Drone Detection and Classification using Passive Forward Scattering Radar

Radar is a system that can analyze object detection that uses radio waves to determine the range, angle or velocity of the object. The passive radar system consists of both transmitters, to generate microwaves domain and produce the electromagnetic waves for radio system, and the receiver, to receive and process the data obtain from the transmitter signal to determine the Doppler signature of the objects that can be used to detect any presence of drone, aircraft and guided missiles that pass through the system between the transmitter and receiver. The objective of this study was mainly to detect drones, which can be liken to a situation where an unmanned aerial vehicle (UAV) is used, and the drone is mainly used by humans to enter or trespass private and secured zone. Besides that, this study can help improve the security at Malaysian borders or at important events, such as during the latest Malaysian 14th General Election, where man flew a drone during the nomination process. The detection can be done by differentiating the size of the drone and prototype, with a focus on the dimension. In this study, we used passive forward scattering radar for drone detection to get the Doppler signature. The Doppler signature is produced when the antenna detects the presence of the drone passing between the transmitter and receiver. The transmitter produces a power signal that transmits a frequency of Long-Term Evolution (LTE), and in this study, the frequencies used were 1.8 GHz and 2.6 GHz. The 1.8 GHz signal provided better quality compared to 2.6 GHz because it has wider and better network coverage known as 4G LTE as introduced by Maxis provider. Furthermore, all of the data collected was processed and analyzed using MATLAB software to classify drone and prototype signatures through Principal Component Analysis (PCA) results. For future contribution of this project, 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

Speed recognition based on ground vehicle in passive forward scattering radar

The merging of noise reduction and reshaped of the signal in time domain is headed to newfangled clustering methods. After a deep investigation on pre-processing the detection of ground vehicle using passive forward scattering radar (PFSR), principal component analysis (PCA) could be used as spectral signature for target’s speed recognition. The clustering-based PCA able to distinguish the target’s rapidity from the passive forward scattering radar receiver. A small five door hatchback vehicle is used for detection as ground vehicle with several speed and various distance from the passive forward scattering radar receiver. The distance give impact to the clustering-based PCA which is closer vehicle to the passive forward scattering radar offers finer variance of training data in speed recognition

RCS classification on ground moving target using LTE passive bistatic radar

Detection and location on the ground moving target are a function of dependent bistatic Radar Cross Section (RCS) and radar design parameters which in this experimental study used LTE signal as a source for passive bistatic radar (PBR). Ground moving target also can be classified in dimensions using conventional processing approaches which we performed a simulation using Computer Simulation Technology (CST) Microwave studio. The target bistatic radar cross-section will give a realistic calculation on PBR performance with the requirement of complete treatment. Three models of ground moving target are designed using Autodesk software which the models are classified as compact car, saloon car and sport utility vehicle (SUV) for size of small and medium and large respectively. The designs are for observation on the performance of RCS using a bistatic area between transmitter and receiver with the frequency transmit signal from long-term evolution (LTE) based station is 2.6 GHz and with far-field conditions. The simulation results show that largest area of ground moving target, SUV had better outcome compared to other ground moving target which reliable with Babinet’s principle, which declares a target of physical cross-sectional area is proportionate to RCS. Different cross-sectional area of transmitting signal from other ground moving target give smaller RCS which cause from the reduction area of reflected signal such as compact car according to small size and saloon car according to medium size. This might improve the sensitivity of LTE passive bistatic radar if using greater size of ground moving target for a better RCS performance

Speed Recognition Based on Ground Vehicle in Passive Forward Scattering Radar

The merging of noise reduction and reshaped of the signal in time domain is headed to newfangled clustering methods. After a deep investigation on pre-processing the detection of ground vehicle using passive forward scattering radar (PFSR), principal component analysis (PCA) could be used as spectral signature for target’s speed recognition. The clustering-based PCA able to distinguish the target’s rapidity from the passive forward scattering radar receiver. A small five door hatchback vehicle is used for detection as ground vehicle with several speed and various distance from the passive forward scattering radar receiver. The distance give impact to the clustering-based PCA which is closer vehicle to the passive forward scattering radar offers finer variance of training data in speed recognition

