This paper takes full advantage of polarimetric scattering parameters and total power to classify polarimetric SAR image data. The parameters employed here are total power, polarimetric entropy, and averaged alpha angle (alphabar). Since these parameters are independent each other and represent all the scattering characteristics, they seem to be one of the best combinations to classify Polarimetric Synthetic Aperture Radar (POLSAR) images. Using unsupervised classification scheme with iterative Maximum Likelihood classifier, it is possible to decompose multi-look averaged coherency matrix with complex Wishart distribution effectively. The classification results are shown using Pi-SAR image data set comparing with other representative methods.

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.

The Sinclair scattering matrix is defined in a fixed radar range. If a radar target extends in the range direction, the reflected signal or the compound scattering matrix will undergo interaction of multiple reflections. Since scattering matrix is subject to target parameters such as shape, size, orientation, material, and radar parameters as frequency, polarization, and incidence angle, it is difficult to specify a representative scattering matrix of a general target. Therefore we choose the simplest target, wire, and its scattering matrix to examine the effect of targets aligned in the range direction with respect to the compound scattering matrix. First, we present a simple formula for the compound scattering matrix of wires with the phase difference due to spacing. Then, we employed the FDTD method to examine the scattering phenomena, changing the spacing in the range direction. The FDTD result reveals that two wires can become sphere (plate) and dihedral corner reflector (diplane) component generators; and that four wires can become a good helix component generator. These phenomena are verified with a laboratory measurement. From the result, the target decomposition should be carefully carried out in terms of range. If a range resolution of a radar is not high enough, the scattering matrix of the desired target may be affected by the targets behind.

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.

This paper presents a three-dimensional polarimetric detection result of targets buried in snowpack by synthetic aperture FM-CW radar system. Since the FM-CW radar is suitable for short range sensing and can be equipped with fully polarimetric capability, we further extended it to a polarimetric three-dimensional SAR system. A field experiment was carried out to image and detect targets in a natural snowpack of 280 cm deep. The polarimetric detection and identification schemes are the polarimetric filtering, three-component decomposition, and the power polarization anisotropy coefficient. These approaches to acquired data show the usefulness of three-dimensional polarimetric FM-CW SAR system.

In this letter, a new formula is proposed for calculating the polarization entropy, based on the least square method. There is no need to calculate the eigenvalues of a covariance matrix as well as to use logarithms of values. So the time for computing the polarization entropy is reduced. Using polarimetric SAR data, the authors validate the effectiveness of the new formula.

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.

Tree canopies contain various scattering elements such as leaves, branches and trunks, which contribute to complex backscattering, depending on frequency and polarization. In this paper, we propose to use the polarimetric correlation coefficient for classifying trees, forests, and vegetations. The polarimetric correlation coefficient can be derived by the elements of Sinclair scattering matrix. Since the scattering matrix can be defined in any polarization basis, we examined the coefficient in the linear HV, circular LR, and optimum polarization bases. First, the change of correlation coefficient inside trees along the range direction is examined using small trees in a laboratory. The wider the range, the better the index. The coefficient defined in the LR polarization basis showed the largest change within tree canopy, which also contribute to retrieve scattering mechanism. Second, this index for discrimination is applied to polarimetric SAR data sets (San Francisco and Briatia area) acquired by AIRSAR and SIR-C/X-SAR. It is shown that polarimetric correlation coefficient in the LR basis best serves to distinguish tree types.

This paper examines polarimetric scattering characteristics caused by a dihedral corner reflector of finite size. The dihedral corner reflector is a basic model of double-bounce structure in urban area. The detailed scattering information serves the interpretation of Polarimetric Synthetic Aperture Radar (POLSAR) data analysis. The Finite-Difference Time-Domain (FDTD) method is utilized for the scattering calculation because of its simplicity and flexibility in the target shape modeling. This paper points out that there exists a stable double-bounce squint angle region both for perfect electric conductor (PEC) and dielectric corner reflectors. Beyond this stable squint angular region, the scattering characteristics become completely different from the assumed response. A criterion on the double-bounce scattering is proposed based on the physical optics (PO) approximation. The detailed analyses on the polarimetric index (co-polarization ratio) with respect to squint angle and an experimental result measured in an anechoic chamber are shown.

This paper presents a target location estimation method that can use a pair of leaky coaxial cables to determine the 2D coordinates of the target. Since convention location techniques using leaky coaxial cables can find a target location along the cable in 1D, they have been unable to locate it in 2D planes. The proposed method enables us to estimate target on a 2D plane using; 1) a beam-forming technique and 2) a reconstruction technique based on Hough transform. Leaky coaxial cables are equipped with numerous slots at regular interval, which can be utilized as antenna arrays that acts both as transmitters and receivers. By completely exploiting this specific characteristic of leaky coaxial cables, we carried out an antenna array analysis that performs in a beam-forming fashion. Simulation and experimental results support the effectiveness of the proposed target location method.

In this brief paper, we examine polarimetric scattering characteristics for understanding seasonal change of paddy rice growth by using quad-polarimetric synthetic aperture radar (SAR) data in the X-band. Here we carry out polarimetric scattering measurement for a simplified paddy rice model in an anechoic chamber at X-band frequency to acquire the the quad polarimetric SAR data from the model. The measurements are performed several times for each growth stage of the paddy rice corresponding to seasonal change. The model-based scattering power decomposition is used for the examination of polarimetric features of the paddy rice model. It is found from the result of the polarimetric SAR image analysis for the measurement data that the growth state of the paddy rice in each stage can be understood by considering the ratio of the decomposition powers, when the planting direction of the paddy rice is not only normal but also oblique to radar direction. We can also see that orientation angle compensation (OAC) is useful for improving the accuracy of the growth stage observation in late vegetative stage for oblique planting case.

