A general platform for millimeter wave synthetic aperture radiometers is introduced in this paper. The platform consists of hardware and simulation software, and has a flexible and open structure. Simulation and experiment results show the platform is suitable for simulation of synthetic aperture radiometer performance, algorithm performance, error influence on radiometer performance, and calibration performance. The platform can be used for radiometry simulation and design of synthetic aperture radiometers.

The mirrored aperture synthesis radiometer (MASR) has been proposed as a promising technique for Earth observation. However, considering the system imperfections, the cosine visibility function and the brightness temperature distribution do not constitute a cosine transform pair. The method to improve the quality of reconstructed brightness temperature images for a practical MASR has not yet been developed. In this article, the complete formulation of cosine visibility functions in a practical MASR is derived to better understand the measurement of a MASR with non-negligible effects of the system imperfections. The array factor of a practical MASR is analyzed. Then, the alias-free field of view (FOV) for a MASR is presented, and an iterative method is proposed to reconstruct the brightness temperature image in the alias-free FOV to reduce the computational burden. The numerical simulation and experimental results demonstrate that the proposed method can be applied to practical MASRs and that the reconstruction quality is significantly improved by the proposed method. Finally, the H-matrix inversion method is discussed as an alternative reconstruction method for a practical MASR. Compared with the H-matrix inversion method, the proposed method is more convenient for practical applications.

Rotating mirrored aperture synthesis (RMAS) has been proposed as a new method for high spatial resolution earth observation from the geostationary orbit. However, in previous researches, the reflector sizes are assumed to be infinite so that all antennas in the antenna array can receive the reflection signals. This assumption is obviously unacceptable in practical applications. How to estimate the reflector sizes is still a problem. In this letter, the principle of RMAS is briefly reviewed. Then, the reflector sizes of an RMAS radiometer are analyzed based on solid geometry, and detailed calculation formulae are derived. A numerical example is given for calculating the reflector sizes of an RMAS radiometer applied in the geostationary orbit.

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.

L-band Radio Frequency Interferences (RFIs) seriously contaminate remote sensing data. This poses a major challenge in processing microwave radiometric data and can substantially degrade the quality of the data. There is an urgent need to estimate RFI intensity in order to mitigate Gibbs errors caused by RFIs along the sidelobes. The traditional CLEAN algorithm is limited in its ability to account for the interactions among multiple RFIs, which results in biased intensity estimations. In this paper, the RFI brightness temperature model is modified to incorporate the interactions among multiple RFI sources. Building upon this modified model, we establish fundamental equation sets and propose a numerical solution method for calculating RFI intensity. Experiments and simulations based on Soil Moisture and Ocean Salinity (SMOS) data confirm that the method presented in this paper, which we have named MUSID, outperforms the traditional CLEAN algorithm.

For the tilted mirrored aperture synthesis (MAS), it can obtain different fields of view (FOV) by adjusting the inclination angle of the reflector. However, the tilted MAS microwave radiometer system is more complex. The antennas need to receive both direct signals and signals reflected by different reflectors, and reflector errors will affect the performance of the tilted MAS system. At present, there is no effective method to correct various errors in tilted MAS systems (especially reflector errors), which results in poor quality of brightness temperature (BT) image reconstruction for the tilted MAS. In this paper, we design a network to reconstruct BT images based on CNN and Transformer, and present a method to reconstruct the tilted MAS BT image by using this network. Based on the analysis of the FOV and spatial resolution of the tilted MAS system, a method for collecting the measured training dataset is presented. Using the measured training dataset for network training, the network learns the information of different errors in the tilted MAS system, including the error information of different reflectors and the error information of amplitude and phase. The simulation and experimental results show that the proposed method can obtain BT images with higher reconstruction quality than the impulse matrix reconstruction method.