Standard

Accelerated SPSA-based Consensus Algorithm for Mutual Device Positioning. / Chernov, A.; Erofeeva, V.; Granichin, O.; Sudomir, A.

2025. 8071-8076 Paper presented at 64th IEEE Conference on Decision and Control, CDC 2025, Rio de Janeiro, Brazil.

Research output: Contribution to conference › Paper › peer-review

Harvard

Chernov, A, Erofeeva, V, Granichin, O & Sudomir, A 2025, 'Accelerated SPSA-based Consensus Algorithm for Mutual Device Positioning', Paper presented at 64th IEEE Conference on Decision and Control, CDC 2025, Rio de Janeiro, Brazil, 9/12/25 - 12/12/25 pp. 8071-8076. https://doi.org/10.1109/CDC57313.2025.11312296

APA

Chernov, A., Erofeeva, V., Granichin, O., & Sudomir, A. (2025). Accelerated SPSA-based Consensus Algorithm for Mutual Device Positioning. 8071-8076. Paper presented at 64th IEEE Conference on Decision and Control, CDC 2025, Rio de Janeiro, Brazil. https://doi.org/10.1109/CDC57313.2025.11312296

Vancouver

Chernov A, Erofeeva V, Granichin O, Sudomir A. Accelerated SPSA-based Consensus Algorithm for Mutual Device Positioning. 2025. Paper presented at 64th IEEE Conference on Decision and Control, CDC 2025, Rio de Janeiro, Brazil. https://doi.org/10.1109/CDC57313.2025.11312296

Author

Chernov, A. ; Erofeeva, V. ; Granichin, O. ; Sudomir, A. / Accelerated SPSA-based Consensus Algorithm for Mutual Device Positioning. Paper presented at 64th IEEE Conference on Decision and Control, CDC 2025, Rio de Janeiro, Brazil.6 p.

BibTeX

@conference{de1863305522464fbaa615d3529a9269,
title = "Accelerated SPSA-based Consensus Algorithm for Mutual Device Positioning",
abstract = "Positioning systems are crucial in multiple fields such as Internet of Things (IoT) due to their wide-ranging applications across smart environments and industries. Existing methods for global and local positioning are not effective in certain scenarios. This paper presents an advanced mutual positioning solution that combines a randomized stochastic optimization algorithm tailored for dynamic systems under unknown-but-bounded disturbances with a consenus method. The proposed method addresses measurement noise while maintaining computational efficiency. The approach is validated through numerical simulations, demonstrating its effectiveness in real-time positioning tasks within complex networks. {\textcopyright} 2025 IEEE.",
keywords = "Background noise, Complex networks, Computational efficiency, Internet of things, Optimization, Spurious signal noise, Bounded disturbances, Consensus algorithms, Global positioning, Local positioning, Measurement Noise, Positioning system, Smart environment, Stochastic optimization algorithm, Unknown but bounded, Wide-ranging applications, Stochastic systems",
author = "A. Chernov and V. Erofeeva and O. Granichin and A. Sudomir",
note = "Export Date: 23 March 2026; Cited By: 1; Conference name: 64th IEEE Conference on Decision and Control, CDC 2025; Conference date: 9 December 2025 through 12 December 2025; Conference code: 218842; CODEN: PCDCD; null ; Conference date: 09-12-2025 Through 12-12-2025",
year = "2025",
doi = "10.1109/CDC57313.2025.11312296",
language = "Английский",
pages = "8071--8076",

}

RIS

TY - CONF

T1 - Accelerated SPSA-based Consensus Algorithm for Mutual Device Positioning

AU - Chernov, A.

AU - Erofeeva, V.

AU - Granichin, O.

AU - Sudomir, A.

N1 - Export Date: 23 March 2026; Cited By: 1; Conference name: 64th IEEE Conference on Decision and Control, CDC 2025; Conference date: 9 December 2025 through 12 December 2025; Conference code: 218842; CODEN: PCDCD

PY - 2025

Y1 - 2025

N2 - Positioning systems are crucial in multiple fields such as Internet of Things (IoT) due to their wide-ranging applications across smart environments and industries. Existing methods for global and local positioning are not effective in certain scenarios. This paper presents an advanced mutual positioning solution that combines a randomized stochastic optimization algorithm tailored for dynamic systems under unknown-but-bounded disturbances with a consenus method. The proposed method addresses measurement noise while maintaining computational efficiency. The approach is validated through numerical simulations, demonstrating its effectiveness in real-time positioning tasks within complex networks. © 2025 IEEE.

AB - Positioning systems are crucial in multiple fields such as Internet of Things (IoT) due to their wide-ranging applications across smart environments and industries. Existing methods for global and local positioning are not effective in certain scenarios. This paper presents an advanced mutual positioning solution that combines a randomized stochastic optimization algorithm tailored for dynamic systems under unknown-but-bounded disturbances with a consenus method. The proposed method addresses measurement noise while maintaining computational efficiency. The approach is validated through numerical simulations, demonstrating its effectiveness in real-time positioning tasks within complex networks. © 2025 IEEE.

KW - Background noise

KW - Complex networks

KW - Computational efficiency

KW - Internet of things

KW - Optimization

KW - Spurious signal noise

KW - Bounded disturbances

KW - Consensus algorithms

KW - Global positioning

KW - Local positioning

KW - Measurement Noise

KW - Positioning system

KW - Smart environment

KW - Stochastic optimization algorithm

KW - Unknown but bounded

KW - Wide-ranging applications

KW - Stochastic systems

U2 - 10.1109/CDC57313.2025.11312296

DO - 10.1109/CDC57313.2025.11312296

M3 - материалы

SP - 8071

EP - 8076

Y2 - 9 December 2025 through 12 December 2025

ER -

ID: 150945159