Road Surface Conditions Identification via H α A Decomposition and Its Application to mm-Wave Automotive Radar

A novel approach based on the entropy-alpha-anisotropy decomposition, also known as the $H\alpha A$ decomposition, for the recognition of road surface conditions using automotive radar is presented. To apply the $H\alpha A$ decomposition to automotive radar data, a dedicated signal processing pipeline has been developed. To investigate its...

Convergence of Scattering Parameters and HαA-Features of Road Surfaces

The convergence of polarimetric scattering parameters and H, α and A features of road surfaces under various conditions is analysed. It is shown that the number of radar measurements used for surface classification can be traded off with accuracy of the estimation of the mean value and covariance of S-parameters and H, α and A features....

Classification of Unmanned Aerial Vehicles (UAVs) Carrying Payloads with Polarimetric Radar

The ability of a fully polarimetric radar to discriminate between payloads carried by UAVs is demonstrated. A novel approach has been employed in the feature extraction algorithm, where features from individual and combined polarimetric channels are extracted for classification. Decision and ensemble fusions on the respective extracted features...

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 ...

Phase-based Classification for Arm Gesture and Gross-Motor Activities using Histogram of Oriented Gradients

Micro-Doppler spectrograms are a conventional data representation domain for movement recognition such as Human Activity Recognition (HAR) or gesture detection. However, they present the problem of time-frequency resolution trade-offs of Short-Time Fourier Transform (STFT), which may have limitations due to unambiguous Doppler frequency, and the...

Derivative Target Line (DTL) for Continuous Human Activity Detection and Recognition

In this paper, we investigate the classification of Activities of Daily Living (ADL) by using a pulsed ultra-wideband radar. Specifically, we focus on contiguous activities that can be inseparable in time and share a common transition, such as walking and falling. The range-time data domain is deliberately exploited to determine transitions from...

Urban Objects Classification With an Experimental Acoustic Sensor Network

This paper proposes feature extraction methods for object classification with passive acoustic sensor networks deployed in suburban environments. We analyzed the emitted acoustic signals of three object classes: 1) guns (muzzle blast); 2) vehicles (running piston engine); and 3) pedestrians (several footsteps). Based on the conducted analysis,...