Human Detection and Classification using Passive Forward Scattering Radar System at Different Places

Aziz, Noor Hafizah Abdul; Phalip, Liyana Nadhirah; Rahman, Nurul Huda Abd

doi:10.1007/978-981-15-0058-9_10

Cited by 2 publications

(3 citation statements)

References 8 publications

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“…The factors that affect the signal are the speed and the size of the object, and also the distance between the object to the receiver. This phenomenon is called the Doppler Effect [4]. Furthermore, passive FSR provides a lot of interesting features such as the generally simple hardware, an improved target radar cross section, a long coherent interval of the receiving signal, protection from stealth technology and possible operation using non-cooperative transmitter [5], [6].…”

Section: Introductionmentioning

confidence: 99%

LTE-based passive forward scattering radar for drone detection and classification

Aziz

Fodzi

Shariff

et al. 2022

J. Phys.: Conf. Ser.

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Passive forward scattering radar is a system that consists of a transmitter that generates microwaves domain, and at the receiver part, receives LTE-based signal from the transmitter, which will result in the Doppler signature of any object. This system can actually be used for detecting the presence of guided missiles, human, aircraft and drone that pass through between the transmitter and receiver. For this study, the main objective is to detect a drone, which are mainly used by humans to trespass or enter secure and private areas. Recently, there have been a few cases of burglary in several states where they have made use of drones to monitor the owner of the house before entering that house. For that reason, this study can help to increase the security and protection against drone trespassing. Specifically, the detection of a drone was carried out by determining the Doppler signature of the drone at two different heights, which are 2 meters (lower) and 3 meters (upper) from the ground by using passive scattering radar. All of the experimental data collected from this study were processed using the MATLAB software to compare the result of drone detection at different heights through Principal Component Analysis (PCA) results. This analysis, from the upper and lower heights, shows a good detection and classification of the drone, however lower height indicated better performance in PCA and confusion matrices analysis. This is due to the bigger cross-sectional area for lower height compared to the upper height of drone that passed through the forward scatter region. This is useful for border protection and monitoring.

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Section: Introductionmentioning

confidence: 99%

LTE-based passive forward scattering radar for drone detection and classification

Aziz

Fodzi

Shariff

et al. 2022

J. Phys.: Conf. Ser.

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“…In this investigation, a Forward Scattering Radar (FSR) system was employed to identify drones. FSR is one type of bistatic radar that are used to identify and classify targets [2], [3].Radar sends out radio waves or microwaves, which are reflected by any object in their path. The reflected waves are received and processed by a receiver radar.…”

mentioning

confidence: 99%

“…In this investigation, a Forward Scattering Radar (FSR) system was employed to identify drones. FSR is one type of bistatic radar that are used to identify and classify targets [2], [3].…”

mentioning

confidence: 99%

Analysis On Drone Detection and Classification in LTE-Based Passive Forward Scattering Radar System

Abdul Aziz,

Mohd Fodzi,

Mohd Shariff

et al. 2023

IJIE

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Long-Term Evolution (LTE) is most commonly used in connection with 4G networks with high spectral efficiency, high peak data rates, flexible in frequency and bandwidth.By utilizing LTE signal in passive forward scattering radar as transmitter, this system is able to create a microwave domain at the radar's receiver part which generated a moving object's Doppler signature.The emergence of guided missiles, humans, airplanes, and drones that travel through between the forward scatter radar systems can really be spotted with this passive radar system. This study's primary goal is to employ passive forward scattering radar and an LTE signal to detect drones, which are commonly used by individuals to violate or invade private and secure places. In detail, a drone was detected at two distinct heights of twometers(lower) and threemeters(higher) from the ground by utilizingpassive forward scattering radar to generate Doppler signature of the flying drone.This experimental work is conducted at two locations which are Taman Suria (UiTM, Shah Alam) and Teluk Kemang (Port Dickson), due to the telecommunication transmitter antenna transmits Long-Term Evolution (LTE) signal with frequency of 1.8 GHz and 2.6 GHz. The results of drone detection at various heights were evaluated using Principal Component Analysis (PCA)on all the experimental data obtained. According to the evaluation, the lower height of the drone performedbetter in classification and confusion matrices analysis than the upper height due to a larger cross-sectional area for the lower height of the drone that travelled through the forward scatter zone.In summary, the overall study clearly demonstrates the effective categorization of flying drone detection at upper and lower positions in Principle Component Analysis (PCA). For future contribution of this research, it can be used at the airport to detect any unwanted drones trespassing the flight departure area, and important areas such as the Federal Administrative Centre of Malaysia, Putrajaya for spying purposes.

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Human Detection and Classification using Passive Forward Scattering Radar System at Different Places

Cited by 2 publications

References 8 publications

LTE-based passive forward scattering radar for drone detection and classification

LTE-based passive forward scattering radar for drone detection and classification

Analysis On Drone Detection and Classification in LTE-Based Passive Forward Scattering Radar System

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