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The extensive deployment of wind farms has significantly impacted the detection capabilities of space–air bistatic radar (SABR) systems. Although space–time adaptive processing techniques are available, their performance is significantly degraded, and even unable to suppress clutter. This paper explores the geometric configuration of the SABR system and the selection of detection areas, establishing a space–time clutter model that addresses the effects of wind turbine clutter (WTC). Expressions for spatial and Doppler frequencies have been derived to deeply analyze the characteristics of clutter spreading. Building on this, the paper extends two-dimensional space–time data to three-dimensional azimuth–elevation–Doppler data. It proposes a three-dimensional space–time multi-beam (STMB) strategy incorporating the Ordering Points to Identify the Clustering Structure (OPTICS) clustering algorithm to suppress WTC effectively. This algorithm selects WTC samples and applies OPTICS clustering to the clutter-suppressed data to achieve this effect. Simulation experiments further verify the effectiveness of the algorithm.

The unmanned aerial vehicle (UAV)-borne video synthetic aperture radar (SAR) possesses the characteristic of having high-continuous-frame-rate imaging, which is conducive to the real-time monitoring of ground-moving targets. The real-time imaging-processing system for UAV-borne video SAR (ViSAR) requires miniaturization, low power consumption, high frame rate, and high-resolution imaging. In order to achieve high-frame-rate real-time imaging on limited payload-carrying platforms, this study proposes a miniaturization design of a high-integration UAV-borne ViSAR real-time imaging-processing component (MRIPC). The proposed design integrates functions such as broadband signal generation, high-speed real-time sampling, and real-time SAR imaging processing on a single-chip FPGA. The parallel access mechanism using multiple sets of high-speed data buffers increases the data access throughput and solves the problem of data access bandwidth. The range-Doppler (RD) algorithm and map-drift (MD) algorithm are optimized using parallel multiplexing, achieving a balance between computing speed and hardware resources. The test results have verified that our proposed component is effective for the real-time processing of 2048 × 2048 single-precision floating-point data points to realize a 5 Hz imaging frame rate and 0.15 m imaging resolution, satisfying the requirements of real-time ViSAR-imaging processing.

The UAV-borne video SAR (ViSAR) imaging system requires miniaturization, low power consumption, high frame rates, and high-resolution real-time imaging. In order to satisfy the requirements of real-time imaging processing for the UAV-borne ViSAR under limited memory and parallel computing resources, this paper proposes a method of embedded GPU-based real-time imaging processing for the UAV-borne ViSAR. Based on a parallel programming model of the compute unified device architecture (CUDA), this paper designed a parallel computing method for range-Doppler (RD) and map drift (MD) algorithms. By utilizing the advantages of the embedded GPU characterized with parallel computing, we improved the processing speed of real-time ViSAR imaging. This paper also adopted a unified memory management method, which greatly reduces data replication and communication latency between the CPU and the GPU. The data processing of 2048 × 2048 points took only 1.215 s on the Jetson AGX Orin platform to form a nine-consecutive-frame image with a resolution of 0.15 m, with each frame taking only 0.135 s, enabling real-time imaging at a high frame rate of 5 Hz. In actual testing, continuous mapping can be achieved without losing the scenes, intuitively obtaining the dynamic observation effects of the area. The processing results of the measured data have verified the reliability and effectiveness of the proposed scheme, satisfying the processing requirements for real-time ViSAR imaging.

The non-stationary clutter of space-based early warning radar (SBEWR) is more serious than that of airborne early warning radar. This phenomenon is primarily attributed to the Earth’s rotation and range ambiguity. The increase in clutter degrees of freedom (DOFs) and the significant widening of the clutter suppression notch are not conducive to moving target detection near main lobe clutter. This paper proposes an effective approach to suppress non-stationary clutter based on an interpulse multi-frequency mode for SBEWR. Using the orthogonality of the uniform stepping frequency signal, partial range ambiguity can be effectively suppressed, and the clutter DOFs will be reduced. Subsequently, joint pitch-azimuth-Doppler three-dimensional spacetime adaptive processing and slant range preprocessing are used to perform clutter suppression. This combination not only curtails the estimation error associated with the clutter covariance matrix but also enhances the overall detection capabilities of the system. The simulation results verify the effectiveness of the proposed approach.

