Synthetic Aperture Interferometric Radiometer Research Articles

A Principal Component Analysis Perspective for RFI Mitigation in Synthetic Aperture Interferometric Radiometer

A Principal Component Analysis Perspective for RFI Mitigation in Synthetic Aperture Interferometric Radiometer

A MAP Approach With Huber-MRF for Synthetic Aperture Interferometric Radiometer

A MAP Approach With Huber-MRF for Synthetic Aperture Interferometric Radiometer

A Novel Distance Estimation Method for Near-Field Synthetic Aperture Interferometric Radiometer

The visibility samples generated by the synthetic aperture interferometric radiometer (SAIR) under near-field observation conditions contain information about the distance from the target to the instrument. This requires a precise understanding of the target–instrument distance to guarantee imaging quality in near-field SAIR applications. In this paper, we introduce a novel distance estimate approach for near-field SAIR systems, which achieves satisfactory imaging performance in the absence of prior information on target–instrument distance. First, we reformulate the signal model of near-field SAIR from the fractional Fourier transform (FRFT) perspective. This formulation ties the distance that is variable to the visibility function in a straightforward manner, offering an efficient solution for image reconstruction in near-field SAIR. Subsequently, we present an iterative strategy for target–instrument distance estimation based on simulated annealing (SA). In each iteration, the modified average gradient (MAG) of images reconstructed within the FRFT framework is evaluated, and based on the Metropolis criterion, the estimated target–instrument distance is optimally updated iteratively. Finally, the validity and effectiveness of the proposed distance estimation method for near-field SAIR imaging systems are demonstrated through numerical simulation and real experiments.

Target Imaging Using Compressed Sampling in Synthetic Aperture Interferometric Radiometer

The target imaging application is significant to various sensing systems, such as radiometers, radars, and infrared. However, high system complexity impedes the application of interferometric radiometers to target imaging tasks to some extent. Specifically for an <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">N</i> -element interferometric radiometer with aperture synthesis technique, complex correlators are of the order of O( <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">N</i> <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> ), giving rise to the great difficulty of system hardware implementation. In this paper, we propose a new compressed interferometric radiometer (CIR) concept for target imaging applications, which exploits the sparsity property of targets in the spatial domain. The CIR target imaging framework mainly adopts the compressive measurement method to acquire partial visibility function samples in the spatial-frequency domain via a proper sparse sampling pattern. Then, these partially observed visibility samples are inverted to image the target contrast information by sparse recovery methods. For the above image recovery process, we propose two novel algorithms named local regional information-based reweighted <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">l</i> 1-norm minimization (LRRL1) and local regional convolution-based reweighted <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">l</i> 1-norm minimization (LRCRL1). The experiments using simulated and real data demonstrate the validity and effectiveness of the proposed CIR target imaging framework, showing superiority in both imaging performance and system complexity compared with conventional algorithms used in interferometric radiometers.

A Coastal RFI Mitigation Method for Synthetic Aperture Interferometric Radiometer

This letter pays attention to the mitigation of the Radio Frequency Interference (RFI) sources located at coastal regions for Synthetic Aperture Interferometric Radiometer (SAIR). To remove an RFI at the visibility level, it will be necessary to estimate the Brightness Temperature (BT) of the point source, which is currently done by computing the median of the surrounded pixels to get the background BT, and subtracting it from the original contaminated BT. However, this strategy is based on the assumption that the background BT distribution around the RFI is flat, and this is not reasonable for those RFIs from coastal cities, and could result in estimation deviation. A robust RFI mitigation method is proposed without introducing complex computing. Instead of focusing only on the local area, the basic idea of our method is to step into the wide area, and minimize the overall fluctuation of the pixels affected by the RFI in the BT image. The method tests based on SMOS visibility samples validate the correctness of the developed method.

