Random Finite Set Approach to Signal Strength Based Passive Localization and Tracking

Ossi Kaltiokallio, Huseyin Yigitler, Jukka Talvitie, Mikko Valkama

Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingsScientificpeer-review


Radio frequency sensor networks can be utilized for locating and tracking people within coverage area of the network. The technology is based on the fact that humans alter properties of the wireless propagation channel which is observed in the channel estimates, enabling tracking without requiring people to carry any sensor, tag or device. Considerable efforts have been made to model the human induced perturbations to the channel and develop flexible models that adapt to the unique propagation environment to which the network is deployed in. This paper proposes a noteworthy conceptual shift in the design of passive localization and tracking systems as the focus is shifted from channel modeling to filter design. We approach the problem using random finite set theory enabling us to model detections, missed detections, false alarms and unknown data association in a rigorous manner. The Bayesian filtering recursion applied with random finite sets is presented and a computationally tractable Gaussian sum filter is developed. The development efforts of the paper are validated using experimental data and the results imply that the proposed approach can decrease the tracking error up to 48% with respect to a benchmark solution.

Original languageEnglish
Title of host publication2023 IEEE/ION Position, Location and Navigation Symposium, PLANS 2023
Number of pages11
ISBN (Electronic)978-1-6654-1772-3
ISBN (Print)978-1-6654-1773-0
Publication statusPublished - 2023
MoE publication typeA4 Conference publication
EventIEEE/ION Position, Location and Navigation Symposium - Monterey, United States
Duration: 24 Apr 202327 Apr 2023

Publication series

NameIEEE/ION Position Location and Navigation Symposium
ISSN (Print)2153-358X
ISSN (Electronic)2153-3598


ConferenceIEEE/ION Position, Location and Navigation Symposium
Abbreviated titlePLANS
Country/TerritoryUnited States


  • Gaussian sum filter
  • localization and tracking
  • random finite set
  • Received signal strength
  • RF sensor network


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