Currently, many microwave radiometers have been successfully used in earth-observation and ocean-monitoring systems. In China, the scanning microwave radiometers (SMR) onboard the Haiyang-2A/2B (HY-2A/2B) satellites are multichannel radiometers capable of obtaining oceanic and atmospheric parameters, such as sea surface temperature (SST), sea surface wind speed (WS), water vapor (WV), and cloud liquid water (LW). As a successor to HY-2A, the HY-2B satellite was launched successfully on October 25, 2018. Compared with the HY-2A’s SMR, the HY-2B’s SMR is an improved microwave radiometer. This article is concerned with the instrument design of the HY-2B’s SMR and its improvements. The important improvements of the HY-2B’s SMR in regard to the feedhorns and cold-sky reflector (CSR) are verified, and the early in-orbit performance of the HY-2B’s SMR is evaluated. The results demonstrate that the HY-2B’s SMR exhibits an important improvement on the HY-2A’s SMR in terms of the quality of the brightness temperature (TB) products and calibration accuracy. The results also show that the HY-2B’s SMR has a good performance in terms of the global TB images and the retrieved products with a good agreement with the expectations.

The global sea surface salinity (SSS) can be accomplished by means of the L-band microwave radiometers from space, such as European Space Agencys SMOS (Soil Moisture and Ocean Salinity) and NASAs Aquarius/SAC-D. However, the Microwave Imaging Radiometer using Aperture Synthesis (MIRAS) in SMOS mission suffers from various errors and unexpected in-orbit phenomena, which degrade SSS accuracy. To further improve SSS accuracy, a Full Polarization Aperture Synthesis Microwave Radiometer (FPASMR) has been proposed for Chinas next generation Haiyang (HY) satellite program with two important improvements, which is composed by an L-band and X-band aperture synthesis radiometer (ASR) with two dimensions. One important improvement is that the sea surface roughness (SSR) and sea surface temperature (SST) are simultaneously measured by the full polarization X-band ASR, and another important improvement is that the microwave-optical receiving technology and in-orbit thermal control subsystem are employed to improve the stability of the FPASMR for reducing visibility phase errors. The system of the FPASMR is introduced in terms of L-band subsystem, X-band subsystem and the calibration subsystem. The main specifications of the FPASMR are analyzed in terms of field of view (FOV), angular resolution and radiometric sensitivity. In addition, the FPASMR calibration is also introduced. The FPASMR demonstrator has also been developed and a series of experiments is performed to assess the performance of the FPASMR demonstrator and the improvements in the FPASMR.

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.

The scanning microwave radiometer (SMR) is an important payload of the Haiyang-2B (HY-2B) satellite. The main reflector of the SMR has its own emission due to the imperfect reflector material and surface roughness; however, the reflector’s emissivity was not measured or estimated during the prelaunch phase. During the post-launch phase, it was discovered that the radiation contribution from the reflector changed with its position and over time. This phenomenon affected the accuracy of the calibration by a few Kelvins. This report analyzes the main reflector’s emissivity based on the observed results when HY-2B pitched-over to view the homogeneous and isotropic cold space. The emissivity of the reflector was approximately 3%, but owing to the larger field of view, the emissivity of 6.925 GHz and 10.7 GHz were not well assessed. After the radiation from the reflector has been corrected, the calibration error caused by the reflector’s emissivity is reduced.

Traditional specific emitter identification (SEI) systems often suffer significant performance degradation when confronted with previously unseen signal sources, underscoring the critical need for accurate detection and rejection of novel-class instances. To address this limitation, we propose an Integrated Deep Feature Representation and Isolation Forest (IDFIF) method for identifying novel-class radiation emitters. IDFIF begins by employing a convolutional neural network (CNN) to extract embedding features from raw In-phase/Quadrature (IQ) signals, enhancing inter-class separability while suppressing intra-class variability. These deep features are then used to construct an unsupervised iForest that learns the statistical distribution of known classes, enabling the effective detection of anomalies via a threshold-based scoring mechanism. Experiments conducted on a real-world ADS-B dataset demonstrate that the proposed method achieves a novel-class detection accuracy of over 94%, significantly outperforming comparative methods. Furthermore, the method exhibits low sensitivity to known-class samples, thereby ensuring robustness and generalization under open-set conditions. The proposed IDFIF method is promising for deployment in challenging electromagnetic environments.

The two-dimensional L-band Aperture Synthesis Microwave Radiometer (LASMR) aboard China's HY-4 ocean salinity satellite faces significant on-orbit calibration challenges, primarily from ionospheric disturbances, solar radiation, and radio frequency interference (RFI). To address this, we develop a novel screening framework that leverages the instrument's full-polarization measurement capability. The core of this framework is a new polarimetric ratio screening (PRS) method, which effectively identifies and filters data contaminated by ionospheric residuals, solar intrusion, and RFI. This technique is integrated with complementary screening criteria—including environmental thresholds, calibration cycle optimization, and geometric filters. On-orbit experiments demonstrate that the method significantly improves brightness temperature (TB) accuracy, reducing the root-mean-square (RMS) error to approximately 2.0 K in the alias-free field of view and 2.4 K in the extended alias-free FOV. These results conclusively validate the polarimetric ratio as a viable and effective technique for enhancing the external calibration of synthetic aperture microwave radiometers.