A Combined RFI Localization Algorithm of BT Image and Subspace Decomposition for Synthetic Aperture Interferometric Radiometer

Radio frequency interferences (RFIs) in the L-band heavily contaminate remote sensing data and bring many challenges to the product quality of synthesis aperture interferometric radiometers. Detecting and localizing RFIs is the urgent need for switching off these RFIs and conducting mitigation algorithms. The localization algorithm based on the brightness temperature (BT) image is limited by the resolution to separate closely spaced RFIs and achieve high localization accuracy in some cases. To achieve super-resolution, the MUSIC method using subspace decomposition technique is suggested. Nevertheless, when the BT image SNR is low, the power of RFI is insufficient to overwhelm the background scene, and the performance of the MUSIC algorithm is unsatisfactory. In this paper, a further improvement is proposed by combining BT image and subspace decomposition. In the BT image domain, background scene cancellation and RFI target enhancement are carried out for enhancing the SNR. In the frequency domain, the MUSIC algorithm is applied utilizing subspace-decomposition to achieve super-resolution localization. Experiments and simulations based on SMOS data validate that the method presented in this paper performs better than both the classical MUSIC algorithm and BT-based localization algorithm in low SNR cases.

Distance Adaptive Imaging Algorithm for Synthetic Aperture Interferometric Radiometer in Near-Field

Distance Adaptive Imaging Algorithm for Synthetic Aperture Interferometric Radiometer in Near-Field

Iterative Regularization Using an Acceleration Technique for Synthetic Aperture Interferometric Radiometer

Iterative Regularization Using an Acceleration Technique for Synthetic Aperture Interferometric Radiometer

A Fast Near-Field Image Reconstruction Algorithm via Band-Limited Filtering for Synthetic Aperture Interferometric Radiometer

A Fast Near-Field Image Reconstruction Algorithm via Band-Limited Filtering for Synthetic Aperture Interferometric Radiometer

A Near-Field Imaging Algorithm Based on Angular Spectrum Theory for Synthetic Aperture Interferometric Radiometer

For the near-field synthetic aperture interferometric radiometer (SAIR), the Fourier transform relationship between the visibility function and the near-field brightness temperature (BT) distribution is not valid. It is a challenging task for near-field SAIR imaging to realize very close-range accurate imaging with a large field of view (FOV). This article presents a new SAIR near-field imaging algorithm based on the angular spectrum theory to realize the passive millimeter-wave (PMMW) imaging, called synthetic-angular-spectrum imaging (SASI) algorithm. This SASI algorithm mainly addresses data samples of a 4-D visibility function acquired from planar arrays. First, we invert 4-D visibility samples into the angular spectrum domain via the Fourier transformation. The obtained angular spectrum data cannot be directly used to estimate the near-field BT distribution. Second, a dedicated phase factor compensation is adopted for handling this problem. The dimension-reducing accumulation is employed to generate the synthetic angular spectrum (SAS) of near-field BT distribution. Finally, we reconstruct the BT image by using the generated SAS data. Simulation and experiment results show that the presented SASI algorithm has the superiority on image reconstruction quality, especially for the off-axis regions, compared with the existing near-field SAIR imaging methods.

Fully Connected Imaging Network for Near-Field Synthetic Aperture Interferometric Radiometer

Fully Connected Imaging Network for Near-Field Synthetic Aperture Interferometric Radiometer

Adaptive L p Reconstruction Method for Synthetic Aperture Interferometric Radiometer

The brightness temperature reconstruction of synthetic aperture interferometric radiometers (SAIRs) is an underdetermined and ill-posed inverse problem. The classical Hilbert-space regularization methods have often the disadvantages of the over-smoothness effects and the oscillations. In this paper, an adaptive Lp reconstruction method in Lebesgue spaces is introduced to obtain the accurate brightness temperature map in SAIRs. The proposed approach can adaptively adjust the exponent p between 1.2 and 2 according to the region of the map to be re-constructed. The experimental results show that the Lp reconstruction method can effectively reduce over-smoothness and Gibbs oscillations, and better improve the accuracy of the inverse results, compared to the traditional minimum-norm and band-limited regularization methods.