RCS Predictions through Angle of Ground Moving Target using LTE-Based Passive Forward Scattering Radar

Moving target detection and location are a function of dependent bistatic Radar Cross Section (RCS) and radar design parameters, which in our experimental study used long term-evolution (LTE) signal as a source for passive forward scattering radar (PFSR). Moving target also can be classified in positions using conventional processing approaches, which we performed a simulation using Computer Simulation Technology (CST) Microwave studio. The target bistatic radar cross-section gives a realistic calculation on passive bistatic radar (PBR) performance with the requirement of complete treatment. A model of a car, Toyota Rush as a ground moving target had been designed to observe the performance of RCS due to the changes of bistatic angle between the transmitter and the receiver with the frequency transmit signal from LTE based station at 2.6 GHz and farfield conditions. The results of the simulation show that the largest area of moving target, which is 90 degree of transmitting signal had better outcome compared to the other angle, which is reliable with Babinet’s principle that declares a target of physical cross-sectional area is proportionate to RCS. Different angle of transmitting signal gave smaller RCS, which is the cause from the reduction area of reflected signal from the ground moving target such as 45 degree according to the front side view of Toyota Rush and 135 degree according to back side of Toyota Rush. This might improve the sensitivity of elevation targets with an adjustment of the receiver angle to the target and transmitter for a better RCS performance

A passive forward scattering radar for detecting humans and characterizing human behaviours

Background: The capability to detect human and identify their movement is progressively important in military and security applications. Usually, most of the radar systems are active systems which it is easily to be detected by the opponent. In consequence, passive radar is set to become alternative to conventional active radar which it offers a decisive operational advantage, it could not be located. Passive radar does not emit any signals of its own which it could not be jammed. Therefore, passive radar use many different transmission sources that are sent out from various location to detect ground moving target especially human. Objective: The integrating of passive forward scattering radar that provide a lot of benefits and capable to detect human and characterize human behaviors which the radar system analysis and signal processing are using MATLAB software. Results: The radar system able to detect human and characterize the behaviors which divided into two movements, walking and running. Conclusion: This is the evolving area of research provide a more useful outcomes in detecting and characterizing the human movements specifically used the passive forward scattering radar concept of unseen by others

Vehicle recognition analysis in LTE based forward scattering radar

By integrating the forward scattering radar (FSR) mode in passive radar can provide many advantages to the conventional passive radar system. The system can benefit from the enhancement in radar cross section (RCS), the low cost and the simple receiver system. In addition, the receiver circuit is less complicated as it does not require a synchronization signal from the transmitter. This paper presents the experimental results for ground target detection and classification in a passive radar system exploiting the effect of forward scatter. The latest 4G Long-Term Evolution (LTE) technology signal is used as the source of the signal transmission. The receiver, the detection and the classification system is explained. Results have shown the system's capability for detecting and classifying ground targets using the FSR technique in passive radar. Hence, it opens up a new frontier in passive radar that can be used for many applications, including border protection, microwave fences, building monitoring and etc

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

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 two meters (lower) and three meters (higher) from the ground by utilizing passive 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 performed better 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

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

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 two meters (lower) and three meters (higher) from the ground by utilizing passive 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 performed better 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

Ground moving target detection using LTE-based passive radar

This paper examines the feasibility of 4G (LTE)-based passive radar for detecting ground moving targets. Specifically, the focus of this paper is to describe the proposed LTE-based passive radar system and to conduct an experiment using a real LTE eNB transmitter as an illumination source. Seven scenarios were carried out to investigate the detection performance of the proposed system on moving targets. Each scenario had different types of ground targets moving with a variety of speeds and directions. The experimental results showed that the LTE-based passive radar system has the capability to detect typical ground targets/objects like cars, motorbikes and humans moving with different speeds, trajectories and ranges. The positive results opened up a new frontier for passive radar systems to be used in many potential applications, including border protection, microwave fences, monitor of buildings and others