Bespoke Simulator for Human Activity Classification with Bistatic Radar

Radar is now widely used in human activity classification because of its contactless sensing capabilities, robustness to light conditions and privacy preservation compared to plain optical images. It has great value in elderly care, monitoring accidental falls and abnormal behaviours. Monostatic radar suffers from degradation in performance...

Radar-based Human Activities Classification with Complex-valued Neural Networks

Human activities classification in assisted living is one of the emerging applications of radar. The conventional analysis considers micro-Doppler signatures as the chosen input for feature extraction or deep learning classification algorithms, or, less frequently, other radar data formats such as the range-time, the range-Doppler, or the...

An LSTM Approach to Short-range personnel recognition using Radar Signals

In personnel recognition based on radar, significant research exists on statistical features extracted from the micro-Doppler signatures, whereas research considering other domains and information such as phase is less developed. This paper presents the use of deep learning methods to integrate both phase and magnitude features from range...

Shape feature aided target detection method for micro-drone surveillance radar

This paper presents a shape feature aided target detection method for micro-drone surveillance radar in order to mitigate the false alarms caused by the ground clutter. The method consists of a segmentation threshold selection method based on target measurements and a shape-feature extraction method based on Hu moments. Then the performance...

Elderly Care: Using Deep Learning for Multi-Domain Activity Classification

Nowadays, health monitoring issues are increasing as the worldwide population is aging. In this paper, the radar modality is used to classify with radar signature automatically. The classic approach is to extract features from micro-Doppler signatures for classification. This data representation domain has its limitations for activities...

Human activity classification with radar signal processing and machine learning

As the number of older adults increases worldwide, new paradigms for indoor activity monitoring are required to keep people living at home independently longer. Radar-based human activity recognition has been identified as a sensing modality of choice because it is privacy-preserving and does not require end-users compliance or manipulation. In...