A Novel Near Field Image Reconstruction Method Based on Beamforming Technique for Real-Time Passive Millimeter Wave Imaging

A Ka-band 1024-channel passive millimeter wave (PMMW) imager (BHU-1024) based on synthetic aperture interferometric radiometer (SAIR) technique has been developed by Beihang University for security screening. BHU-1024 uses linear phased array to obtain resolution in the horizontal direction and uses aperture synthesis to obtain resolution in the vertical direction. This imager is designed for detecting concealed weapons on the human body and operated under the near-field condition of the antenna array. Thus, the conventional direct Fourier imaging theory, which is based on the far-field approximation, can’t be applied any longer. In this paper, a novel near-field image reconstruction method based on the beamforming technique is proposed. In this method, we derive the near-field imaging formula by beamforming theory and demonstrate the feasibility of obtaining spatial brightness temperature distribution by beam focusing. In the design of the beamformer, we further optimize the weight vector to suppress the sidelobe levels of the synthesized beam. The results of simulation and measurement demonstrate that the proposed method is an advantageous, effective imaging method for near-field passive millimeter wave imaging. At present, the proposed method has been applied to the actual passive millimeter wave imaging system BHU-1024.

A Novel RFI Detection Method for Microwave Radiometers Using Multilag Correlators

Radio frequency interference (RFI) is an increasing problem in microwave radiometry, particularly for Earth observation, because the antennas are pointing toward the Earth. RFI has been observed at the L-band in European Space Agency’s (ESA’s) Soil Moisture and Ocean Salinity (SMOS) Earth Explorer mission, National Aeronautics and Space Administration’s (NASA’s) Soil Moisture Active and Passive (SMAP) and Aquarius missions, and Advanced Microwave Scanning Radiometer-Earth Observing System (AMSR-E) and WindSat missions at 10.7 and 18.7 GHz (Misra and de Matthaeis, 2014). Therefore, dedicated onboard systems are, nowadays, a must to detect and remove contaminated measurements, improving radiometric accuracy and increasing the spatial coverage. In this work, a novel detection technique, specially tailored for synthetic aperture interferometric radiometers (SAIRs), is proposed and its performance analyzed. It is based on the change of the shape of the cross correlation function at lags different from zero under the presence of RFI. The performance of the proposed technique is compared to other common RFI detection algorithms, and its limitations and advantages are discussed. Postcorrelation detection performance is found to outperform other commonly used algorithms, such as kurtosis. In addition, it presents some convenient properties for its practical application in correlation and real aperture radiometers.

Low- and Moderate-Level RFI Detection Using Point-Source Ripple for Synthetic Aperture Interferometric Radiometer

Finding out and turning off the radio-frequency interference (RFI) sources as many as possible is an important work for synthetic aperture interferometric radiometer (SAIR). While the impact of strong RFIs on reconstructed brightness temperature (BT) image is clearly observable, the presence of low- or moderate-level RFIs is often hard to be aware of, leaving the RFI detection and localization a difficult problem. In this article, an improved RFI detection method is proposed by making use of the point-source ripple to give prominence to the RFIs presented in the SAIR imagery. The method tests based on Soil Moisture and Ocean Salinity satellite (SMOS) visibility samples and the performance evaluations by numerical simulations validate the correctness and effectiveness of the developed method.

Unified Reciprocal Space Processing for Short-Range Active and Passive Imaging Systems

Large scale sensing systems increasingly operate in short-range geometries, providing three-dimensional imaging capabilities that leverage the large number of degrees of freedom of distributed arrays. The two most powerful modes of operation include active, multiple-input multiple-output arrays, in which an image is processed from signals measured using different pairs of transmitting and receiving antennas; and passive, synthetic aperture interferometric radiometer arrays, which can image using ambient, non-cooperative radiation by processing signals measured at different receiving antenna pairs. In this paper, we explore the analogy between these two imaging modes, and outline a generalized framework for analyzing these systems in the array near field. Focusing on the similarities between the formalisms describing the operation of generic active and passive systems, it is proposed, to our knowledge for the first time in the scientific literature, to adapt a Fourier-based imaging technique optimized for short-range active MIMO systems to passive technologies, interrogating the emissivity of a spatially distributed target. The systematic method presented in this paper provides a framework for characterizing and optimizing short range coherent or incoherent systems used in threat detection and non-destructive testing applications.

