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All Journal International Journal of Electrical and Computer Engineering Bulletin of Electrical Engineering and Informatics
Abd Rashid, Nur Emileen
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Computer Science & IT Electrical & Electronics Engineering

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Human movement detection and classification capabilities using passive Wi-Fi based radar Razali, Hidayatusherlina; Abd Rashid, Nur Emileen; Nasarudin, Muhammad Nazrin Farhan; Ismail, Nor Najwa; Ismail Khan, Zuhani; Enche Ab Rahim, Siti Amalina; Megat Ali, Megat Syahirul Amin; Zakaria, Nor Ayu Zalina
International Journal of Electrical and Computer Engineering (IJECE) Vol 14, No 3: June 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v14i3.pp3545-3556

Abstract

Human detection and classification via Wi-Fi transmission have received a lot of attention in recent years as crucial facilitators in security and human-computer interaction (HCI). The passive Wi-Fi radar (PWR) system used by previous researchers applied cross-ambiguity function (CAF) and CLEAN algorithms to process the detected signals. This paper explores the feasibility and viability of a PWR system in detecting and classifying human movements without utilizing CAF and CLEAN algorithms. The movements are performed by four participants but with comparable body sizes and heights. Three daily human movements are investigated namely walking, bending, and sitting, with each participant performing each movement 24 times, providing a total of 96 samples per activity. The system is evaluated based on the consistency of the signal pattern in a frequency domain and the percentage accuracy is assessed using an artificial neural network (ANN) classifier and trained using a leave-one-out cross-validation (LOOCV) method. The frequency domain results reveal that the signals are consistent, with no noticeable variations or changes in the voltage intensity or shape of the main lobe. The classification of the movements shows that the classifier has an overall accuracy of 97.6%.
Spectral estimator effects on accuracy of speed-over-ground radar Mohd Shariff, Khairul Khaizi; Zainuddin, Suraya; Abdul Aziz, Noor Hafizah; Abd Rashid, Nur Emileen; Zalina Zakaria, Nor Ayu
International Journal of Electrical and Computer Engineering (IJECE) Vol 12, No 4: August 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v12i4.pp3900-3910

Abstract

Spectral estimation is a critical signal processing step in speed-over-ground (SoG) radar. It is argued that, for accurate speed estimation, spectral estimation should use low bias and variance estimator. However, there is no evaluation on spectral estimation techniques in terms of estimating mean Doppler frequency to date. In this paper, we evaluate two common spectral estimation techniques, namely periodogram based on Fourier transformation and the autoregressive (AR) based on burg algorithm. These spectral estimators are evaluated in terms of their bias and variance in estimating a mean frequency. For this purpose, the spectral estimators are evaluated with different Doppler signals that varied in mean frequency and signal-to-noise ratio (SNR). Results in this study indicates that the periodogram method performs well in most of the tests while the AR method did not perform as well as these but offered a slight improvement over the periodogram in terms of variance.
Clutter evalution of unmanned surface vehicles for maritime traffic monitoring Nadiy Zaiaami, Muhammad; Abd Rashid, Nur Emileen; Ismail, Nor Najwa; Ibrahim, Idnin Pasya; Enche Ab Rahim, Siti Amalina; Zalina Zakaria, Nor Ayu
Bulletin of Electrical Engineering and Informatics Vol 13, No 3: June 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v13i3.6836

Abstract

A traditional maritime radar system is utilized for ship detection and tracking through onshore transmitters and receivers. However, it faces challenges when it comes to detecting small boats. In contrast, unmanned surface vehicles (USVs) have been designed to monitor maritime traffic. They excel in detecting vessels of various sizes and enhance the capabilities and resolution of maritime radar systems. Nevertheless, just like conventional radar systems, USVs encounter difficulties due to environmental interference and clutter, affecting the accuracy of target signal detection. This research proposes a comprehensive numerical assessment to tackle the clutter issue associated with USVs. This involves gathering clutter signal data, performing numerical analysis, and employing distribution fitting techniques that leverage mathematical distributions to unravel data complexity. The root mean square error (RMSE) is applied in this analysis to validate the efficacy of the distribution model. The results of this study aim to formulate a clutter model that can enhance radar performance in detecting small vessels within cluttered environments.
Co-Authors Abdul Aziz, Noor Hafizah Enche Ab Rahim, Siti Amalina Ibrahim, Idnin Pasya Ismail Khan, Zuhani Ismail, Nor Najwa Megat Syahirul Amin Megat Ali Mohd Shariff, Khairul Khaizi Nadiy Zaiaami, Muhammad Nasarudin, Muhammad Nazrin Farhan Razali, Hidayatusherlina Zainuddin, Suraya Zakaria, Nor Ayu Zalina Zalina Zakaria, Nor Ayu