Self-Supervised Learning for Enhancing Angular Resolution in Automotive MIMO Radars

A novel framework to enhance the angular resolution of automotive radars is proposed. An approach to enlarge the antenna aperture using artificial neural networks is developed using a self-supervised learning scheme. Data from a high angular resolution radar, i.e., a radar with a large antenna aperture, is used to train a deep neural network...

Radar Sensing in Healthcare: Challenges and Achievements in Human Activity Classification & Vital Signs Monitoring

Driven by its contactless sensing capabilities and the lack of optical images being recorded, radar technology has been recently investigated in the context of human healthcare. This includes a broad range of applications, such as human activity classification, fall detection, gait and mobility analysis, and monitoring of vital signs such as...

Continuous Human Activity Classification with Radar Point Clouds and Point Transformer Networks

Due to numerous benefits, radar is considered as an important sensor for human activity classification. The problem of classifying continuous sequences of activities of unconstrained duration has been studied in this work. To tackle this challenge, a radar data processing method utilizing point transformer networks has been proposed. The method...

Coevolution of machine learning and process-based modelling to revolutionize Earth and environmental sciences: A perspective

Machine learning (ML) applications in Earth and environmental sciences (EES) have gained incredible momentum in recent years. However, these ML applications have largely evolved in ‘isolation’ from the mechanistic, process-based modelling (PBM) paradigms, which have historically been the cornerstone of scientific discovery and policy support....

Roadmap on signal processing for next generation measurement systems

Signal processing is a fundamental component of almost any sensor-enabled system, with a wide range of applications across different scientific disciplines. Time series data, images, and video sequences comprise representative forms of signals that can be enhanced and analysed for information extraction and quantification. The recent advances in...

Designing Depression Screening Chatbots

Advances in voice recognition, natural language processing, and artificial intelligence have led to the increasing availability and use of conversational agents (chatbots) in different settings. Chatbots are systems that mimic human dialogue interaction through text or voice. This paper describes a series of design considerations for...

Radar sensing for human healthcare: Challenges and results

In this paper, radar sensing in the domain of human healthcare is discussed, specifically looking at the typical applications of human activity classification (including fall detection), gait analysis and gait parameters extraction, and vital signs monitoring such as respiration and heartbeat. A brief overview of open research challenges and...

Advancing ecohydrology in the 21st century: A convergence of opportunities

Nature-based solutions for water-resource challenges require advances in the science of ecohydrology. Current understanding is limited by a shortage of observations and theories that can further our capability to synthesize complex processes across scales ranging from submillimetres to tens of kilometres. Recent developments in environmental...

LQG and Gaussian process techniques: For fixed-structure wind turbine control

Wind turbines are growing bigger to becomemore cost-efficient. This does increase the severity of the vibrations that are present in the turbine blades, both due to predictable effects like wind shear and tower shadow, and due to less predictable effects like turbulence and flutter. If wind turbines are to become bigger and more cost-efficient,...