The Gannan region is situated in Ganzhou City, Jiangxi Province, China, and has a complicated geological background. Seasonal droughts significantly jeopardize the water security of the local population. Groundwater is essential to alleviate the region’s water needs. In this research, the groundwater potential (GWP) of the Gannan region was assessed using the Soil and Water Assessment Tool (SWAT) and the Analytical Hierarchical Process (AHP). The groundwater recharge and rainfall estimated by the SWAT model exhibited notable inconsistencies regarding their spatial distribution. Eight groundwater potential assessment factors (lithology, fault density, land use, slope, convergence index, drainage density, rainfall, and groundwater recharge) were constructed by integrating remote sensing, geological, and SWAT output data. Two GWP maps were constructed by an overlay analysis based on the obtained weights using the AHP, with the rainfall and groundwater recharge assigned the same weight to calculate the GWP with the other six factors separately. Each map was split into five classes: excellent, good, moderate, poor, and very poor. Data from 23 wells and 42 springs were collected to validate the two maps by correlation analysis between the GWP and flow rates of wells and springs. The correlation analysis result indicates that the GWP calculated by the recharge (R2 = 0.8 and 0.74, respectively) is more accurate than the GWP calculated by the rainfall (R2 = 0.21 and 0.48, respectively) and can provide a theoretical basis for groundwater management and exploration in the area.

We introduce an approach for the direct measurement of the gravitational potential (GP) along the trajectory of a satellite, with a specific focus on Low-Earth Orbit (LEO) satellites. A LEO satellite communicates with several Geosynchronous Equatorial Orbit (GEO) satellites via frequency signal links. The GP difference can be measured in real-time using the gravitational frequency shift approach by equipping both LEO and GEO satellites with precise atomic clocks. Since the GP at the high orbits of the GEO satellites can be precisely determined by the present gravitational field model EGM2008, the GP along the LEO satellite’s trajectory can be determined. In this study, simulation experiments were conducted, featuring a GRACE-type satellite as the LEO satellite in communication with three equidistant GEO satellites. The results indicated that the accuracy of the GP measurements along the LEO satellite’s trajectory primarily depends on the precision of the onboard atomic clocks. Supposing optical atomic clocks attain an instability level of 1×10−17τ−1/2 (τ in seconds), we determined the GP distribution covered by the LEO satellite’s trajectories with 30-day observations. Then, we determined a gravitational field at the centimeter level based on the GP distribution. The GP data derived from the trajectory of a LEO satellite can be utilized to establish temporal gravitational fields, which have broad applications in different disciplines.

The International Association of Geodesy (IAG) aims to establish the International Height Reference System (IHRS) as one of its primary scientific objectives. Central to the realization of the IHRS is global vertical datum unification, which requires the connection of existing local vertical height reference systems (VHS) robustly and consistently. However, conventional methods are not suitable for estimating the offsets between two distant local height systems. In this paper, we propose a framework for connecting two local VHSs using ultraprecise clock frequency signal links between satellites and ground stations, referred to as the satellite frequency signal transmission (SFST) approach. The SFST approach allows for the direct determination of the geopotential and height differences between two ground datum stations without any location restrictions between the two VHSs. The simulation results show that the VHSs of China and the US can be unified with an accuracy of several centimeters, provided that the stability of atomic clocks used on-board the satellite and at on-ground datum locations reaches 4.8×10−17τ−1/2 for an averaging time τ (in seconds). We conclude that the SFST approach shows promise for achieving centimeter-level accuracy in unifying the global vertical height datum and represents a new paradigm for the realization of the IHRS.