The wavelet transform provides information both in the spatial domain and in the frequency domain because of its inherent nature of space-frequency analysis. This paper presents a classification result of synthetic aperture radar image obtained by JERS-1 based on the discrete wavelet transform. This paper points out that the wavelet analysis has yielded a fine result in texture classification compared to a conventional method with less computation time.

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 superresolution technique is considered for use in antenna gain measurements. A modification of the MUSIC algorithm is employed to resolve incident signals separately in the time domain. The modification involves preprocessing the received data using a spatial scheme prior to applying the MUSIC algorithm. Interference rejection in the antenna measurements using the fast Fourier transform (FFT) based techniques have been realized by a recently developed vector network analyzer, and its availability has been reported in the literature. However, response resolution in the time domain of these conventional techniques is limited by the antenna bandwidth. The MUSIC algorithm has the advantage of being able to eliminate unwanted responses when performing antenna measurements in situations where the antenna band-width is too narrow to support FFT based techniques. In this paper, experimental results of antenna gain measurements in a multipath environment show the accuracy and resolving power of this technique.

In this paper, we study on direction-of-arrival (DOA) estimation error reduction by Khatri-Rao (KR) product extended array in the presence of correlated waves. Recently, a simple array signal processing technique called KR product extended array has been proposed. By using the technique, degrees-of-freedom of an array can be easily increased. However, DOA estimation accuracy deteriorates when correlated or coherent waves arrive. Such highly correlated waves often arrive for radar application, hence error reduction technique has been desired. Therefore, in this paper, we propose a new method for error reduction preprocessing scheme by using N-th root of matrix. The N-th root of matrix has a similar effect to the spatial smoothing preprocessing for highly correlated signals. As a result, DOA estimation error due to signal correlation will be reduced. The optimal order of N depends on the data itself. In this paper, a simple iterative method to obtain adaptive N is also proposed. Computer simulation results are provided to show performance of the proposed method.

Much attention has recently been paid to direction of arrival (DOA) estimation using compressed sensing (CS) techniques, which are sparse signal reconstruction methods. In our previous study, we developed a method for estimating the DOAs of multi-band signals that uses CS processing and that is based on the assumption that incident signals have the same complex amplitudes in all the bands. That method has a higher probability of correct estimation than a single-band DOA estimation method using CS. In this paper, we propose novel DOA estimation methods for multi-band signals with frequency characteristics using the Khatri-Rao product. First, we formulate a method that can estimate DOAs of multi-band signals whose phases alone have frequency dependence. Second, we extend the scheme in such a way that we can estimate DOAs of multi-band signals whose amplitudes and phases both depend on frequency. Finally, we evaluate the performance of the proposed methods through computer simulations and reveal the improvement in estimation performance.

The MIMO technique can improve system performance of not only communication system but also of radar systems. In this paper, we apply the MIMO radar with enhanced angular resolution to the indoor location estimation of humans. The Khatri-Rao (KR) matrix product is also adopted for further angular resolution enhancement. We show that the MIMO radar with the KR matrix product processing can increase the number of virtual elements effectively with suitable element arrangement, hence higher angular resolution can be realized. In general, the KR matrix product processing is not suitable for coherent radar because of signal correlation. However, when targets signals have enough Doppler frequency differential against each other, this approach works well because the signals are decorrelated. In addition, Doppler filtering is introduced to remove unwanted responses of stationary objects which make human detection difficult with conventional methods. Computer simulation and experimental results are provided to show performance of the proposed method.

Antenna array is essential factor for multiple- input multiple-output (MIMO) wireless systems. Since the antenna array is composed of closely spaced elements, the mutual coupling among the elements cannot be ignored for the best performance of the array. Mutual coupling affects the MIMO channel, so the performance of a MIMO system, including channel capacity and diversity, varies with the degree of mutual coupling. The effect of mutual coupling is a function of the antenna load impedance. Therefore, designing an optimal element-matched array for a MIMO system requires consideration of the optimal matching condition for the array elements, the one that maximizes the channel capacity. We evaluated the effects of mutual coupling with various matching conditions in dipole arrays, and investigated their effects on the path correlation and channel capacity of MIMO systems. Simulation showed that the conventional conjugate matching of each element is still suitable for closely spaced elements except when the separation is about less than 0.1λ. Theoretical consideration of the received power of a closely-spaced-element array is also provided to show the effects of mutual coupling.

Direction of arrival estimation of coherent multipath waves by using superresolution technique often requires decorrelation preprocessings. Spatial smoothing preprocessings are the most popular schemes as the techniques. In mobile environment, position change of the target/transmitter often brings us decorrelation effect. In addition, multiple signals transmitted by an antenna array, such as a MIMO transmitter, can also cause the same effect. These effects can be categorized as the spatial smoothing preprocessing at the transmitter. In this paper, we analyze the spatial smoothing effect at the transmitter in the presence of multipath coherent waves. Theoretical and simulation results show that the spatial smoothing at the transmitter has a good feature in comparison with the conventional SSP at the receiving array. We also show that better decorrelation performance can be obtained when the SSPs at the transmitter and receiving array are applied simultaneously.

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.