Deep Learning-based identification of human gait by radar micro-Doppler measurements

For the first time identification of human individuals using micro-Doppler (m-D) features measured at X-band has been demonstrated. Deep Convolutional Neural Networks (DCNNs) have been used to perform classification. Inspection and visualization of the classification results were performed using Uniform Manifold Approximation and Projection ...

Use of Symmetrical Peak Extraction in Drone Micro-Doppler Classification for Staring Radar

The commercialization of drones has granted the public with unprecedented access to unmanned aviation. As such, the detection, tracking, and classification of drones in radars have become an area in high demand to mitigate accidental or voluntary misuse of these platforms. This paper focuses on the classification of drone targets in a safety...

Continuous Human Activity Classification from FMCW Radar with Bi-LSTM Networks

Recognition of human movements with radar for ambient activity monitoring is a developed area of research that yet presents outstanding challenges to address. In real environments, activities and movements are performed with seamless motion, with continuous transitions between activities of different duration and a large range of dynamic...

Radar and video multimodal learning for human activity classification

Camera systems are widely used for surveillance in the security and defense domains. The main advantages of camera systems are their high resolution, their ease of use, and the fact that optical imagery is easy to interpret for human operators. However, particularly when considering application in the defense domain, cameras have some...

Radar Micro-Doppler Patterns for Drone's Characterisation

Micro-Doppler patterns of multi-propeller drones measured by radar systems are widely used in the classification of different drones, since the micro-Doppler patterns illustrate the velocity and motion properties of the drones. However, on this topic, there are a few issues the current researches have not tackled yet, and these will be discussed...

Simulation of Radar Micro-Doppler Patterns for Multi-Propeller Drones

This paper presents a thin-wire electromagnetic (EM) model of multi-propeller drone that generates drone micro-Doppler pattern efficiently as a function of radar parameters and propeller properties. Experimental results of propeller micro-Doppler pattern measured in anechoic chamber was investigated and used to validate the results produced...

Radar micro-Doppler of Wind Turbines: Low-Frequency Polarimetric Extension of Simplified Analytical Model

A simplified polarimetric model for radar signal scattering on wind turbines (WT) is proposed, which can be used for interpretation of observation in time and Doppler domains. This model uses representation of real WT as slowly rotating linear wire structures. The earlier proposed model has been extended to more general cases of WT with...

Development of Advanced Model of Radar and Communication Signals Scattering on Wind Turbines

In the recent years, there has been an increase in the popularity of renewable energy sources. One such being the wind energy. With the development in the field of wind energy, the structure of the wind turbines (WT) has also increased. The huge wind turbine structure (WTS) and the wind farms, both offshore and onshore, has a strong impact on...

Radar micro-Doppler of wind turbines: Simulation and analysis using rotating linear wire structures

A simple electromagnetic model of wind-turbine's main structural elements as the linear wired structures is developed to simulate the temporal patterns of observed radar return Doppler spectra (micro-Doppler). Using the model, the micro-Doppler for different combinations of the turbines rotation frequency, radar pulse repetition frequency, and...

FMCW radar algoritme ontwikkeling

Dit document beschrijft de ontwikkeling van een detectie en classificatie algoritme voor een sensormodule. Deze sensormodule maakt gebruik van een radarmodule en een video camera. Dit project is uitgevoerd ten behoeve van het Bachelor afstudeerproject Electrical Engineering aan de TU Delft. Deze sensormodule had als doel het detecteren en...

Model-based Classification of Human Motion: Using a Particle Filter Approach

Automatic detection of humans is an important part of many security and surveillance applications. Automatic processing diminishes the effect of human errors on the detection and allows extensive analysis after detection. Radar has certain advantages for human detection because of its all-weather and day and night capability, as well the fact it...