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4G LTE Detection using Nemo Handy
for PFSR Support System
By
NOOR HAFIZAH BINTI ABDUL AZIZ
Antenna Research Centre (ARC)
Faculty of Electrical Engineering, UiTM
Muhammad Anwar Aminudin
Faculty of Electrical Engineering, UiTM 1
Introduction Conventional radar: • Transmitter and Receiver are collocated. • Transmit electromagnetic waves in the space. • Hits the target present in the radar coverage area. The waves scatter
back to the receiver for detection. • All information about the target can be determined.
Receiver Transmitter
RT RR β
Target
Transmitter / Receiver
R
Target
Monostatic Bistatic
2
Introduction Conventional radar: • Transmitter and Receiver are collocated. • Transmit electromagnetic waves in the space. • Hits the target present in the radar coverage area. The waves scatter
back to the receiver for detection. • All information about the target can be determined.
Receiver Transmitter
RT RR β
Target
Transmitter / Receiver
R
Target
Monostatic
Forward Scatter
3
• Illuminators of opportunity is considered as the transmitter (passive radar
system).
• The angle between the transmitted and reflected rays is a bistatic angle, β.
Introduction: Passive Radar
Illuminator of
opportunity
Reference
Receiver
RT
RR
Target
β
Direct path Reflected path
Target Echo
Receiver Passive
Bistatic Radar
FM Radio, WiFi,
DVB, DAB,
WiMAX, GSM,
Satellite, LTE
4
• Special mode of bistatic radar.
• Narrow region stretched along the baseline of the bistatic angle, 𝛽 near 180⁰.
• The conventional FSR system transmits its own radio waves which can easily be
demolished by an enemy.
Baseline
Dedicated Transmitter Receiver
RT RR
Direct path (leakage)
Target
Forward Scatter Radar (FSR)
β
When 𝛽 near 180⁰, target blocks (“shadows”) EM energy travelling from the transmitter to the receiver.
5
• This could be done by integrating the forward scatter geometry (𝛽 near 180⁰) into the
passive radar system.
• The radar system is unseen by any hostile threat but on the other hand, it could detect
others.
– Leakage/direct signal which is unwanted in conventional radar, is good for FSR due to
signal perturbation of target.
• Integrating the forward scattering radar (FSR) mode in passive radar. The system can
get benefit from:
the enhancement in radar cross section (RCS)
the simple receiver system, thus low cost
the modulation of the specific transmitter does not influence the FS processing
signal.
Baseline
Receiver
RT RR
Direct path (leakage)
Target
Passive Forward Scatter Radar (FSR)
β
LTE Tower Base Station
8
LTE Based Passive FS Radar Applications
Passive FSR for
Traffic Surveillance
Passive FSR
for Building
Protection
Passive FSR for
Theft Surveillance
Passive FSR for
Border Protection
Passive FSR for
Low Altitude Air
Target Protection
LTE eNB Transmitter
Drone Insects migration monitoring
9
Sura, Dungun (Terengganu) (4.728, 103.433)
Experiment Site
10
PASSIVE RADAR SYSTEM
4.728029, 103.433336
Teluk Kemang, Port Dickson (Negeri Sembilan) (2.448, 101.856)
Experiment Site
11
BASE STATION
PASSIVE RADAR SYSTEM
2.448141, 101.855917
Taman Suria, UiTM Shah Alam (Selangor) (3.074, 101.498)
Experiment Site
12
2.754381, 101.441070
LTE Passive FSR Hardware
Receiving antenna
BPF
Amplifier
ADC
Detector
LPF & HPF
LNA
13
LTE Signal Spectrum
20 MHz
2.63 GHz
4G LTE with Center Frequency 1.8 GHz 14
Dungun Port Dickson Taman Suria
Arrangement of human trajectory
15
NEMO Handy
Human Moving Target Trajectory
Passive Radar
𝑨
LTE
5 m
𝑩
Speed (km/h) Moving target
58
0 m
Time (sec)
Am
plit
ude (
volt)
16
17
PLACE PERSON WIDTH (m) HEIGHT (m) DIMENSION (m2)
DUNGUN 1 0.26 1.78 0.4628
2 0.29 1.76 0.5104
PORT
DICKSON
1 0.26 1.76 0.4576
2 0.28 1.48 0.4144
TAMAN
SURIA
1 0.32 1.76 0.5632
2 0.29 1.76 0.5104
The information of the persons for the targets
18
Number of Sample Experiments
Person Number of samples
Dungun Port Dickson Taman Suria
Training Testing Training Testing Training Testing
1 31 4 33 4 34 4
2 34 4 35 4 32 4
Total 65 8 68 8 66 8
73 76 74
Cla
ssific
ation
Blo
ck D
iagra
m
Normalisation
Principal Component
Analysis (PCA)
Training
Classification
Rules/ k-NN
Time Domain
Signature
Display Person Category
Power Spectrum Estimation
(Frequency Domain)
1
2
3
Fea
ture
Extr
acti
on
19
Extract Data
Classification
Data Recording
Select Data
PFSR NEMO HANDY
Time Domain Signature
20
Time Domain Signature
21
Frequency Domain Signature
22
Frequency Domain Signature
23
Principle Component Analysis
24
Principle Component Analysis
25
NEMO Analysis
26
Condition Parameters
RSRP (dB) RSRQ (dB)
Excellent >=-80 >=-10
Good -80 to -95 -10 to -15
Moderate -95 to -110 -15 to -20
Poor <-110 <-20
Confusion Matrix
The classification results obtained from Dungun, Port Dickson and Taman Suria were 75%, 100% and 100%, respectively.
Dungun Port Dickson
Taman Suria
27
Person No. of
samples
Automatically
classified (%)
Person
1 2
1 37 75 25
2 39 25 75
Person No. of
samples
Automatically
classified (%)
Person
1 2
1 38 100 0
2 36 0 100
Person No. of
samples
Automatically
classified (%)
Person
1 2
1 35 100 0
2 38 0 100
Conclusion LTE signal is very useful in this PFSR system to detect human’s Doppler for differentiate and
classify targets due to forward scatter main lobe (FSML) which the targets’ RCS are influenced only
by the size and the shape of their silhouettes.
Nemo Handy was used to detect the signal strength of LTE signal and support passive forward
scattering radar system in detecting moving humans in the range of forward scatter region.
A simple LTE based passive forward scattering radar receiver and system in the experimental setup
was implemented at different places which are Dungun, Port Dickson and Taman Suria, (UiTM) with
2 different persons as target.
Classification for the radar system can be clearly seen, and this result discovered that body build
and size do indeed affect the power signal received by the radar receiver.
The farther the distance, the higher the environment noise, and so, it will be tougher to classify the
signal.
Nemo Handy proved that the value of RSRP and RSRQ parameters can affect the classification of
human Doppler signature.
The best value for RSRP should be less than -70dB, and RSRQ should be less than -12dB to
support better detection results in passive forward scatter radar system.
This project was successful in detecting the signal strength of 4G LTE network that focused on
Reference Signal Received Power (RSRP) and Reference Signal Received Quality (RSRQ), which
support the passive forward scattering radar system. 28