building blocks with respect to the direction of the radar illumination. Both of these kinds of scatterers are difficult to identify in high resolution POLSAR images of complex urban areas. The indices employed here are the correlation coefficient, a modified coefficient normalized by the reflection symmetric conditional case, and the total power. It is shown that forest areas and oriented building blocks are easily detected and identified. The terrain classification yielded by these combinations is very accurate as confirmed by photographic ground truth images.

Synthetic aperture radar interferometry have been established in the past two decades, and used extensively for many applications including topographic mapping of terrain and surface deformation. Vegetation analysis is also a growing area of its application. In this paper, we propose an polarimetric SAR interferometry technique for interferometric phase extraction of each local scatterer. The estimated position of local scattering centers has an important information for effective tree height estimation of forest. The proposed method formulated for local scattering center extraction is based on the ESPRIT algorithm which is known for high-resolution capability of closely located incident waves. The method shows high-resolution performance when local scattered waves are uncorrelated and have different polarization characteristics. Using the method, the number of dominant local scattering centers and interferometric phases in each image pixel can be estimated directly. Validity of the algorithm is demonstrated by using examples derived from SIR-C data.

High-resolution Direction-of-Arrival (DOA) estimation techniques for antenna arrays have been widely desired in many applications such as smart antennas, RF position location, and RFID system. To realize high-resolution capability of the techniques, precise array calibration is necessary. For an array of single-mode elements, a calibration matrix derived by the open-circuit method is the simplest one. Unfortunately, calibration performance of the method is not enough for the high-reslution DOA estimation techniques. In this paper, we consider problems of the calibration matrix derived by the method, and show that errors in the matrix can be effectively removed by an optimal diagonal weight coefficient. In the proposed compensation technique, the number of newly introduced parameters, or unknowns, is only one for an array of the identical elements. Performance of the simple compensation technique is verified numerically and experimentally.

This paper examines seasonal change of the true water area of Lake "Sakata" by using Polarimetric Synthetic Aperture Radar (POLSAR) image analysis. The true water area includes not only the body of water but also the water area under emerged-plants and/or floating-leave plants in the lake. Statistical POLSAR image analysis is carried out for both X- and L-band data, based on the three-component scattering power decomposition method, where the decomposed components are surface scattering, double-bounce scattering and volume scattering components. From the results of the image analysis for the L-band POLSAR data acquired by Pi-SAR system, it is found that strong double-bounce scattering can be observed at the vicinity of the boundary region between water area and the surrounding emerged-plants area in early and middle summer. This phenomenon is an important factor for environmental monitoring. To verify the generating mechanism of the double-bounce scattering, the Finite-Difference Time-Domain (FDTD) polarimetric scattering analysis is also executed for a simplified boundary model, which simulates the local boundary region around the lake and consists of lots of vertical thin dielectric pillars on a perfect electric conductor (PEC) plate or on a PEC and dielectric hybrid plate. Taking into account the polarimetric feature of the double-bounce scattering obtained by both the FDTD and POLSAR image analyses, one can distinguish the actual water area from the bush of the emerged-plants around the lake, even when the water area is concealed by emerged-plants and/or floating-leave plants. Consequently, it is found that by using the proposed approach, one can estimate the true water area seasonal change for the lake and the surrounding wetland.

This paper presents a coherent decomposition scheme for polarimetric SAR data. Coherent decomposition means the decomposition is applied to a single or a few scattering matrix data. Based on the scattering matrix acquired with an FM-CW polarimetric SAR system, we have devised a simple decomposition technique using the coherency matrix for the purpose of identifying scatterers. This paper presents the decomposition technique and some decomposition results obtained by a fully polarimetric FM-CW radar. It is shown the scattering mechanisms are well recovered and the orientation angles of wire scatterer are precisely measured.