Phase and Amplitude Calibrations of Rotating Equispaced Circular Array for Geostationary Microwave Interferometric Radiometers— Theory and Methods

The calibration strategy for synthetic aperture interferometric radiometers based on noise injection has been successfully demonstrated in the Microwave Imaging Radiometer with Aperture Synthesis (MIRAS) instrument onboard the Soil Moisture and Ocean Salinity (SMOS) mission of the European Space Agency (ESA). With the emerging demands of increasing both array size and frequency bands, the internal calibration hardware becomes more difficult to implement. Although several external calibration methods have been proposed, the so-called phase ambiguity problem was not carefully considered. In this article, a novel calibration strategy for both phase and amplitude calibrations based on redundant space calibration is proposed, which utilizes the unique structure of equispaced circular array and rotational sampling strategy. The original irregular phase ambiguity degenerates to the fixed <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\pi $ </tex-math></inline-formula> -ambiguity, where only two possible solutions to phases are introduced. Both phase and amplitude of visibility can be simultaneously calibrated by the proposed strategy, and no cooperative calibration target is needed.

Geolocation of RFIs by Multiple Snapshot Difference Method for Synthetic Aperture Interferometric Radiometer

The presence of unauthorized radio frequency interference (RFI) sources seriously affects the retrieval of brightness temperature of a synthetic aperture interferometric radiometer (SAIR). Postobservation RFI geolocation is important for improving the RFI situation hereafter and mitigating the impact of the identified RFIs. Previous works have demonstrated the potential of using high-/super-resolution direction-of-arrival (DOA) estimation techniques to achieve accurate localization of RFI sources in SAIR imagery. In this article, a multiple snapshot difference method is proposed to further reduce the RFI source geolocation bias. The covariance matrices of the consecutive snapshots with power changed RFIs are picked out and subtracted to cancel out the background scene. A MUSIC-based DOA algorithm is developed. Numerical simulations validate the theoretical correctness and the practical effectiveness of the proposed method.

Synthesis of Large Alias-Free Field-of-View Linear Arrays for Synthetic Aperture Interferometric Radiometers

The alias-free field-of-view (AF-FOV) is inversely proportional to the spatial-frequency sampling spacing in the synthetic aperture interferometric radiometers. When the physical size of the antenna elements is large relative to the wavelength, the AF-FOV is limited. This article focuses on extending the AF-FOV from the perspective of array design. By introducing the sampling spacing-compression factor, we define a type of large AF-FOV linear array (LFOVLA) that can generate consecutive spatial-frequency samples with sampling spacing less than the minimum antenna spacing. A simulated annealing (SA)-based algorithm is presented to generate a double AF-FOV linear array (DFOVLA), which has the advantage of generating lower redundancy DFOVLA and reducing time cost compared with the previous method. A general pattern method is also proposed to seek a large DFOVLA directly. The DFOVLA configurations below 26 elements are given. The simulation results show that the DFOVLA has a larger AF-FOV than the traditional array in the synthetic aperture interferometric radiometers.

A New Passive Imaging Technique Based on Compressed Sensing for Synthetic Aperture Interferometric Radiometer

The synthesis aperture interferometric technology provides a promising passive imaging approach to the radiometer for reconstructing the brightness temperature distribution of the scene. However, the application of this technology may be limited by the large number of antennas, receivers, and analog-to-digital converters (ADCs) required in the radiometer. In order to reduce the complexity of the hardware requirements, a new passive microwave imaging technique based on compressed sensing (CS) is proposed in this letter. Different from the existing CS-based imaging methods that randomly select part of samples measured by all receivers, the proposed method develops a new practicable measurement matrix that employs the samples measured by partial receivers to recover the brightness temperature image. Numerical simulations and experiments are performed to demonstrate the effectiveness of the proposed method for reducing the hardware resources and the data amount while maintaining the image quality.