The microwave imager combined active and passive (MICAP) serves as a primary payload for the Chinese Ocean Salinity Mission (COSM). Its passive component employs 1-D synthetic aperture radiometry, while the active component utilizes digital beamforming scatterometry. This integrated design, which marks itself as the first spaceborne application, enables multifrequency active-passive observation on multisea surface parameters within a unified payload, yet simultaneously poses challenges for high-accuracy brightness temperature (TB) reconstruction. The conventional G-matrix method's accuracy is fundamentally constrained by underdetermination and disparities among element antenna patterns-a limitation notably observed in the SMOS mission. While deep learning approaches demonstrate efficacy in simulations, they encounter a "Sim-to-Real" gap arising from deviations between idealized training data and actual observations, primarily due to the imperfect characterization of on-orbit antenna patterns. To address these, this article proposes a high-accuracy physics-guided residual U-Net, named inverse fast Fourier transform (IFFT)-ResUNet, combined with a fine-tuning strategy. The proposed architecture embeds the IFFT as a physical prior to guide the data-driven reconstruction. To bridge the visibility functions (VFs) inconsistency, a transfer learning strategy is adopted, adapting the model from general imaging laws learned on simulations to real measurements. End-to-end simulation results demonstrate that the proposed method achieves high-precision reconstruction with a root-mean-square error (RMSE) of 0.14 K. Furthermore, the physics-guided fine-tuning strategy exhibits exceptional data efficiency, achieving performance comparable to or better than training from scratch using only 10% of the training data, thereby drastically reducing the dependency on extensive on-orbit calibration samples. Validation using the MICAP airborne flight campaign data over Laizhou Bay confirms the method's practical feasibility and lays a foundation for its subsequent application to spaceborne observations.

Ground-based scatterometers are widely used for quantitative microwave backscattering measurements in soil moisture retrieval, vegetation monitoring, and satellite scatterometer validation. However, low-cost software-defined radio (SDR) transceivers provide limited instantaneous bandwidth, making it difficult to transmit and process signals with bandwidths on the order of hundreds of MHz for fine range resolution, especially for systems requiring real-time onboard processing. To address this problem, this paper presents a vehicular, fully polarimetric, SDR-based scatterometer that achieves an equivalent wideband response by sequentially transmitting adjacent narrow subbands and coherently synthesizing them onboard. To enable real-time operation on a resource-limited field-programmable gate array/system-on-chip (FPGA/SoC) platform, we adopt a frequency-domain synthesis-pulse-compression pipeline that avoids interpolation and eliminates repeated matched filtering across subbands. A slot-based online phase calibration is performed within the settling window after each fast lock to estimate and compensate random local oscillator (LO) phase offsets, preserving coherent stitching. In addition, pulse repetition within each subband and coherent accumulation are integrated to improve the signal-to-noise ratio (SNR) under real-time throughput constraints. A Zynq-based implementation demonstrates deterministic onboard range-profile output, with a minimum processing latency of about 1.57 ms per frame. Loopback and outdoor experiments validate the equivalent 200 MHz bandwidth (five 40 MHz subbands), achieving approximately 0.75 m resolution and yielding sidelobe metrics consistent with the designed windowing, including a peak sidelobe ratio (PSLR) of −27.43 dB and an integrated sidelobe ratio (ISLR) of −12.38 dB. Field scans over farmland further show consistent σ0 trends across incidence angle and azimuth, indicating reliable onboard quantitative backscattering measurement. These results demonstrate that the proposed method provides a feasible solution for deterministic real-time equivalent wideband scatterometry on a low-cost SDR platform.

A high-gain, low-sidelobe, dual-polarized Cassegrain antenna working at W-band (95 GHz) is presented for airborne cloud radar application. The offset Cassegrain antenna is used to avoid the obstruction of secondary reflecting surface. A W-band corrugated feed and orthogonal mode coupler (OMT) are designed and simulated. The simulated results show that low return loss and high port isolation are reached by the two ports of OMT. The Cassegrain antenna was computed by physical optics (PO) theory. The simulated results show that high gain of 48.9 dB, very low side lobe level of -31 dB and low cross polarization level of -36.2 dB are achieved by the computed results. The proposed Cassegrain antenna is very suitable for airborne cloud radar system.

Hyperspectral microwave radiometer is a new type of passive microwave remote sensor for observing middle and upper atmospheric temperature, humidity, trace gas, and other parameters such as winds. The digital spectrometer, which allows the fine sampling of the spectral lines, is the core component of the radiometer. In this article, we propose the design and implementation of a new type of wideband, real-time channelized digital spectrometer, which realizes the core base-64 real-time complex fast Fourier transform (FFT) algorithm and channelization algorithm by improving the filter bank, 128-channel parallel processing of FFT and complex number processing. The digital spectrometer has a sampling rate of 20 Gsps, a quantization bit number of 8 bits, and an input bandwidth of 10 GHz, which realizes the spectrum analysis of 4096 channels. Then, an observation test was carried out using a V-band ground-based microwave radiometer equipped with the 10-GHz spectrometer, and the atmospheric temperature profile was successfully measured from the surface to the stratosphere. The retrieval results were compared with the ERA5 reanalysis data and the L2 temperature products of the FY-3-D/MWTS-MWHS and Aura/microwave limb sounder (MLS), with a better consistency, which proved the application and potential of the new wideband digital spectrometer in the atmospheric sounding.

This article presents the design and implementation of a high-precision digital beamforming scatterometer, exploring its key technologies, which include digital beamforming, real-time amplitude and phase correction, and on-orbit real-time signal processing. Leveraging these technologies, the Haiyang-4A (HY-4A) scatterometer can flexibly adjust beam direction electronically, achieving a wide scanning range and efficient observational capabilities without changing the satellite's flight path. To validate the scatterometer's performance, we conducted a series of rigorous tests, including microwave anechoic chamber tests, echo simulator joint tests, and airborne flight calibration experiments. The test results demonstrate that the HY-4A digital beamforming scatterometer achieves high accuracy and reliability in measuring sea surface backscatter coefficients, providing robust support for monitoring ocean salinity and surface characteristics.

Sea Surface Salinity (SSS) is a crucial parameter influencing ocean circulation and the global water cycle in global climate monitoring and oceanographic research. However, remote sensing of SSS is challenged by the impact of sea surface roughness on microwave radiation measurements. To enhance measurement accuracy, the Ocean 4A satellite is equipped with a digital beamforming scatterometer integrated with advanced active and passive microwave remote sensing instruments. This system provides timely sea surface roughness information through co-frequency observations, enabling real-time correction of radiometric measurement errors. In this study, we conduct an in-depth analysis of the on-orbit real-time signal processing technology of the spaceborne digital beamforming scatterometer, covering system architecture, real-time signal processing algorithms, and software optimization. The developed real-time signal processing algorithms demonstrate excellent performance, achieving high accuracy and reliability in data acquisition. Results from point target tests using a combined echo simulator and airborne calibration and validation confirm the effectiveness of the proposed methods. These findings lay a solid foundation for high-precision SSS measurements and showcase the potential of the Ocean 4A scatterometer in enhancing global climate monitoring capabilities.