Implementation of an extrapolated single-propagation particle filter for interference source localization using a sensor network

Duc Dung Vu; Sanat K. Biswas; Alan Kan; Ediz Cetin

doi:10.1007/978-3-031-29871-4_37

Implementation of an extrapolated single-propagation particle filter for interference source localization using a sensor network

Duc Dung Vu^*, Sanat K. Biswas, Alan Kan, Ediz Cetin

^*Corresponding author for this work

School of Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding contribution › peer-review

2 Citations (Scopus)

Abstract

Global Navigation Satellite System (GNSS) signals are vulnerable to intentional or unintentional Radio Frequency Interference (RFI) due to their low-received signal power levels. In order to geo-locate and track the RFI source(s), distributed network of sensors are used. However, the sensor measurements tend to be corrupted or degraded due to the environment and system noise. In addition, the non-linear nature of the position estimation based on Angle of Arrival (AOA) and Time Difference of Arrival (TDOA) measurements further complicates the problem. This paper presents the hardware design of an extrapolated single-propagation particle filter (ESP-PF). The ESP-PF was proposed to overcome the challenges in RFI source localization based on hybrid AOA and TDOA measurements from and between the sensor nodes, respectively. The performance of this hardware implementation is evaluated and compared with its fully-software counterpart in terms of position estimation accuracy. The results show that the hardware implementation performs comparably with that of the floating-point software-only implementation.

Original language	English
Title of host publication	Sensing technology
Subtitle of host publication	proceedings of ICST'15
Editors	Nagender Kumar Suryadevara, Boby George, Krishanthi P. Jayasundera, Subhas Chandra Mukhopadhyay
Place of Publication	Cham
Publisher	Springer, Springer Nature
Pages	365-373
Number of pages	9
ISBN (Electronic)	9783031298714
ISBN (Print)	9783031298707, 9783031298738
DOIs	https://doi.org/10.1007/978-3-031-29871-4_37
Publication status	Published - 2023
Event	15th International Conference on Sensing Technologies (ICST) 2022 - Sydeny, Australia Duration: 5 Dec 2022 → 7 Dec 2022 Conference number: 15th

Publication series

Name	Lecture Notes in Electrical Engineering
Publisher	Springer
Volume	1035
ISSN (Print)	1876-1100
ISSN (Electronic)	1876-1119

Conference

Conference	15th International Conference on Sensing Technologies (ICST) 2022
Country/Territory	Australia
City	Sydeny
Period	5/12/22 → 7/12/22

Keywords

Interference
GNSS
Particle Filter
Geo-localization

Access to Document

10.1007/978-3-031-29871-4_37

Cite this

Vu, D. D., Biswas, S. K., Kan, A., & Cetin, E. (2023). Implementation of an extrapolated single-propagation particle filter for interference source localization using a sensor network. In N. K. Suryadevara, B. George, K. P. Jayasundera, & S. C. Mukhopadhyay (Eds.), Sensing technology: proceedings of ICST'15 (pp. 365-373). (Lecture Notes in Electrical Engineering; Vol. 1035). Springer, Springer Nature. https://doi.org/10.1007/978-3-031-29871-4_37

Vu, Duc Dung ; Biswas, Sanat K. ; Kan, Alan et al. / Implementation of an extrapolated single-propagation particle filter for interference source localization using a sensor network. Sensing technology: proceedings of ICST'15. editor / Nagender Kumar Suryadevara ; Boby George ; Krishanthi P. Jayasundera ; Subhas Chandra Mukhopadhyay. Cham : Springer, Springer Nature, 2023. pp. 365-373 (Lecture Notes in Electrical Engineering).

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abstract = "Global Navigation Satellite System (GNSS) signals are vulnerable to intentional or unintentional Radio Frequency Interference (RFI) due to their low-received signal power levels. In order to geo-locate and track the RFI source(s), distributed network of sensors are used. However, the sensor measurements tend to be corrupted or degraded due to the environment and system noise. In addition, the non-linear nature of the position estimation based on Angle of Arrival (AOA) and Time Difference of Arrival (TDOA) measurements further complicates the problem. This paper presents the hardware design of an extrapolated single-propagation particle filter (ESP-PF). The ESP-PF was proposed to overcome the challenges in RFI source localization based on hybrid AOA and TDOA measurements from and between the sensor nodes, respectively. The performance of this hardware implementation is evaluated and compared with its fully-software counterpart in terms of position estimation accuracy. The results show that the hardware implementation performs comparably with that of the floating-point software-only implementation.",

keywords = "Interference, GNSS, Particle Filter, Geo-localization",

author = "Vu, \{Duc Dung\} and Biswas, \{Sanat K.\} and Alan Kan and Ediz Cetin",

