Analysis of error sources in underwater localization systems

Cario, Gianni; Casavola, Alessandro; Gagliardi, Gianfranco; Lupia, Marco; Severino, Umberto; Bruno, Fabio

doi:10.1109/oceanse.2019.8867536

Cited by 11 publications

(13 citation statements)

References 2 publications

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“…As the actual application environment is known, the sound speed is measured and fixed. If the time of signal transmission and reception and the speed of sound in the medium are known, the distance between the transmitter and the receiver can be calculated [8]. In this way, not only can the observability be maintained under the condition of infrequently changing formation, but the complexity of underwater acoustic communication can also be reduced [9,10].…”

Section: Introductionmentioning

confidence: 99%

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: Introductionmentioning

confidence: 99%

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

Zhang

2022

Sensors

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“…In addition, the limited precision of these auxiliary sensors makes it difficult to accurately estimate the array shape in real-time application [9,10]. The source-dependent methods, in essence, measure the relative time or phase delays among sensors by using one or more sources with known or unknown directions based on underwater acoustic data [11][12][13][14][15][16][17][18][19][20][21][22][23][24][25][26][27][28]. The single and double near-field source-dependent method is used for towed array shape estimation [11].…”

Section: Introductionmentioning

confidence: 99%

“…The single and double near-field source-dependent method is used for towed array shape estimation [11]. Error sources in the localization systems are analyzed to reduce the impact on final estimation of array shape [12]. The Kalman filters theoretical model is used to address the towed array shape estimation [13].…”

Section: Introductionmentioning

confidence: 99%

A Nonlinear Data-Driven Towed Array Shape Estimation Method Using Passive Underwater Acoustic Data

2022

Remote Sensing

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Large-aperture towed linear hydrophone array has been widely used for beamforming-based signal enhancement in passive sonar systems; however, its performance can drastically decrease due to the array distortion caused by rapid tactical maneuvers of the towed platform, oceanic currents, hydrodynamic effects, etc. In this paper, an enhanced data-driven shape array estimation scheme is provided in the passive underwater acoustic data, and a novel nonlinear outlier-robust particle filter (ORPF) method is proposed to acquire enhanced estimates of time delays in the presence of distorted hydrophone array. A conventional beamforming technique based on a hypothetical array is first used, and the detection of the narrow-band components is sequentially carried out so that the corresponding amplitudes and phases at these narrow-band components can be acquired. We convert the towed array estimation problem into a nonlinear discrete-time filtering problem with the joint estimates of amplitudes and time-delay differences, and then propose the ORPF method to acquire enhanced estimates of the time delays by exploiting the underlying properties of slowly changing time-delay differences across sensors. The proposed scheme fully exploits directional radiated noise targets as sources of opportunity for online array shape estimation, and thus it requires neither the number nor direction of sources to be known in advance. Both simulations and real experimental data show the effectiveness of the proposed method.

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“…Some preliminary results of this work have been published in [ 9 ]. In this respect, this paper represents an extended version containing enlarged domains of applicability, additional technical details on the practicability of the proposed simulation environment, and a comprehensive set of simulations, allowing the assessment of the approach, carried out with data acquired from real diving sessions.…”

Section: Introductionmentioning

confidence: 99%

“…The simulator therefore has the purpose of simulating the hardware system and modifying some of its parameters, such as the base-line length and the error on the GPS and IMU units, in order to understand how to act to reduce the accuracy error of the entire positioning system. Some preliminary results of this work have been published in [9]. In this respect, this paper represents an extended version containing enlarged domains of applicability, additional technical details on the practicability of the proposed simulation environment, and a comprehensive set of simulations, allowing the assessment of the approach, carried out with data acquired from real diving sessions.…”

Section: Introductionmentioning

confidence: 99%

Accurate Localization in Acoustic Underwater Localization Systems

Cario

Casavola

Gagliardi

et al. 2021

Sensors

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In underwater localization systems several sources of error may impact in different ways the accuracy of the final position estimates. Through simulations and statistical analysis it is possible to identify and characterize such sources of error and their relative importance. This is especially of use when an accurate localization system has to be designed within required accuracy prescriptions. This approach allows one to also investigate how much these sources of error influence the final position estimates achieved by an Extended Kalman Filter (EKF). This paper presents the results of experiments designed in a virtual environment used to simulate real acoustic underwater localization systems. The paper intends to analyze the main parameters that significantly influence the position estimates achieved by a Short Baseline (SBL) system. Specifically, the results of this analysis are presented for a proprietary localization system constituted by a surface platform equipped with four acoustic transducers used for the localization of an underwater target. The simulator here presented has the purpose of simulating the hardware system and modifying some of its design parameters, such as the base-line length and the errors on the GPS and Inertial Measurement Unit (IMU) units, in order to understand which parameters have to modify for improving the accuracy of the entire positioning system. It is shown that statistical analysis techniques can be of help in determining the best values of these parameters that permit to improve the performance of a real hardware system.

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Analysis of error sources in underwater localization systems

Cited by 11 publications

References 2 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

A Nonlinear Data-Driven Towed Array Shape Estimation Method Using Passive Underwater Acoustic Data

Accurate Localization in Acoustic Underwater Localization Systems

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