Weighted SPSA-based Consensus Algorithm for Distributed Cooperative Target Tracking

Victoria Erofeeva, Oleg Granichin, Olga Granichina, Anton Proskurnikov, Anna Sergeenko

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

2 Scopus citations


In this paper, a new algorithm for distributed multi-target tracking in a sensor network is proposed. The main feature of that algorithm, combining the SPSA techniques and iterative averaging ("consensus algorithm"), is the ability to solve distributed optimization problems in presence of signals with fully uncertain distribution; the only assumption is the signal's boundedness. As an example, we consider the multi-target tracking problem, in which the unknown signals include measurement errors and unpredictable target's maneuvers; statistical properties of these signals are unknown. A special choice of weights in the algorithm enables its application to targets exhibiting different behaviors. An explicit estimate of the residual's covariance matrix is obtained, which may be considered as a performance index of the algorithm. Theoretical results are illustrated by numerical simulations.

Original languageEnglish
Title of host publication2021 European Control Conference, ECC 2021
PublisherInstitute of Electrical and Electronics Engineers Inc.
Number of pages6
ISBN (Electronic)9789463842365
StatePublished - 2021
Event2021 European Control Conference, ECC 2021 - Delft, Netherlands
Duration: 29 Jun 20212 Jul 2021

Publication series

Name2021 European Control Conference, ECC 2021


Conference2021 European Control Conference, ECC 2021

Scopus subject areas

  • Control and Optimization
  • Artificial Intelligence
  • Decision Sciences (miscellaneous)
  • Control and Systems Engineering
  • Mechanical Engineering
  • Computational Mathematics


Dive into the research topics of 'Weighted SPSA-based Consensus Algorithm for Distributed Cooperative Target Tracking'. Together they form a unique fingerprint.

Cite this