A multiaspect synthetic aperture radar (SAR) is a novel imaging mode, which supports high spatial resolution, 3-D imaging, and automatic target recognition. However, traditional SAR imaging algorithms will not only degrade SAR images, but also lose significant angular information. Adaptive subaperture imaging algorithms can solve these problems. Distinguishing between anisotropic targets and isotropic targets and extracting the persistence angle are two main steps in these algorithms, both of which will be improved in this letter. First, a better characteristic coefficient, namely, amplitude statistical coefficient (ASC), is proposed to accurately distinguish between anisotropic targets and isotropic targets. Also, change-point detection is introduced to exactly extract the persistence angle. Besides, this letter attempts for the first time to quantitatively assess the characteristic coefficient indicating the anisotropy. For this purpose, two indicators are proposed: anisotropy discrimination index (ADI) and noise resistance range (NRR). The validity of this letter has been verified through the point target simulation data, the microwave anechoic chamber data, and the Gotcha public release data.

Monitoring rice growth from the space has aroused the interests of researchers from all over the world. Previous researches about rice phenology focused on dividing paddy rice into different phenological intervals, without knowing the specific date when a certain phenological stage starts. In this paper, different characteristics of the start of three important phenological stages are analyzed. A set of C-band SAR images acquired by SENTINEL-1 has been used to retrieve the start of three key phenological stages (leaf development, stem elongation and inflorescence emergence) of paddy rice. A dynamic time warping method was applied for the alignment of SAR time series curves, which are constructed using backscattering coefficients of different polarimetric channels (VH, VV and VH/VV ratio). Results show that all three kinds of time series curves show great potential in detecting start of leaf development of rice and VH/VV curves perform better in recognizing start of inflorescence emergence.

As a typical next-generation radar system, multistatic radar operates with distinct transmit and receive antennas, which can obtain three or more simultaneous echo datasets [1] . Such radar system has great potential in increasing the capability, reliability and flexibility of future SAR missions [2] . Recent years, various spaceborne multistatic SAR configurations have been introduced [3] , [4] , and the datasets are relatively scant due to the difficulty in constellation configurations. A multistatic radar system was developed in the anechoic chamber of Laboratory of Target Microwave Properties in 2021, which supposed to provide large amounts of radar cross section (RCS) and imaging data in the future. The amplitude of the RCS was calibrated using a metallic sphere, and the accuracy of the multistatic radar system was validated, which demonstrated the capability of the system.

Height is an important indicator of rice growth condition and phenological period. The Polarimetric SAR Interferometry (PolInSAR) has proven a valuable technique for providing structural metrics of vegetation. Anechoic chamber experiments, allowing a high flexibility in the configuration of operating parameters, such as frequency and baseline, is the most convenient and feasible way to study the potential of PolInSAR in rice height retrieval. In this study, the first PolInSAR measurements of a recently built anechoic chamber, The Laboratory of Target Microwave Properties (LAMP), were presented and analyzed versus frequency and baseline, and rice height was retrieved using the measurement data. The results confirm that LAMP has the ability of PolInSAR, and the height of rice in milk stage is retrieved more precisely in the frequency range of 2.5 to 4.7GHz, when the baseline is 0.5°. The results are expected to contribute to studying and to defining the operation modes for future SAR missions.

Bistatic radar system has attracted lots of studies on earth observation while lacking of data. An indoor bistatic system built in Laboratory of Target Microwave Properties (LAMP) was introduced, and the preliminary bistatic imaging experiments of a metallic cuboid by Inverse SAR (ISAR) was implemented. The characteristics of edge diffraction and specular reflection of electromagnetic wave could be observed clearly on the bistatic images, that highly consistent with the theory of electromagnetic wave. The results demonstrated the capability of this indoor bistatic system, promising to provide more bistatic data for further researches.