The ground and sea clutter received by space-based early warning radar (SBEWR) has severely range ambiguous characteristics due to its platform location, and the non-stationary factor caused by Earth’s rotation makes the received clutter at different range ambiguous positions seriously broaden in the Doppler dimension. The complex clutter suppression performance of SBEWR obtained by traditional method is degraded significantly. To solve this problem and achieve better clutter suppression performance, a novel multi-domain adaptive processing method for clutter suppression is proposed in this paper. The proposed method introduced a range related signal processing domain based on conventional space–time domain by using frequency diverse array phase multiple-input multiple-output (FDA-Phase-MIMO) radar. In addition, a novel multi-domain joint dimensionality reduction structure was designed. The novel multi-domain joint adaptive processing using the proposed dimensionality reduction structure could not only obtain great clutter suppression performance of SBEWR, but also minimize the requirement of the number of selected auxiliary channels. Simulation examples show the effectiveness of the proposed method.

In 1954, the Yangtze River valley was hit by heavy precipitation anomalies, which caused large casualties and economic losses; however, systematic analyses of the causes are lacking. Adopting the latest national historical precipitation data collected by the China Meteorological Administration (CMA) and global sea surface temperature (SST) records, this retrospective study determined the spatial–temporal distribution characteristics of the precipitation in 1954 in Wuhan, a city situated in the Yangtze River valley. The results confirmed that the 1954 precipitation anomalies were characterized by a high volume and a long period of rainfall, plus numerous cloudbursts, with most of the precipitation concentrated during June and July at the mid- and low-Yangtze areas along the Yangtze. An El Niño event caused the West Pacific subtropical highs to continually move southward during the summer, creating a long-term rainband in the drainage basin. Moreover, the continued low SSTs in the Sea of Okhotsk generated an active blocking high that continuously brought high-latitude cold air into the south, boosting precipitation over the drainage basin. This study proposed a new causal model of summertime precipitation across the Yangtze River valley in 1954, whereby the unusual SST changes initially triggered atmospheric circulation anomalies, which caused the precipitation anomalies of 1954.

Mianyang City is located in the varied topographic areas of Sichuan Province in southwestern China and is characterized by a complex geological background. This area is prone to disasters and its varied topography is inconvenient for emergency water storage and supply. Groundwater is essential for alleviating the demand for water and post-disaster emergency water supply in this area. This study applied AHP to integrate remote sensing, geological and hydrological data into GIS for the assessment of groundwater potential, providing a plan for the rational exploitation of groundwater and post-disaster emergency water supply in the area. Nine factors, including the spring calibration related to groundwater, were integrated by AHP after multicollinear checks. As a result, the geology-controlled groundwater potential map was classified into five levels with equal intervals. All the results were validated using borehole data, indicating the following: the areas with yield rates of <1t/d·m, 1–20 t/d·m, and 20–400 t/d·m accounted for 2.66%, 36.1%, and 39.62%, respectively, whereas the areas with yield rates of 400–4000 t/d·m and >4000t/d·m accounted for only 20.88% and 0.75% of the overall area. The flexibility of this quick and efficient method enables its application in other regions with a similar geological background.

The spaceborne synthetic aperture radar (SAR) is quite powerful in worldwide ocean observation, especially for ship monitoring, as a hot topic in ocean surveillance. The launched Gaofen-3 (GF3) satellite of China can provide C-band and multi-polarization SAR data, and one of its scientific applications is ocean ship detection. Compared with the single polarization system, polarimetric systems can be used for more effective ship detection. In this paper, a generalized extreme value (GEV)-based constant false alarm rate (CFAR) detector is proposed for ship detection in the ocean by using the reflection symmetry metric of dual-polarization. The reflection symmetry property shows big differences between the metallic targets at sea and the sea surface. In addition, the GEV statistical model is employed for reflection symmetry statistical distribution, which fits the reflection symmetry probability density function (pdf) well. Five dual-polarimetric GF3 stripmap ocean data sets are introduced in the paper, to show the contrast in enhancement by using reflection symmetry and to investigate the GEV model fit to the reflection symmetry metric. Additionally, with the detection experiments on the real GF3 datasets, the effectiveness and efficiency of the GEV model for reflection symmetry and the model-based ocean ship detector are verified.