Single range aided navigation and source localization: Observability and filter design

Batista, Pedro; Silvestre, Carlos; Oliveira, Paulo

doi:10.1016/j.sysconle.2011.05.004

Cited by 142 publications

(88 citation statements)

References 19 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This representation makes the SLAM problem solvable with the Kalman filter (KF), and global stabillety can be proven by observability analysis [12]. Further, necessary and sufficient conditions on the observability of the nonlinear system are derived in [13]. Similar work, is done by Lourenco and Guerreiro [14][1], in which a globally asymptotically stable (GAS) sensorbased SLAM estimation is presented, for range and bearing, bearing only and range only measurements.…”

Section: Introductionmentioning

confidence: 94%

Redesign and analysis of globally asymptotically stable bearing only SLAM

Bjørne

Johansen

Brekke

2017

2017 20th International Conference on Information Fusion (Fusion)

View full text Add to dashboard Cite

Abstract-The Simultaneous Localization And Mapping (SLAM) estimation problem is a nonlinear problem, due to the nature of the range and bearing measurements. In latter years it has been demonstrated that if the nonlinearities from the attitude are handled by a separate nonlinear observer, the SLAM dynamics can be represented as a linear time varying (LTV) system, by introducing these nonlinearities and nonlinear measurements as time varying vectors and matrices. This makes the SLAM estimation problem globally solvable with a Kalman filter, however, the noise structure is no longer trivial. In this paper, a new bearings only SLAM estimation algorithm is presented, including a novel design of the noise covariance matrices. Simulations of the SLAM estimator are presented, and show the performance of the state and uncertainty estimates, as well as the stability of the proposed estimator.

show abstract

Section: Introductionmentioning

confidence: 94%

Redesign and analysis of globally asymptotically stable bearing only SLAM

Bjørne

Johansen

Brekke

2017

2017 20th International Conference on Information Fusion (Fusion)

View full text Add to dashboard Cite

show abstract

“…However, the matrix A(t, y(t)) depends not only on time but also on the system output, even though the system can be seen as a linear time-varying system for observability analysis purposes as the dependency on the system state is now absent and the system output is known. This property is established in (Batista et al 2011b, Lemma 1), according to which if the observability Gramian associated with a system with a dynamics matrix depending on the system input and output is invertible, then the system is observable. This result will be used throughout this section.…”

Section: Observability Analysismentioning

confidence: 99%

“…Proof The proof follows by transforming the system in analysis by means of a Lyapunov transformation [see Brockett (1970)], and then proving that the observability Gramian of the transformed system is non-singular in the conditions of the theorem, which, as (Batista et al 2011b, Lemma 1) states, implies the observability of the transformed system. A Lyapunov transformation preserves the observability properties of a system, hence it suffices to prove that the new, transformed system is observable.…”

Section: Theorem 1 Consider System (4) and Letmentioning

confidence: 99%

“…A Lyapunov transformation preserves the observability properties of a system, hence it suffices to prove that the new, transformed system is observable. This approach has been used successfully in the past, see for example Batista et al (2011b) and Batista et al (2010). Let T(t) be a Lyapunov transformation such that…”

Section: Theorem 1 Consider System (4) and Letmentioning

confidence: 99%

See 1 more Smart Citation

Simultaneous localization and mapping for aerial vehicles: a 3-D sensor-based GAS filter

et al. 2015

Self Cite

View full text Add to dashboard Cite

This paper presents the design, analysis, and experimental validation of a globally asymptotically stable (GAS) filter for simultaneous localization and mapping (SLAM) with application to unmanned aerial vehicles. The main contributions of this paper are the results of global convergence and stability for SLAM in tridimensional (3-D) environments. The SLAM problem is formulated in a sensor-based framework and modified in such a way that the structure may be regarded as linear time-varying for observability purposes, from which a Kalman filter with GAS error dynamics follows naturally. The proposed solution includes the estimation of both body-fixed linear velocity and rate B Pedro Lourenço gyro measurement biases. Experimental results from several runs, using an instrumented quadrotor equipped with a RGB-D camera, are included in the paper to illustrate the performance of the algorithm under realistic conditions.

show abstract

“…24,30 Linearization may fail to adequately model the input/output relationship of the nonlinear system over a wide range of operating conditions. The empirical observability gramian does not require linearization but merely the ability to simulate the system.…”

Section: B Measures Of Leader Aircraft Observabilitymentioning

confidence: 99%

Wake Estimation and Optimal Control for Autonomous Aircraft in Formation Flight

DeVries

Paley

2013

AIAA Guidance, Navigation, and Control (GNC) Conference

View full text Add to dashboard Cite

The continued development of sophisticated aircraft with high fidelity control systems will enable autonomous execution of challenging tasks such as aerial refueling and close formation flight. In order to achieve such tasks in autonomous flight, an aircraft must sense other aircraft in close proximity and position itself relative to them. For example, aerial refueling requires the follower aircraft to intercept the filling nozzle attached to the leader aircraft; also, formation-flying aircraft must position themselves strategically to realize benefits of aerodynamic efficiency. This paper uses lifting-line theory to represent a two-aircraft formation and presents a grid-based, recursive Bayesian filter for estimating the wake parameters of the leader aircraft using noisy pressure measurements distributed along the trailing aircraft's wing; the estimator also requires a binary, relative-altitude measurement to break the vertical symmetry. Optimal control strategies are presented to steer the follower aircraft to a desired position relative to the leader while simultaneously optimizing the observability of the leader's relative position. The control algorithms guide the follower aircraft along trajectories that maintain adequate observability, thereby guaranteeing estimator performance. Theoretical results are illustrated using numerical examples of two-aircraft formations.

show abstract

Single range aided navigation and source localization: Observability and filter design

Cited by 142 publications

References 19 publications

Redesign and analysis of globally asymptotically stable bearing only SLAM

Redesign and analysis of globally asymptotically stable bearing only SLAM

Simultaneous localization and mapping for aerial vehicles: a 3-D sensor-based GAS filter

Wake Estimation and Optimal Control for Autonomous Aircraft in Formation Flight

Contact Info

Product

Resources

About