This paper mainly analyzes the change of InSAR phase with deformation and displacement by using multifunctional microwave indoor measurement. The experimental target adopts the high-voltage line tower component with strong scattering - metal tripod, which causes “deformation” by padding the bottom of the tripod by 5mm. According to the experimental principle of equal height interference fringes of electromagnetic waves, the measured data before and after deformation of the metal tripod are processed to obtain the phase data at different incident angles, The consistency between the InSAR phase change after phase unwrapping and the actual vertical deformation of the tripod is verified, which provides a basis for the accurate evaluation of InSAR crustal deformation monitoring, and has a good reference for the influence of different working parameters, especially the incident angle on InSAR results.

In this paper, the Laboratory of Target Microwave Properties (LAMP) was introduced and a full-parameters microwave properties measurement experiment for soil salinized process was demonstrated. In this experiment, the microwave characteristic of three targets of soil in different soil salinized stage were measured in a non-interference environment. The changes of soil salt content and distribution can be reflected in radar images. In the future, more experiments should be carried out to acquire and analyze the weak signal.

In this work, we apply the supervised descent method (SDM) to 3-D limited data inversion. In the measurement of the far field, the scattered field in 3-D measurement is small in magnitude and easily polluted by noise. Combining with limited observed data, the inversion problem is highly nonunique and ill-posed. To mitigate the ill-posedness, the model-based inversion is adopted by describing metallic targets based on prior information. Then, a series of generic descent directions is learned in the training stage iteratively using SDM. During inversion, the values of these model-based parameters are reconstructed directly using the learned directions. This approach is validated using both synthetic and experimental data. All simulations and experiments are conducted in a monostatic measurement setup to match real measurement conditions. The results show that by choosing proper prior information, the model-based SDM inversion can effectively compensate for the lack of data and achieve decent accuracy.

Measurement of microwave characteristics for targets in an anechoic chamber could improve the cognition of EM waves scattering mechanism. In this paper, a Full-Parameters Microwave Properties Measurement System (LAMP) was introduced, including the overall capabilities, the antenna RF system and etc. The Radar Cross Section (RCS) measurement and SAR images measured by LAMP, were demonstrated in this paper, when the frequencies of EM waves, the incidence angles and the azimuth angles varied It was verified that the accuracy of RCS of a metal sphere measured by LAMP was 1.09dBsm and 1.00dBsm in HH and VV polarization, respectively, comparing with Mie scattering computational results, when the frequency involved ranging from 2.5GHz to 18GHz.

This paper presents a global weighted least-squares (GWLS) optimization framework for polarimetric synthetic aperture radar (PolSAR) despeckling. GWLS is simpler than other optimization methods because it does not lead to complex optimization and iterative convergence problems. Solving the PolSAR despeckling problem based on GWLS is equivalent to solving nine sparse linear systems. First, the guidance image is constructed by the span image of the PolSAR data to calculate the five-point spatially inhomogeneous Laplacian matrix. Next, the weighted sum of the Laplacian matrix and an identity matrix is used to construct a coefficient matrix for the nine linear systems. Finally, each speckle-free channel of PolSAR data is reconstructed equally and globally by solving the linear systems with the same coefficient matrix. Filtering each element of the coherency matrix equally preserves the scattering property inherent in PolSAR data. The performance of the GWLS-based method is demonstrated by both simulated and real PolSAR data. Refined Lee filter, intensity-driven adaptive-neighborhood, improved sigma filter, and nonlocal pretest filter are used in qualitative and quantitative comparison. The experiments show that the proposed method can reach a good tradeoff between noise suppressing and detail preservation and has relatively high processing efficiency.

The main objective of this paper is to evaluate a time series of Sentinel-1A soil moisture product acquired from March 2015 to November 2016 using global passive ones: SMAP, SMOS and AMSR-2, together with ground measurements at ISMN site Dahra in Senegal. The retrieving algorithm is a LUT method based on simulated data cube using MIMICS and AIEM of VV polarization. Results show that ubRMSD and MAD of soil moisture estimated by 1km Sentinel-1A compared to ground measurements are both below 6%, and most of Pearson correlations between Sentinel-1A and global products are significant, which indicate the great potential of the application of Sentinel-1 data. Comparisons among the global products are also conducted to embody that L band is indeed more suitable for soil moisture estimation than C band.