In this paper, a multi-temporal analysis of polarimetric synthetic aperture radar (Pol-SAR) data over the sandbank and oyster farm area is presented. Specifically, a four-component scattering model, being able to identify single bounce, double bounce, volume, and helix scattering power contributions, has been employed to retrieve information. Decomposition results of a time series RADARSAT Pol-SAR images acquired over the western Taiwan coast indicate that the coastal tide level plays a key role in the sandbank and oyster farm monitoring. At high tide levels, the underlying sandbank creates a shallow area with an increased roughness of the above sea surface, leading to an enhanced surface scattering power as compared to the ambient water. Contrarily, at low tide levels, the exposed sandbank appears to be a smooth scatterer, generating decreased backscattering power than the surrounding area. On the other hand, the double-bounce scattering power is shown to be highly correlated with the tide level in the oyster farms due to their vertical structures. This also demonstrates a promising potential of the four-component scattering power decomposition for coastal tide level monitoring applications.

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.

This paper proposes a method to detect buildings and houses whose walls are not parallel to Synthetic Aperture Radar (SAR) flight path. Experimental observations show that it is difficult to detect these targets because of small backscattering characteristics. The detection method is based on the correlation coefficient in the circular polarization basis, taking full advantage of Polarimetric SAR (POLSAR) data. Since the correlation coefficient is real-valued for natural distributed targets with reflection symmetry and for non-natural targets orthogonal to illumination direction, and it becomes a complex number for non-natural targets aligned not orthogonal to radar Line-Of-Sight (LOS), the value seems to be an effective index for detection of obliquely aligned non-natural targets. The detection results are shown using the X-band Polarimetric and Interferometric SAR (Pi-SAR) single-path data set in conjunction with other polarimetric indices.

In this paper, we propose a simple algorithm for detecting a vehicle trapped in flooded urban area by using quad-polarimetric SAR data. The four-component scattering power decomposition and phase difference of HH-VV co-pol ratio are effectively used in the proposed algorithm. Here we carry out polarimetric scattering measurement for a scaled vehicle model surrounded by two buildings model in an anechoic chamber, to acquire the quad-polarimetric SAR data. It is confirmed from the results of the image analysis for the measured SAR data that the proposed algorithm for vehicle detection works well even under severe environment where the vehicle is set in the shadow of the building and/or the alignment of the vehicle or the buildings is obliquely oriented to direction of the radar line of sight.

High resolution direction-of-arrival (DOA) estimation algorithm for array antennas becomes popular in these days. However, there are several error factors such as mutual coupling among the elements in actual array. Hence array calibration is indispensable to realize intrinsic performance of the algorithm. In the many applications, it is preferable that the calibration can be done in the practical environment in operation. In such a case, the incident wave becomes coherent multipath wave. Calibration of array in the multipath environment is a hard problem, even when DOA of elementary waves is known. To realize array calibration in the multipath environment will be useful for some applications even if reference signals are required. In this report, we consider property of reference waves in the multipath environment and derive a new calibration technique by using the multipath coherent reference waves. The reference wave depends on not only the DOA but also complex amplitude of each elementary wave. However, the proposed technique depends on the DOA only. This is the main advantage of the technique. Simulation results confirm the effectiveness of the proposed technique.

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.

In general, dynamic channel assignment has a better performance than fixed channel assignment in a cellular mobile communication system. However, it is complex to control the system and a lot of equipments are required in each cell when dynamic channel assignment is applied to a large service area. Therefore, it is effective to limit the size of the service area in order to correct the defects of dynamic channel assignment. So, we propose an application of dynamic channel assignment to a part of a service area when fixed channel assignment is applied to the remaining part of the area. In the system, the efficiency of channel usage in some cells sometimes becomes terribly low. The system has such a problem to be improved. We show that the rearrangement of the channel allocation is effective on the problem.

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.

An FM-CW radar system for the detection of objects buried in sandy ground is explored and is applied to a field measurement. The key factors for underground FM-CW radar performance are the center frequency and bandwidth determining the depth at which the radar can detect targets and the resolution in the range direction. In order for FM-CW radar sounding, two ridged horn antennas are employed in the system, which are operative in the frequency range of 250-1000MHz. The impedance matching to the ground is optimized by measuring the echo strength from a fixed target as a function of the spacing interval between the antenna aperture and the ground surface. It is shown that the radar with an output power of 18dBm could detect a metallic plate (30100cm) and a pipe (10cmφ) buried at the depth of 1.2m. Also the synthetic aperture technique together with an averaging and subtracting method produced fine image in shallow region up to 100cm in the sandy ground.

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.