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Vu, DD, Biswas, SK, Kan, A & Cetin, E 2023, Implementation of an extrapolated single-propagation particle filter for interference source localization using a sensor network. in NK Suryadevara, B George, KP Jayasundera & SC Mukhopadhyay (eds), Sensing technology: proceedings of ICST'15. Lecture Notes in Electrical Engineering, vol. 1035, Springer, Springer Nature, Cham, pp. 365-373, 15th International Conference on Sensing Technologies (ICST) 2022, Sydeny, New South Wales, Australia, 5/12/22. https://doi.org/10.1007/978-3-031-29871-4_37

Implementation of an extrapolated single-propagation particle filter for interference source localization using a sensor network. / Vu, Duc Dung; Biswas, Sanat K.; Kan, Alan et al.
Sensing technology: proceedings of ICST'15. ed. / Nagender Kumar Suryadevara; Boby George; Krishanthi P. Jayasundera; Subhas Chandra Mukhopadhyay. Cham: Springer, Springer Nature, 2023. p. 365-373 (Lecture Notes in Electrical Engineering; Vol. 1035).

Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding contribution › peer-review

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AU - Vu, Duc Dung

AU - Biswas, Sanat K.

AU - Kan, Alan

AU - Cetin, Ediz

N1 - Conference code: 15th

PY - 2023

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N2 - Global Navigation Satellite System (GNSS) signals are vulnerable to intentional or unintentional Radio Frequency Interference (RFI) due to their low-received signal power levels. In order to geo-locate and track the RFI source(s), distributed network of sensors are used. However, the sensor measurements tend to be corrupted or degraded due to the environment and system noise. In addition, the non-linear nature of the position estimation based on Angle of Arrival (AOA) and Time Difference of Arrival (TDOA) measurements further complicates the problem. This paper presents the hardware design of an extrapolated single-propagation particle filter (ESP-PF). The ESP-PF was proposed to overcome the challenges in RFI source localization based on hybrid AOA and TDOA measurements from and between the sensor nodes, respectively. The performance of this hardware implementation is evaluated and compared with its fully-software counterpart in terms of position estimation accuracy. The results show that the hardware implementation performs comparably with that of the floating-point software-only implementation.

AB - Global Navigation Satellite System (GNSS) signals are vulnerable to intentional or unintentional Radio Frequency Interference (RFI) due to their low-received signal power levels. In order to geo-locate and track the RFI source(s), distributed network of sensors are used. However, the sensor measurements tend to be corrupted or degraded due to the environment and system noise. In addition, the non-linear nature of the position estimation based on Angle of Arrival (AOA) and Time Difference of Arrival (TDOA) measurements further complicates the problem. This paper presents the hardware design of an extrapolated single-propagation particle filter (ESP-PF). The ESP-PF was proposed to overcome the challenges in RFI source localization based on hybrid AOA and TDOA measurements from and between the sensor nodes, respectively. The performance of this hardware implementation is evaluated and compared with its fully-software counterpart in terms of position estimation accuracy. The results show that the hardware implementation performs comparably with that of the floating-point software-only implementation.

KW - Interference

KW - GNSS

KW - Particle Filter

KW - Geo-localization

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SN - 9783031298707

SN - 9783031298738

T3 - Lecture Notes in Electrical Engineering

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BT - Sensing technology

A2 - Suryadevara, Nagender Kumar

A2 - George, Boby

A2 - Jayasundera, Krishanthi P.

A2 - Mukhopadhyay, Subhas Chandra

PB - Springer, Springer Nature

CY - Cham

T2 - 15th International Conference on Sensing Technologies (ICST) 2022

Y2 - 5 December 2022 through 7 December 2022

ER -

Vu DD, Biswas SK, Kan A , Cetin E. Implementation of an extrapolated single-propagation particle filter for interference source localization using a sensor network. In Suryadevara NK, George B, Jayasundera KP, Mukhopadhyay SC, editors, Sensing technology: proceedings of ICST'15. Cham: Springer, Springer Nature. 2023. p. 365-373. (Lecture Notes in Electrical Engineering). doi: 10.1007/978-3-031-29871-4_37