Detection of On-Road Vehicles Emanating GPS Interference Gorkem Kar - - PowerPoint PPT Presentation

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Detection of On-Road Vehicles Emanating GPS Interference Gorkem Kar - - PowerPoint PPT Presentation

Aug 16, 2022 49 likes •260 views

Detection of On-Road Vehicles Emanating GPS Interference Gorkem Kar Hossen Mustafa Yan Wang Yingying Chen Wenyuan Xu Marco Gruteser Tam Vu Winlab Winter Research Review ACM CCS 2014 1 GPS in Critical Infrastructures 2 GPS Jammers 3

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SLIDE 1

Detection of On-Road Vehicles Emanating GPS Interference

Gorkem Kar Hossen Mustafa Yan Wang Yingying Chen Wenyuan Xu Marco Gruteser Tam Vu

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Winlab Winter Research Review ACM CCS 2014

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SLIDE 2

GPS in Critical Infrastructures

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SLIDE 3

GPS Jammers

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SLIDE 4

Newark Airport Incident

  • In 2010, ground GPS receivers did not work for

a few minutes repeatedly over couple of months.

  • It took 3 months to locate the problem.

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SLIDE 5

Current Solutions

  • Handheld devices

– Works only in static scenarios – Used manually for a short time

  • Standard wireless localization techniques

– Not sufficient to pinpoint a vehicle in dense traffic

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What is needed?

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SLIDE 6

What is Needed?

  • A detection and identification system that is;

– automated, with high accuracy, and at a low cost,

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SLIDE 7

Overview of Jamming Detection System

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Jammer Monitoring Point Mobile Phone

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SLIDE 8

Multiple Monitoring Points

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Jammer is detected with MP1 @ time t1 MP 2 MP 1

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SLIDE 9

Multiple Monitoring Points

Jammer is detected with MP2 @ time t2 MP 2 MP 1

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SLIDE 10

Monitoring Points

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SLIDE 11

Experimental Setup

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USRP

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SLIDE 12

MP Location

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Camera Monitoring Point

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SLIDE 13

Detection Zone

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SLIDE 14

Identified Vehicle Positions at tm

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(m) (m)

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SLIDE 15

Single Monitoring Point Case

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@ MP 1 @ MP 2

We could uniquely identify the transmitting car with 65% @ MP 1 and 35% @ MP 2 with NO false positive rate.

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SLIDE 16

Multiple Monitoring Case

  • The detection rate can be improved by

combining the information collected from both zones.

– Intersect the candidate vehicle sets @ MP1 and MP2.

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This resulted in only a single detected vehicle and a correct identification of our transmitter vehicle in all cases.

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SLIDE 17

Passive Roadside Monitoring

  • 5 locations are chosen in NJ and SC; 200 hours of

monitoring passively,

– a major highway, – one of the busiest toll road, – and an urban road

  • Two suspicious interference incidents are

detected.

  • May not come from real jammer, but still proves

the interference exist @ L1 frequency band (which is GPS band, 1.5 GHz).

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SLIDE 18

Mobile Detectors

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SLIDE 19

How to Detect the Interference via Mobile Phones?

Profiling

– Use Android API to get the current SNR(Signal-to-Noise Ratio) value of the location – Create a SNR profile of a sample route by matching SNR with GPS position (expected SNR)

Anomaly Detection

– Compare current reading(SNR) of the mobile detector with the expected SNR from profiling stage – If current reading of SNR is lower than the expected SNR, there should be an interference at L1 freq., central office should be notified.

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Average SNR (dB)

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SLIDE 20

Conclusion

  • Presented a low-cost jammer identification

system that can be mass deployed in roadways to automatically detect and identify the vehicles with GPS jammers.

  • The key components of the system are

monitoring stations and mobile detectors.

  • Our mobile detector can detect interfering signals

based on measurements that are readily available in most GPS receivers

– Thus, it is possible to detect jammers via crowdsourcing.

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SLIDE 21

THANKS!

  • Any questions?