The Chinese ocean salinity satellite mission is currently undergoing development and rigorous testing. The satellite will be equipped with an L-band Y-shaped Synthetic Aperture Interferometric Radiometer (SAIR), which is similar to the highly regarded MIRAS. Leveraging lessons learned from the SMOS mission, significant emphasis has been placed on addressing Radio Frequency Interference (RFI). A pre-launch ground experiment has been conducted specifically for the SAIR payload of the Chinese ocean salinity satellite. This experiment aims to research and verify the efficacy of RFI processing algorithms. Notably, our observations indicate that the radiometer detects Gaussian thermal radiation noise, whereas RFIs consist of non-Gaussian signals, such as radar and wireless communication signals. This fundamental difference in signal types results in distinct system responses, leading to biases in RFI suppression, particularly for powerful RFI sources. To mitigate the suppression residuals of strong RFI, we have introduced an innovative adaptive channel response adjustment strategy. The core concept involves decomposing the covariance matrix to isolate the signal space dominated by intense RFI signals. By projecting the steering vector onto this signal space, we can accurately estimate the channel response of the RFI and make precise adjustments accordingly. Our experimental and simulation results are encouraging, demonstrating a marked improvement in RFI suppression effectiveness. This advancement is crucial for enhancing the accuracy and reliability of ocean salinity measurements from our satellite, ultimately contributing to a deeper understanding of our planet’s vital ocean ecosystems.

Sea surface salinity (SSS) is a fundamental parameter for understanding ocean phenomena and plays a vital role in studying global climate change and weather prediction models. Following the earlier launch of Soil Moisture and Ocean Salinity (SMOS), Aquarius, and Soil Moisture Active Passive (SMAP) satellites, the Chinese Ocean Salinity and Soil Moisture Mission (COSM) was successfully launched on November 14, 2024. The launched satellite is equipped with the 2-D L-band Aperture Synthesis Microwave Radiometer (LASMR) and the Microwave Imager Combined Active and Passive (MICAP) components to gather high-precision SSS information. This paper presents the Airborne LASMR (ALASMR), which features a Y-shaped two-dimensional synthetic aperture microwave radiometer and contains 11 antenna units with a unit spacing of 0.82λ. The ground test investigations of the ALASMR have been conducted to evaluate antenna patterns, test the sensitivity of receiving channels, and conduct ocean aviation experiments. To examine the flight observation, uniform salinity is assumed for the sea area obtained from the calibration platform of National Satellite Ocean Application Service (NSOAS) whereas the salinity gradient is taken for the Laizhou Bay area. The ALASMR exhibits enhanced imaging performance, with a spatial resolution of about 0.35 km and a width of about 1.24 km at the flight altitude of 1.2 km. The retrieval of SSS in the sea area of the ocean calibration platform is also demonstrated in this work. This indicates that ALASMR can reliably execute salinity observation of near-shore with high precision and provide a cross-calibration data source for COSM after its launch.

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.

For 1-D aperture synthesis (1-D AS) radiometers, truncated sampling occurs in the frequency domain due to the system baseline limitation. Therefore, there is an obvious Gibbs oscillation in the reconstructed image. To solve this problem, an imaging method based on a 1-D convolutional neural network (1-D CNN) is proposed in this article. Compared with deep learning methods based on 2-D convolutions, the 1-D convolution not only reduces the amount of computation but also produces further performance improvements. The input data of the network are the 1-D visibility function samples, and the output data are the 1-D brightness temperature (BT) samples. The network learns the mapping relationship from the training of the 1-D visibility function samples and 1-D BT samples to complete 1-D AS imaging without any prior knowledge. To verify the performance of this imaging method, simulations and experiments based on the airborne C-band 1-D microwave interferometric radiometer (ACMIR) system are implemented. The simulation and experimental results demonstrate that the proposed AS-CNN method achieves higher performance than the inverse fast Fourier transform (IFFT) method in terms of image quality and Gibbs phenomenon suppression. In the case of an antenna failure and missing baseline, the AS-CNN method proposed in this article can still obtain a BT image with high imaging quality, which shows that the robustness of the network is better than that of the IFFT method.

In this paper, Mirrored Aperture Synthesis with tilting reflectors (MAS-T) is proposed to improve spatial resolution with fewer antennas for passive microwave remote sensing. The principle of MAS-T is given. The initial experimental results demonstrate that MAS-T can achieve higher spatial resolution with the same antenna array compared with conventional aperture synthesis.

Mirrored aperture synthesis (MAS) has been proposed as a novel interferometry to achieve higher spatial resolution in passive microwave remote sensing. The phase and amplitude errors for MAS are a crucial problem that has yet to be analyzed. In this letter, a model for the phase and amplitude errors is established. A correction method based on an external source is proposed to correct the phase and amplitude errors. An analysis of the position of the external source is performed by computing its impact on the radiometric accuracy of a reference scene. The imaginary parts of the cross correlations for MAS are analyzed for the first time. Simulations and experiments are carried out to demonstrate the effectiveness of the correction method.

In this letter, 1-D mirrored aperture synthesis with two tilted reflectors (1-D MAS-T) is proposed to improve the spatial resolution of an antenna array without extending its size. The principle of 1-D MAS-T is given. The size of the reflector is analyzed, and detailed calculation formulae is derived. Numerical simulations and experiments are carried out to illustrate the performance of 1-D MAS-T. The results demonstrate that 1-D MAS-T can achieve a higher spatial resolution than conventional aperture synthesis with the same antenna array.

