Distributed consensus-based observer design for target state estimation with bearing measurements

This paper introduces a novel distributed consensus-based observer design that enables a group of agents in an undirected communication network to solve the problem of target tracking, where the target is modeled as a chain of integrators of arbitrary order. Each agent is assumed to know its own position and simultaneously measure bearing vectors relative to the target. We start by introducing a general continuous time observer design tailored to systems whose state dynamics are modeled as chains of integrators and whose measurement model follows a particular nonlinear but observer-suited form. This design leverages a correction term that combines innovation and consensus components, allowing each agent to broadcast only a part of the state estimate to its neighbours, which effectively reduces the data flowing across the network. To provide uniform exponential stability guarantees, a novel result for a class of nonlinear closed-loop systems in a generalized observer form is introduced and subsequently used as the main tool to derive stability conditions on the observer gains. Then, by exploring the properties of orthogonal projection matrices, the proposed design is used to solve the distributed target tracking problem and provide explicit stability conditions that depend on the target-agents geometric formation. Practical examples are derived for a target modeled as first-, second-, and third-order integrator dynamics, highlighting the design procedure and the stability conditions imposed. Finally, numerical results showcase the properties of the proposed algorithm.

Authors

Publication Details

Journal
Automatica
Published
2026-05-02
DOI
https://doi.org/10.1016/j.automatica.2026.113031
Primary Topic
Distributed Control Multi-Agent Systems
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Distributed consensus-based observer design for target state estimation with bearing measurements

Rita Cunha, Marcelo Jacinto, Francisco Rego, Pedro Trindade
Automatica
Distributed Control Multi-Agent Systems
article

Distributed consensus-based observer design for target state estimation with bearing measurements

Rita Cunha, Marcelo Jacinto, Francisco Rego, Pedro Trindade
article en

Abstract

This paper introduces a novel distributed consensus-based observer design that enables a group of agents in an undirected communication network to solve the problem of target tracking, where the target is modeled as a chain of integrators of arbitrary order. Each agent is assumed to know its own position and simultaneously measure bearing vectors relative to the target. We start by introducing a general continuous time observer design tailored to systems whose state dynamics are modeled as chains of integrators and whose measurement model follows a particular nonlinear but observer-suited form. This design leverages a correction term that combines innovation and consensus components, allowing each agent to broadcast only a part of the state estimate to its neighbours, which effectively reduces the data flowing across the network. To provide uniform exponential stability guarantees, a novel result for a class of nonlinear closed-loop systems in a generalized observer form is introduced and subsequently used as the main tool to derive stability conditions on the observer gains. Then, by exploring the properties of orthogonal projection matrices, the proposed design is used to solve the distributed target tracking problem and provide explicit stability conditions that depend on the target-agents geometric formation. Practical examples are derived for a target modeled as first-, second-, and third-order integrator dynamics, highlighting the design procedure and the stability conditions imposed. Finally, numerical results showcase the properties of the proposed algorithm.

AutomaticaVol. 189
Fundação para a Ciência e a Tecnologia
Openalex Percentile: Top 99%
Distributed Control Multi-Agent Systems
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.