Comparative analysis of EKF and Particle Filter performance for an acoustic tracking system for AUVs exploiting bearing-only measurements

Bresciani, Matteo; Costanzi, Riccardo; Manzari, Vincenzo; Peralta, Giovanni; Terracciano, Daniele S.; Caiti, Andrea

doi:10.1109/ieeeconf38699.2020.9389288

Cited by 3 publications

(2 citation statements)

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“…We consider p T k = x k y k to be the state vector for the follower AUV. To simplify this analysis, we substitute Equation ( 14) and (15) into Equation (4) to rearrange the Jacobian matrices Fk−1 and Ĥi,k equivalently, as follows:…”

Section: Observability and Consistency Analysis Of Multi-auv Cooperat...mentioning

confidence: 99%

“…Many multi-AUV (or robot) cooperative localization algorithms have been proposed and successfully implemented in the literature, including standard-based extended Kalman filter (EKF) [14], particle filter (PF) [15], maximum a posteriori (MAP) [16], and moving horizon estimation (MHE) [17]. However, in these studies, the observability matrix of state estimation has a subspace with higher dimensions than the ideal observability matrix.…”

Section: Introductionmentioning

confidence: 99%

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Consistent Extended Kalman Filter-Based Cooperative Localization of Multiple Autonomous Underwater Vehicles

Zhang

2022

Sensors

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In order to solve the problem of inconsistent state estimation when multiple autonomous underwater vehicles (AUVs) are co-located, this paper proposes a method of multi-AUV co-location based on the consistent extended Kalman filter (EKF). Firstly, the dynamic model of cooperative positioning system follower AUV under two leaders alternately transmitting navigation information is established. Secondly, the observability of the standard linearization estimator based on the lead-follower multi-AUV cooperative positioning system is analyzed by comparing the subspace of the observable matrix of state estimation with that of an ideal observable matrix, it can be concluded that the estimation of state by standard EKF is inconsistent. Finally, aiming at the problem of inconsistent state estimation, a consistent EKF multi-AUV cooperative localization algorithm is designed. The algorithm corrects the linearized measurement values in the Jacobian matrix for cooperative positioning, ensuring that the linearized estimator can obtain accurate measurement values. The positioning results of the follower AUV under dead reckoning, standard EKF, and consistent EKF algorithms are simulated, analyzed, and compared with the real trajectory of the following AUV. The simulation results show that the follower AUV with a consistent EKF algorithm can keep synchronization with the leader AUV more stably.

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Section: Observability and Consistency Analysis Of Multi-auv Cooperat...mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Consistent Extended Kalman Filter-Based Cooperative Localization of Multiple Autonomous Underwater Vehicles

Zhang

2022

Sensors

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Mobile Feature Enhanced High-Accuracy Positioning Based on Carrier Phase and Bayesian Estimation

Fan

Zeng

Tian

2022

IEEE Internet Things J.

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Using Interchangeably the Extended Kalman Filter and Geodetic Robust Adjustment Methods to Increase the Accuracy of Surface Vehicle Positioning in the Coastal Zone

Naus

Szymak

2023

Applied Sciences

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This paper presents a study to evaluate the comparative positioning accuracy of Surface Vehicle (SV) using Dead Reckoning (DR), Geodetic Least-Squares Adjustment (GLSA), Geodetic Robust Adjustment (GRA), and External Kalman Filter (EKF) methods. This involved simulating the results of navigational measurements subject to errors (including gross errors) used to position the SV swimming along a given trajectory in the vicinity of three beacons. We showed an apparent increase in the SV positioning accuracy, from approximately 9 m of Root Mean Square (RMS) obtained by DR and GLSA methods, to approximately 2 m (RMS), achieved using GRA and EKF methods. We also showed that, by interchanging GRA and EKF methods, it is still possible to increase the positioning accuracy of the SV up to 1.14 m (RMS). However, such an interchange should occur after the experimentally determined limit of the mean error of the position coordinates estimated by the GRA method has been exceeded.

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Comparative analysis of EKF and Particle Filter performance for an acoustic tracking system for AUVs exploiting bearing-only measurements

Cited by 3 publications

References 5 publications

Consistent Extended Kalman Filter-Based Cooperative Localization of Multiple Autonomous Underwater Vehicles

Consistent Extended Kalman Filter-Based Cooperative Localization of Multiple Autonomous Underwater Vehicles

Mobile Feature Enhanced High-Accuracy Positioning Based on Carrier Phase and Bayesian Estimation

Using Interchangeably the Extended Kalman Filter and Geodetic Robust Adjustment Methods to Increase the Accuracy of Surface Vehicle Positioning in the Coastal Zone

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