Nanosecond-Precision Time-of-Arrival Estimation for Aircraft Signals with Low-Cost SDR Receivers

Calvo-Palomino, Roberto; Ricciato, Fabio; Repas, Blaž; Giustiniano, Domenico; Lenders, Vincent

doi:10.1109/ipsn.2018.00055

Cited by 17 publications

(8 citation statements)

References 10 publications

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“…Table 1.1 shows the software released as open source along this thesis. [4,7] LTESS-Track GPLv3 github.com/electrosense/LTESS-track [3] dump1090-hp GPLv3 github.com/openskynetwork/dump1090-hptoa [5] Mode S decoder GPLv3 github.com/openskynetwork/modes-uplink-decoder [6]…”

Section: Software Released As Open Sourcementioning

confidence: 99%

“…We have developed a web front-end to enable easy visualization of the spectrum data 5 . The spectrum visualizer allows interactive sensor selection and varying frequency resolution for detailed spectrum viewing.…”

Section: Live and Historical Spectrum Visualizationmentioning

confidence: 99%

“…5 shows the estimated LO frequency offset values reported by rtl_test after τ seconds based on the average of k subsequent measurements in window of size W , for different values of the latter. The measurement obtained with our method is also plotted as reference.…”

mentioning

confidence: 99%

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Collaborative wideband signal decoding using non-coherent receivers

Calvo-Palomino

Cordobés

Ricciato

et al. 2019

Proceedings of the 18th International Conference on Information Processing in Sensor Networks

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The Electromagnetic (EM) spectrum is well regulated by frequency assignment authorities, national regulatory agencies and the International Communication Union (ITU). Nowadays more and more devices such as mobile phones and Internet-of-Things (IoT) sensors make use of wireless communication. Additionally we need a more efficient use and a better understanding of the EM space to allocate and manage efficiently all communications. Governments and telecommunication operators perform spectrum measurements using expensive and bulky equipments scheduling very specific and limited spectrum campaigns. However, this approach does not scale as it can not allow to widely scan and analyze the spectrum 24/7 in real time due to the high cost of the large deployment. A pervasive deployment of spectrum sensors is required to solve this problem, allowing to monitor and analyze the EM radio waves in real time, across all possible frequencies, and physical locations. This thesis presents ElectroSense, a crowdsourcing and collaborative system that enables large scale deployments using Internet-of-Things (IoT) spectrum sensors to collect EM spectrum data which is analyzed in a big data infrastructure. The ElectroSense platform seeks a more efficient, safe and reliable real-time monitoring of the EM space by improving the accessibility and the democratization of spectrum data for the scientific community, stakeholders and the general public. In this work, we first present the ElectroSense architecture, and the design challenges that must be faced to attract a large community of users and all potential stakeholders. It is envisioned that a large number of sensors deployed in ElectroSense will be at affordable cost, supported by more powerful spectrum sensors when possible. Although low-cost Radio Frequency (RF) sensors have an acceptable performance for measuring the EM spectrum, they present several drawbacks (e.g. frequency range, Analog-to-Digital Converter (ADC), maximum sampling rate, etc.) that can negatively affect the quality of collected spectrum data as well as the applications of interest for the community.In order to counteract the above-mentioned limitations, we propose to exploit the fact that a dense network of spectrum sensors will be in range of the same transmitter(s).We envision to exploit this idea to enable smart collaborative algorithms among IoT RF sensors. In this thesis we identify the main research challenges to enable smart xiii xiv collaborative algorithms among low-cost RF sensors. We explore different crowdsourcing and collaborative scenarios where low-cost spectrum sensors work together in a distributed manner. First, we propose a fast and precise frequency offset estimation method for lowcost spectrum receivers that makes use of Long Term Evolution (LTE) signals broadcasted by the base stations. Second, we propose a novel, fast and precise Time-of-Arrival (ToA) estimation method for aircraft signals using low-cost IoT spectrum sensors that can achieve sub-nanosecond precision. Third, we propose a collabo...

