Passive Towed Array Shape Estimation Using Heading and Acoustic Data

Odom, Jonathan L.; Krolik, Jeffrey L.

doi:10.1109/joe.2014.2318531

Cited by 25 publications

(13 citation statements)

References 32 publications

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“…This proves that Algorithm 1 provides a practical approach to acquire the accurate estimates of element-space waveforms, without requiring the exact hydrophone coordinates and amplitude response coefficients of the distorted towed array. Note that the time-delay estimation in Algorithm 1 can be seen as a matching filter (MF), as shown in (24). MF is a popular technique for array signal processing and is widely applied in the active sonar system, where the reference signal (transmitted signal) is known.…”

Section: A Performance Evaluation Of Iterative Algorithm For Isf Parmentioning

confidence: 99%

“…A passive sonar array often requires a large aperture, even up to several kilometers, to achieve accurate localization and high array gain [23]. This long aperture is typically formed by trailing a hydrophone array behind a towing platform in a nominally straight line [24]. In this case, the forces caused by oceanic currents and internal waves can change the shape of the towed array to some extent [25].…”

Section: Introductionmentioning

confidence: 99%

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Robust Wideband DOA Estimation Based on Element-Space Data Reconstruction in a Multi-Source Environment

Zhu

Fang

et al. 2021

IEEE Access

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In the presence of multiple sources, the performance of direction-of-arrival (DOA) estimation based on beam power maximization is susceptible to the energy leaking from the interference beams to the target beam, especially in the case that the signal of interest (SOI) is quite weak. To address this issue, a robust wideband DOA estimation method is proposed in this paper. Unlike those conventional high-resolution methods which mitigate the influence of energy leakage by reducing beamwidths and sidelobe levels, the proposed method achieves this by directly reconstructing the element-space data to approach the received hydrophone data of the single-source scenario containing only the SOI. Elementspace data reconstruction (ESDR) for the SOI is achieved by removing the element-space waveforms of all the interference signals from the received hydrophone data. Moreover, an iterative algorithm is developed to adaptively extract the element-space waveform of each interference signal, without requiring the prior information of the array amplitude response coefficients and hydrophone coordinates of a distorted towed array. Simulation results show that the proposed method outperforms its counterparts in terms of estimation accuracy for a multi-source scenario. Meanwhile, the DOA estimation performance of the proposed method in a multi-source environment is close to that obtained by the beam power maximization method in the single-source scenario, even if the signal-to-interference ratio (SIR) is as low as-25 dB. At-sea experimental results prove that, even though the number of signal sources is as many as seven and the SOI is contaminated by real ocean ambient noise, the proposed method still achieves a better DOA estimation performance compared to existing state-of-the-art methods. INDEX TERMS Distorted towed array, element-space waveform estimation, energy leakage, multi-source environment, wideband direction-of-arrival (DOA) estimation.

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Section: A Performance Evaluation Of Iterative Algorithm For Isf Parmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Robust Wideband DOA Estimation Based on Element-Space Data Reconstruction in a Multi-Source Environment

Zhu

Fang

et al. 2021

IEEE Access

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“…2a. If M = 2, these two depth sensors are placed at segments (1,6), (6,13), (1218), and (2,18). The ratio of predictor MSE to sensor MSE of each segment in these cases is plotted in Fig.…”

Section: Effect Of Choice Of Sensors' Positionsmentioning

confidence: 99%

“…The latter class has been established on the Paidoussis equation, which describes the dynamics motions of towed flexible slender cylinders in the axial flow. It uses the non-acoustic data from depth/slope sensors to estimate [13][14][15][16][17][18], whose computation complexity is lower than the computation complexity of acoustic methods especially when a sequential optimal Bayesian filter is applied. Therefore, non-acoustic methods are more applicable in most of the real-time sonar systems.…”

Section: Introductionmentioning

confidence: 99%

Approximately optimal distribution of depth sensors over towed array

Wen

Chen

2018

IET signal process.

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Towed array shape estimation aided with non-acoustic sensors is widely used for its rather low computational complexity of solutions and rather explicit results. In addition, previous studies have emphasised that depth sensors' distribution has a dramatic influence on the accuracy of this kind of array shape estimation method. Established on the basic theory of towed array shape estimation using Kalman Filters, the approximately optimal distribution of a certain number of depth sensors over a certain number of discretised towed arrays yields the approximately best achievable performance in terms of minimum space average mean square error (AMSE), is addressed in this study. The effect of depth sensors' distribution has been discussed. Then an exact expression for the space AMSE is derived. The expression is simplified in a reasonable way considering the practical issues in order to calculate the minimum space AMSE rapidly and effectively. The performance assessments demonstrate the effectiveness of the newly proposed method.

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“…They also worked on NGS for small-and medium-sized Remotely Piloted Aircraft Systems (RPAS) utilizing the GNSS-(global navigation satellite system-) and microelectromechanical system-(MEMS-) based IMU and vision-based navigation (VBN) sensor and the Aircraft Dynamics Model (ADM) that was treated as a virtual sensor [27,28]. Other research works were implemented in an underwater environment that focused on robot pose estimation [29], towed array shape estimation [30], and passive target tracking [31].…”

Section: Introductionmentioning

confidence: 99%

Design, Development, and Deployment of Real-Time Sensor Fusion (CnW + EKF) for a Linux-Based Embedded System Using Qt-Anywhere

Vista

Chong

2018

Journal of Sensors

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This paper describes the design, development, and implementation of a real-time sensor fusion system that utilizes the classification and weighing plus extended Kalman filter algorithm to derive heading for navigation using inexpensive sensors. This algorithm was previously tested only through postprocessing using MATLAB and is now reprogrammed using Qt and deployed on a Linux-based embedded board for real-time operation. Various data from inexpensive sensors such as global positioning system devices, an electronic compass, and an inertial measurement unit were utilized to ultimately derive a more reliable and accurate heading value. The algorithm flow can be described with the GPS values first being evaluated and classified which are then fused with the EC heading using classification and weighing, whose result is then passed through an EKF to fuse with the IMU data. Real-time tests and trials were done to prove the operational capability of the developed process. The complete setup and configuration processes of the systems for development and deployment via Qt are also provided for those interested to replicate the process.

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Passive Towed Array Shape Estimation Using Heading and Acoustic Data

Cited by 25 publications

References 32 publications

Robust Wideband DOA Estimation Based on Element-Space Data Reconstruction in a Multi-Source Environment

Robust Wideband DOA Estimation Based on Element-Space Data Reconstruction in a Multi-Source Environment

Approximately optimal distribution of depth sensors over towed array

Design, Development, and Deployment of Real-Time Sensor Fusion (CnW + EKF) for a Linux-Based Embedded System Using Qt-Anywhere

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