Xiaohui Peng

Polarization-based material classification technique using passive millimeter-wave polarimetric imagery

The polarization properties of thermal millimeter-wave emission capture inherent information of objects, e.g., material composition, shape, and surface features. In this paper, a polarization-based material-classification technique using passive millimeter-wave polarimetric imagery is presented. Linear polarization ratio (LPR) is created to be a new feature discriminator that is sensitive to material type and to remove the reflected ambient radiation effect. The LPR characteristics of several common natural and artificial materials are investigated by theoretical and experimental analysis. Based on a priori information about LPR characteristics, the optimal range of incident angle and the classification criterion are discussed. Simulation and measurement results indicate that the presented classification technique is effective for distinguishing between metals and dielectrics. This technique suggests possible applications for outdoor metal target detection in open scenes.

RFI Mitigation in Aperture Synthesis Radiometers Using a Modified CLEAN Algorithm

For aperture synthesis radiometers, sparse samplings on the

An Imaging Method With Array Factor Synthesis in Synthetic Aperture Interferometric Radiometers

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Super-resolution RFI localization with compressive sensing in synthetic aperture interferometric radiometers

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SMOS RFI mitigation using array factor synthesis of synthetic aperture interferometric radiometry

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An adaptive sidelobe reduction method for the aperture synthesis radiometer

frequency plane cause undesirable sidelobes in the synthesized beam. Through these sidelobes, artificial sources emitting in the protected 1400-1427 MHz band contaminate the retrievals of the soil moisture and ocean salinity (SMOS) from MIRAS measurements. One effective way to correct the artificial interferences is to create a synthetic signal to compensate for the interferences impact. Based on the similar idea, in this letter, we describe an algorithm to compensate for the interferences impact by constructing an artificial signal as close as possible to the Gaussian beam. Numerical studies using synthetic and real SMOS data have been carried out to demonstrate that the proposed algorithm outperforms the classical CLEAN algorithm in correcting the impact of the extended radio frequency interference source.

Statistical regularization in synthetic aperture imaging radiometry

In this letter, an imaging method with array factor synthesis in synthetic aperture interferometric radiometers (SAIRs) is presented. The presented method can efficiently control the characteristics of the equivalent array factor of SAIR, such as null position and depth, sidelobe level, and so on, which will be beneficial in the presence of potential interferences, such as radio frequency interference. The method is based on the formulation that the SAIR array is equivalent to a phased array with a virtual antenna element located in each baseline. The previous built-in method and the conventional Fourier inverse method can be seen as a special case of the presented one. Numerical results validate the effectiveness of the presented method.

Fast RFI localization using virtual array in synthetic aperture interferometric radiometers

An accurate geolocation of the radio frequency interference (RFI) sources is significant to effectively switch off illegal transmitters. In this study, utilizing the sparse property of RFI in the observed scene, a super-resolution RFI localization method based on compressive sensing is presented in synthetic aperture interferometric radiometer (SAIR). Numerical results show the presented method can achieve an super-resolution RFI localization even when there are some missing data due to correlator or receiver failure.

An equivalent method of mixed dielectric constant in passive microwave/millimeter radiometric measurement

Radio frequency interference (RFI) is one of the most significant limiting factors in the retrieval of geophysical parameters measured by microwave radiometers. In this work, based on the measured visibilities of European Space Agencys Soil Moisture and Ocean Salinity (SMOS) mission, RFI mitigation results are presented using two approaches of array factor synthesis of synthetic aperture interferometric radiometry, i.e., RFI mitigation based on null control and low sidelobe synthesis. Results show that, for the approach of array factor synthesis with null control, the Gibbs-like contamination of weak and moderate RFIs can be mitigated very well, but it is not enough effective for strong RFIs because of instrument errors. On the other hand, for strong RFIs, at the cost of spatial resolution degradation which may be not critical for ocean salinity retrieval, result shows the approach of low sidelobe synthesis can be effective to mitigate the Gibbs-like contamination of strong RFIs.

RFI localization in synthetic aperture interferometric radiometers based on sparse Bayesian inference

ABSTRACT For an aperture synthesis radiometer, sidelobe artefact is an important problem in image reconstruction from finite visibility samples, especially, when there are strong point sources in the observed scene. The conventional Fourier inversion method with fixed window reduces sidelobe artefacts only at the expense of worsened mainlobe resolution. An adaptive beamforming method is developed in this letter as a means of reducing sidelobe artefacts while preserving the mainlobe resolution. The main idea behind this method is to form a scene-dependent weighting function for visibilities to minimize the energy received by the sidelobes. Numerical studies show that the proposed method has an improvement in reducing the sidelobe artefacts compared with the Fourier inversion method.