Recent climate change has brought extremely heavy rains and widescale flooding to many areas around the globe. However, previous flood prediction methods usually require a lot of computation to obtain the prediction results and impose a heavy burden...
Assessing sleep posture, a critical component in sleep tests, is crucial for understanding an individual’s sleep quality and identifying potential sleep disorders. However, monitoring sleep posture has traditionally posed significant challenges...
Precipitation nowcasting is extremely important in disaster prevention and mitigation, and can improve the quality of meteorological forecasts. In recent years, deep learning-based spatiotemporal sequence prediction models have been widely used in pr...
Precipitation nowcasting is a critical part of meteorological services and applications. Recently, mainstream research has been focused on adopting deep learning-based models to generate the predictions, yet existing deep learning models face challen...
Precipitation nowcasting, which involves the short-term, high-resolution prediction of rainfall, plays a crucial role in various real-world applications. In recent years, researchers have increasingly utilized deep learning-based methods in precipita...
Precipitation nowcasting by radar echo extrapolation using machine learning algorithms is a field worthy of further study, since rainfall prediction is essential in work and life. Current methods of predicting the radar echo images need further impro...
Weather radar, as a crucial component of remote sensing data, plays a vital role in convective weather forecasting through radar echo extrapolation techniques. To address the limitations of existing deep learning methods in radar echo extrapolation,...
As an important part of remote sensing data, weather radar plays an important role in convective weather forecasts to reduce extreme precipitation disasters. The existing radar echo extrapolation methods do not utilize the local natural characteristi...
Accurate short-term precipitation forecast is extremely important for urban flood warning and natural disaster prevention. In this paper, we present an innovative deep learning model named ISA-PredRNN (improved self-attention PredRNN) for precipitati...
Accurate echo classification is crucial for Millimeter-wave Cloud Radar (MMCR) data quality control. Existing approaches, however, often struggle to generalize across complex scenes or lack physical interpretability. Here we propose PhySNet, a physic...
To improve the unmanned aerial vehicle (UAV) detection and recognition rate based on radar detection technology, this paper proposes to take the radar range-Doppler planar graph that characterizes the echo information of the UAV as the input of the i...
Precipitation nowcasting is mainly achieved by the radar echo extrapolation method. Due to the timing characteristics of radar echo extrapolation, convolutional recurrent neural networks (ConvRNNs) have been used to solve the task. Most ConvRNNs have...
Accurate precipitation nowcasting is of great significance for flood prevention, agricultural production, and public safety. In recent years, spatiotemporal sequence models based on deep learning have been widely used for precipitation nowcasting and...
Machine learning (ML) algorithmic developments and improvements in Earth and planetary science are expected to bring enormous benefits for areas such as geospatial database construction, automated geological feature reconstruction, and surface dating...
In this study, detection and three-dimensional (3D) imaging of lightning plasma channels are presented using radar interferometry. Experiments were carried out in Leshan, China with a 48.2 MHz VHF radar configured with an interferometric antenna arra...
A new method is proposed for identifying ground clutter in single-polarization radar data based on the gated recurrent unit (GRU) neural network. This method needs five independent input variables related to radar reflectivity structure, which are th...
Wideband interference (WBI) can significantly reduce the image quality and interpretation accuracy of synthetic aperture radar (SAR). To eliminate the negative effects of WBI on SAR, we propose a novel end-to-end data-driven approach to mitigate WBI....
Hitchhiking bistatic radar system takes the direct wave signal that is transmitted by the non-cooperative radar emitter as the reference to detect and analyze the target echo signal, so as to realize the positioning and tracking of the target. This r...
This paper describes a method to provide quality control for radial velocity maps derived from radar echo voltage cross spectra measured by broad-beam high frequency radars. The method involves the comparison of voltage cross spectra measured at Dopp...
Ground clutter persists as residual stationary or recurrent echo in gridded reflectivity-only weather radar products, then is converted into spurious light rainfall when reflectivity is mapped to rain rate. This study presents an image-level quality...
To address the problem that conventional neural networks trained on radar echo data cannot handle the phase of the echoes, resulting in insufficient information utilization and limited performance in detection and classification, we extend neural net...
To address the challenge of detecting weak targets with small radar cross-sections (RCS), this work explores an integrated framework that leverages cross-level multimodal fusion of radar echoes. This method considers the target’s motion propert...
For high resolution imaging of a non-cooperative moving target, this paper proposes a sparse fusion imaging method. The imaging system contains two radar stations, which are separated by a certain bistatic angle and configured in a transmitter/receiv...
Pulse-echo sensing is the driving principle behind biological echolocation as well as biologically-inspired sonar and radar sensors. In biological echolocation, a single emitter sends a self-generated pulse into the environment which reflects off obj...
Ground clutter data are usually generated using a statistical model, but they cannot effectively reflect the spatial distribution characteristics of ground objects. It is important in practical projects to effectively predict ground clutter when terr...