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Section: Software Released As Open Sourcementioning

confidence: 99%

Section: Live and Historical Spectrum Visualizationmentioning

confidence: 99%

See 1 more Smart Citation

Collaborative wideband signal decoding using non-coherent receivers

Calvo-Palomino

Cordobés

Ricciato

et al. 2019

Proceedings of the 18th International Conference on Information Processing in Sensor Networks

Self Cite

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“…At the data-link level, the ADS-B message is encapsulated in Mode-S frames. As such, ADS-B uses Pulse-Position Modulation (PPM) and the replies/broadcasts are encoded by a certain number of pulses, each pulse being 1 µs long [14].…”

Section: Ads-b In a Nutshellmentioning

confidence: 99%

SOS - Securing Open Skies

Sciancalepore¹,

Pietro²

2018

Security, Privacy, and Anonymity in Computation, Communication, and Storage

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Automatic Dependent Surveillance -Broadcast (ADS-B) is the next generation communication technology selected for allowing commercial and military aircraft to deliver flight information to both ground base stations and other airplanes. Today, it is already on-board of 80% of commercial aircraft, and it will become mandatory by the 2020 in the US and the EU. ADS-B has been designed without any security consideration -messages are delivered wirelessly in clear text and they are not authenticated. In this paper we propose Securing Open Skies (SOS), a lightweight and standard-compliant framework for securing ADS-B technology wireless communications. SOS leverages the well-known µTESLA protocol, and includes some modifications necessary to deal with the severe bandwidth constraints of the ADS-B communication technology. In addition, SOS is resilient against message injection attacks, by recurring to majority voting techniques applied on central community servers. Overall, SOS emerges as a lightweight security solution, with a limited bandwidth overhead, that does not require any modification to the hardware already deployed. Further, SOS is standard compliant and able to reject active adversaries aiming at disrupting the correct functioning of the communication system. Finally, comparisons against state-of-the-art solutions do show the superior quality and viability of our solution.

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“…More recent works also demonstrate that is possible to apply the MLAT algorithm for detecting malicious ADS-B transmitters [ 30 , 31 ]; they also propose to improve the MLAT performance by optimizing the network geometry (using genetic algorithms) and smoothing the measurements by the use of Kalman filters. Finally, in [ 32 ], it was shown that it is possible to achieve precise TDOA estimation also using low-cost ADS-B receivers in the MLAT sensor network.…”

Section: Introductionmentioning

confidence: 99%

ADS-B Crowd-Sensor Network and Two-Step Kalman Filter for GNSS and ADS-B Cyber-Attack Detection

Leonardi

Sirbu

2021

Sensors

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Automatic Dependent Surveillance-Broadcast is an Air Traffic Control system in which aircraft transmit their own information (identity, position, velocity, etc.) to ground sensors for surveillance purposes. This system has many advantages compared to the classical surveillance radars: easy and low-cost implementation, high accuracy of data, and low renewal time, but also limitations: dependency on the Global Navigation Satellite System, a simple unencrypted and unauthenticated protocol. For these reasons, the system is exposed to attacks like jamming/spoofing of the on-board GNSS receiver or false ADS-B messages’ injection. After a mathematical model derivation of different types of attacks, we propose the use of a crowd sensor network capable of estimating the Time Difference Of Arrival of the ADS-B messages together with a two-step Kalman filter to detect these attacks (on-board GNSS/ADS-B tampering, false ADS-B message injection, GNSS Spoofing/Jamming). Tests with real data and simulations showed that the algorithm can detect all these attacks with a very high probability of detection and low probability of false alarm.

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Nanosecond-Precision Time-of-Arrival Estimation for Aircraft Signals with Low-Cost SDR Receivers

Cited by 17 publications

References 10 publications

Collaborative wideband signal decoding using non-coherent receivers

Collaborative wideband signal decoding using non-coherent receivers

SOS - Securing Open Skies

ADS-B Crowd-Sensor Network and Two-Step Kalman Filter for GNSS and ADS-B Cyber-Attack Detection

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