Research/Technical Note
Feasibility Study on Radar-based Human Activity Recognition
Taiwo Samuel Aina*
Issue:
Volume 13, Issue 4, August 2025
Pages:
143-153
Received:
19 February 2025
Accepted:
3 March 2025
Published:
4 July 2025
Abstract: The growing interest in employing radar for human activity recognition is driven by the exponential rise in the incidence and risk of falls associated with aging, compounded by diminished leg strength, prolonged medication side effects, visual impairments, and other variables that contribute to decreasing strength. In comparison to contact devices and other non-contact devices, radar exhibits considerable advantages in terms of non-contact capability, accuracy, resilience, detection range, and privacy security. Radar-based Human Activity Recognition (HAR) works by using a Doppler frequency shift to figure out what people are doing. This shift creates unique Doppler signatures. The Doppler frequency shift is when electromagnetic waves change their frequency and wavelength depending on how fast the observer is moving compared to the source. This paper presents Radar based human activity recognition based on a convolutional neural network. Specifically, this paper utilized public datasets available by University of Glasgow, United Kingdom. The radar utilizes Novelda's X4 system-on-chip (SoC), with an integrated receiver and transmitter antenna, providing very precise distance and motion measurements. The target was located 0.45 meters from the radar at the time of data collection. The investigation makes use of PyTorch to implement classification through CNN architectures. The CNN model demonstrates effective ability to detect human activities within radar-based RF images. Although the model proves resilient it requires a larger collection of labelled data to reach higher performance standards.
Abstract: The growing interest in employing radar for human activity recognition is driven by the exponential rise in the incidence and risk of falls associated with aging, compounded by diminished leg strength, prolonged medication side effects, visual impairments, and other variables that contribute to decreasing strength. In comparison to contact devices ...
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Research Article
High Performance Hexa Band Compact Microstrip Patch Antenna Design for Terahertz Applications
Issue:
Volume 13, Issue 4, August 2025
Pages:
154-167
Received:
21 May 2025
Accepted:
25 June 2025
Published:
15 July 2025
Abstract: Designing the multiband antenna presented considerable challenges, requiring meticulous optimization to ensure consistent performance across multiple frequency ranges. This research introduces an innovative rectangular microstrip patch antenna (RMPA) that operates as a hexa-band in the terahertz (THz) frequency spectrum. The antenna's compact physical dimensions are 56×64×3.3 µm³, and it is constructed using a Quartz (Fused) substrate with a dielectric constant (𝜀𝑟) of 3.75. The radiating patch and ground plane layers are made from copper. This antenna resonates at six distinct frequencies: 2.87 THz, 3.98 THz, 5.71 THz, 7.42 THz, 8.63 THz, and 9.49 THz. The bandwidths are 140 GHz, 130 GHz, 880 GHz, 310 GHz, 680 GHz, and 530 GHz; the efficiencies are 76.26%, 75.38%, 85.95%, 78.53%, 84.24%, and 78.62%; and gains are at 5.71 dBi, 5.46 dBi, 8.41 dBi, 7.41 dBi, 7.74 dBi, and 6.29 dBi at resonance frequency, respectively. Simulations performed using Computer Simulation Technology (CST) Software (version 2019) confirm the antenna’s high efficiency and gain. With its flexible design and verified performance, this antenna is well-suited for a wide range of wireless applications, including radar, space science, sensing, and high-speed communication.
Abstract: Designing the multiband antenna presented considerable challenges, requiring meticulous optimization to ensure consistent performance across multiple frequency ranges. This research introduces an innovative rectangular microstrip patch antenna (RMPA) that operates as a hexa-band in the terahertz (THz) frequency spectrum. The antenna's compact physi...
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