In inverse synthetic aperture radar (ISAR) imaging, time-frequency analysis is the basic method for processing echo signals, which are reflected by the results of time-frequency analysis as each component changes over time. In the time-frequency map,...
Human activity recognition (HAR) is an important field in the application of millimeter-wave radar. Radar-based HARs typically use Doppler signatures as primary data. However, some common similar human activities exhibit similar features that are dif...
Short-term rainfall prediction by radar echo map extrapolation has been a very hot area of research in recent years, which is also an area worth studying owing to its importance for precipitation disaster prevention. Existing methods have some shortc...
Most HF radars operate in a monostatic or quasi-monostatic configuration. The collocation of transmit and receive facilities simplifies testing and maintenance, reduces demands on communications networks, and enables the use of established and relati...
High-frequency (HF) radar is a land-based instrument that can observe the radial distribution of oceanographic information, such as surface currents, wave heights, and wind directions. The first-order echo peak of the Doppler spectrum is often splits...
The integrated detection and jamming system employs integrated signals devoid of typical radar signal characteristics for detection and jamming. This allows for the sharing of resources such as waveform, frequency, time, and aperture, significantly e...
Transmitting orthogonal waveforms are the basis for giving full play to the advantages of MIMO radar imaging technology, but the commonly used waveforms with the same frequency cannot meet the orthogonality requirement, resulting in serious coupling...
Weather radar data can capture large-scale bird migration information, helping solve a series of migratory ecological problems. However, extracting and identifying bird information from weather radar data remains one of the challenges of radar aeroec...
With the development of human–computer interaction(s) (HCI), hand gestures are playing increasingly important roles in our daily lives. With hand gesture recognition (HGR), users can play virtual games together, control the smart equipment, etc...
Near-field millimeter-wave synthetic aperture radar (MMW-SAR) imaging provides high-resolution sensing capability for short-range target detection and characterization, but dense spatial sampling imposes considerable storage and processing burdens. T...
The problem that this paper is concerned with is High Frequency Surface Wave Radar (HFSWR) detection of desired targets against a complex interference background consisting of sea clutter, ionosphere clutter, Radio Frequency Interference (RFI) and at...
Super-resolution technology is considered as an efficient approach to promote the image quality of forward-looking imaging radar. However, super-resolution technology is inherently an ill-conditioned issue, whose solution is quite susceptible to nois...
The conventional back projection (BP) algorithm is an accurate time-domain algorithm widely used for multiple-input multiple-output (MIMO) radar imaging, owing to its independence of antenna array configuration. The time-delay curve correction back p...
Basal melt in the Dome A region will influence the deep-ice-core drilling at Kunlun Station. The melting point (wet bedrock) has a higher reflectivity than the surrounding area, which can be assessed using radar echoes from the bedrock. This paper us...
Taiwan is located at the edge of the northwestern Pacific Ocean and within a typhoon zone. After typhoons are generated, strong winds and heavy rains come to Taiwan and cause major natural disasters. This study employed fully convolutional networks (...
Foreign Object Debris (FOD) refers to any foreign material on the airfield that may injure and threaten the aircraft and airport system. Due to the complex background on the airfield pavement and weak target echoes in long-distance monitoring, it is...
The polar regions of Mars, including the South and North Poles, are crucial for studying Martian climate and geological history, as they contain the largest reservoir of subsurface water ice. This study introduces a new approach for reflector detecti...
Synthetic aperture radar (SAR) is often affected by other high-power electromagnetic devices during ground observation, which causes unintentional radio frequency interference (RFI) with the acquired echo, bringing adverse effects into data processin...
The task of precipitation nowcasting is significant in the operational weather forecast. The radar echo map extrapolation plays a vital role in this task. Recently, deep learning techniques such as Convolutional Recurrent Neural Network (ConvRNN) mod...
Reliable object detection in marine radar imagery is critical for maritime situational awareness, collision avoidance, and autonomous navigation. However, it remains challenging due to sea clutter, small targets, and interference from fixed navigatio...
We propose the use of Sentinel-1 Synthetic Aperture Radar (SAR) to provide a continuous and global monitoring of Radio Frequency Interferences (RFI) in C-band. We take advantage of the first 8–10 echo measures at the beginning of each burst, a 50–70...
When synthetic aperture radar (SAR) is conducting remote sensing or terrain mapping, its radar beam is inevitably occluded by the variations in the under-test topography. Although back-projection algorithm (BPA) can theoretically directly solve the i...
Airborne synthetic aperture radar (SAR) systems often encounter the threats of interceptors or electronic countermeasures (ECM) and suffer from motion measurement errors. In order to design and analyze SAR systems while considering such threats and e...
A compact 24 GHz FMCW radar board was evaluated for low-speed bicycle and small-vehicle sensing under strict memory and latency constraints. The hardware uses only 30 MHz modulation bandwidth, giving a nominal range resolution of about 5.0 m and a Do...
Previous ground-based, radar lunar imaging experiments have usually employed the Range-Doppler (RD) algorithm. This algorithm performs in the frequency domain and has high computational efficiency. However, in the case of a long coherent integration...
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