AIMC Topic: Radar

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Real-Time Object Detection and Classification by UAV Equipped With SAR.

Sensors (Basel, Switzerland)
The article presents real-time object detection and classification methods by unmanned aerial vehicles (UAVs) equipped with a synthetic aperture radar (SAR). Two algorithms have been extensively tested: classic image analysis and convolutional neural...

Human Being Detection from UWB NLOS Signals: Accuracy and Generality of Advanced Machine Learning Models.

Sensors (Basel, Switzerland)
This paper studies the problem of detecting human beings in non-line-of-sight (NLOS) conditions using an ultra-wideband radar. We perform an extensive measurement campaign in realistic environments, considering different body orientations, the obstac...

Space Target Classification Improvement by Generating Micro-Doppler Signatures Considering Incident Angle.

Sensors (Basel, Switzerland)
Classifying space targets from debris is critical for radar resource management as well as rapid response during the mid-course phase of space target flight. Due to advances in deep learning techniques, various approaches have been studied to classif...

Improving Radar Human Activity Classification Using Synthetic Data with Image Transformation.

Sensors (Basel, Switzerland)
Machine Learning (ML) methods have become state of the art in radar signal processing, particularly for classification tasks (e.g., of different human activities). Radar classification can be tedious to implement, though, due to the limited size and ...

Lean Neural Networks for Autonomous Radar Waveform Design.

Sensors (Basel, Switzerland)
In recent years, neural networks have exploded in popularity, revolutionizing the domains of computer vision, natural language processing, and autonomous systems. This is due to neural networks ability to approximate complex non-linear functions. Des...

LPI Radar Waveform Recognition Based on Neural Architecture Search.

Computational intelligence and neuroscience
In order to reach the intelligent recognition, the deep learning classifiers adopted by radar waveform are normally trained with transfer learning, where the pretrained convolutional neural network on an external large-scale classification dataset (e...

Specific Radar Recognition Based on Characteristics of Emitted Radio Waveforms Using Convolutional Neural Networks.

Sensors (Basel, Switzerland)
With the increasing complexity of the electromagnetic environment and continuous development of radar technology we can expect a large number of modern radars using agile waveforms to appear on the battlefield in the near future. Effectively identify...

Target Recognition of SAR Images Based on SVM and KSRC.

Computational intelligence and neuroscience
A synthetic aperture radar (SAR) target recognition method combining linear and nonlinear feature extraction and classifiers is proposed. The principal component analysis (PCA) and kernel PCA (KPCA) are used to extract feature vectors of the original...

Spatiotemporal modeling of land subsidence using a geographically weighted deep learning method based on PS-InSAR.

The Science of the total environment
The demand for water resources during urbanization forces the continuous exploitation of groundwater, resulting in dramatic piezometric drawdown and inducing regional land subsidence (LS). This has greatly threatened sustainable development in the lo...

Target Classification in Synthetic Aperture Radar Images Using Quantized Wavelet Scattering Networks.

Sensors (Basel, Switzerland)
The need to classify targets and features in high-resolution imagery is of interest in applications such as detection of landmines in ground penetrating radar and tumors in medical ultrasound images. Convolutional neural networks (CNNs) trained using...