GNSS interference source tracking using Kalman Filters

Sanat K. Biswas, Ediz Cetin

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contributionpeer-review

4 Citations (Scopus)


Modern infrastructure and a myriad of services rely on positioning and timing information provided by Global Navigation Satellite Systems (GNSS) and in particular the Global Positioning System (GPS). However, given their low received signal power levels, GNSS signals are vulnerable to Radio Frequency Interference (RFI), either from non-intentional or intentional (jamming), sources. Hence, GNSS itself has become a critical infrastructure which must be protected. Since RFI source is unknown a priori, passive localization systems consisting of spatially distributed Sensor Nodes (SNs) are needed to geo-locate the RFI. These systems typically use source Angle of Arrival (AOA), Time Difference of Arrival (TDOA) or a combination of AOA/TDOA measurements which are non-linear in nature, to estimate the RFI position. Also, dynamics associated with the RFI source(s) further complicates the geo-localization process. This paper explores and reports on the use of various Kalman Filters in combining AOA and TDOA measurements for efficient geo-localization and tracking of dynamic and stationary RFI sources based on real measurements from one such geo-localization system. We report on and contrast the geo-localization accuracies and computational complexities of the Extended, Unscented and Single Propagation Unscented Kalman Filters along with the traditional snap-shot approach.
Original languageEnglish
Title of host publication2020 IEEE/ION Position, Location and Navigation Symposium (PLANS)
Place of PublicationPiscataway, NJ
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Number of pages6
ISBN (Electronic)9781728102443
ISBN (Print)9781728194462
Publication statusPublished - 2020
Event2020 IEEE/ION Position, Location and Navigation Symposium - Portland, United States
Duration: 20 Apr 202023 Apr 2020


Conference2020 IEEE/ION Position, Location and Navigation Symposium
Abbreviated titlePLANS 2020
Country/TerritoryUnited States


Dive into the research topics of 'GNSS interference source tracking using Kalman Filters'. Together they form a unique fingerprint.

Cite this