The medium- and large- scale global sea surface temperature (SSTs), which is an important ocean parameter, are mainly measured by the space-borne microwave radiometry. However, the resolution and sensitivity are greatly limited by antenna size, orbit altitude, and flight speed. In this paper, an airborne C-band one-dimensional (1-D) microwave interferometric radiometer (ACMIR) is developed to obtain the SSTs with a high resolution and sensitivity. The spatial resolution of the ACMIR ranges from 40.7m to 612m, corresponding to the flight height of 500m to 8000m, while the sensitivity varies from 0.25K to 0.36K, associating with the boresight to the edge of the field of view. In order to evaluate the performance of the ACMIR, an ocean aviation experiment was conducted in the coastal area of the Yellow Sea in September 2020. The land observation results indicate that typical ground objects can be clearly distinguished. Furthermore, thesea surface brightness temperatures acquired by the ACMIR are compared with the estimates based on the radiative transfer model, with SST retrieval error of 0.77°C. The ACMIR can offer a high-resolution and accuracy of SST especially in coastal areas, and can meet several application requirements related to SSTs.

Ship detection is important for a wide range of applications. In this article, an airborne passive interferometric microwave sensor (PIMS) is proposed as a powerful complementary tool for ship detection. The fundamental of ship detection by the airborne PIMS is introduced. A specification called “the detection factor” is addressed to quantitatively assess the performance of the airborne PIMS for ship detection. The detection probability is discussed and addressed based on the constant false-alarm rate (CFAR). Numerical simulations are performed to demonstrate the feasibility of ship detection by the airborne PIMS. The impacts of the atmosphere and the sea wind on the performance of the airborne PIMS for ship detection are also addressed in terms of theoretical analyses and numerical simulations. The airborne experiments are also carried out by an X-band PIMS to verify the practicability of ship detection by the airborne PIMS in a sunny weather and a cloudy weather. The data processing procedure and a ship detection algorithm in the experiments are introduced. The airborne experimental results reveal that the ships can be effectively detected and tracked by the airborne X-band PIMS in a sunny weather and a cloudy weather. It demonstrates the practicability of ship detection by the airborne PIMS. The ship detection probability is also analyzed, which agrees well with the theoretical detection probability.

In the aperture synthetic radiometer system, good correction of systematic errors is the precondition of high quality image. So far the calibration of the receiving channel errors has been down relatively well, however, the calibration of the antenna errors remains to be improved. The paper proposed an inorbit external calibration method for aperture synthetic radiometer using external points on the ground, and the method aimed at the antenna error. Simulation proved the accuracy and feasibility of the method, then the implementary scheme was discussed. The method is of significant referential value to the image quality improvement and the practical engineering realization.

L\X-band Full Polarization Aperture Synthesis Microwave Radiometer (FPASMR) is a 2-Daperture synthesis radiometer working at L and X-band with full polarization measurement for obtaining high precise measurement of sea salinity and soil moisture. In order to better verify the performance of the system and the validity of the calibration methods, the demonstrator prototype of FPASMR was used in the airborne calibration experiment. Because of the limit of the observation window, the aircraft and load balancing, the demonstrator of 19 X-band antennas Y-shaped array was chosen. This paper is going to show the results of experiment.

L\X-band Full Polarization Aperture Synthesis Microwave Radiometer (FPASMR) is a 2-D aperture synthesis radiometer working at L and X-band with full polarization measurement for obtaining high precise measurement of sea surface salinity. FPASMR consists of dual Y-shaped arrays containing 23 L-band antennas per arm plus one in the center in L-band array and the same numbers of X-band antennas in X-band array. The demonstrator prototype of FPASMR has been developed and the validation has also been fulfilled.

This paper briefly discusses the working principle of synthetic aperture microwave radiometer system. Through the system sensitivity and repeatability test, The sensitivity and repeatability of the system are obtained. Based on the test, a correction algorithm for calibration error of calibration network sensitivity and receiver repeatability is proposed, which can be used to calibrate the data in different environments on the satellite and provide the basis for the future onboard calibration.

Either soil moisture or ocean salinity plays important role in globe water cycle. They are key parameters for monitoring the globe climate change [1]. Aperture Synthesis Microwave Imaging Radiometer will measure global sea surface salinity with 50-km spatial resolution, and the average monthly salinity accuracy aims at 0.1 psu (parts per thousand). This requires the radiometer has long-term calibration stability of <0.3K over 30 days. A special research was developed to achieve this objective. The research has addressed several areas including noise diode sensitivity versus temperature, L-band low-noise receiver performance under different test conditions and some components characterization which used in the Radiometer. Many of the research results and the calibration methods have been used to help to improve the performance of the radiometer.

Correlation radiometer is the basic unit of interferometer or full polarization radiometer which can obtain the correlation of two receiving channels. The paper presents a novel receiving configuration of correlation radiometer using the digital signal processing to fulfill the IQ demodulation and acquire the band of application requirement exactly. This new receiving configuration can eliminate the quadrature errors which can simplify the calibration procedure and acquire exact receiving band which can improve the consistence of multiple parallel receiving channels. This novel receiving configuration which has been applied in L\X-band Full Polarization Aperture Synthesis Microwave Radiometer (FPASMR) establishes the basis of spaceborne engineering application in the future.

L\X-band Full Polarization Aperture Synthesis Microwave Radiometer (FPASMR) is a 2-D aperture synthesis radiometer which can measure the sea salinity and soil moisture. As a key component of FPASMR, the digital correlator has been introduced in this paper from three abstract: the system design, the hardware design and the test results of the demonstrator. The results demonstrate that the digital correlator referred in this paper can ensure the realtime signal sampling and processing of 140 ADC channels which meet the practical requirements.