Dipole Source Localization Based on Least Square Method and 3D Printing

Lin, Xin; Zhang, Yong; Ji, Mingjiang; Zheng, Xiande; Li, Kehong; Qiu, Jing; Liu, Guanjun

doi:10.1109/icma.2018.8484566

Cited by 5 publications

(7 citation statements)

References 8 publications

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“…Table 3 as follows can be a summary of this section. Flow induced by oscillating sources Tang et al 2019 [62] 8 pressure sensors Linearizing the kinematic and dynamic conditions of the free surface wave equation Yang et al 2007 [30] An array of AHC sensors Extracting velocity amplitudes at the sphere vibration frequency Yang et al 2010 [32] 15 biomimetic neuromasts Beamforming algorithm Pandya et al 2006 [44] An array of 16 hot-wire anemometers Template training approach and the modeling approach Asadnia et al 2013 [33] An array of 2 by 5 pressure sensors Measuring the maximum peak-to-peak out put of the sensors Abdulsadda et al 2011 [35] 5 IPMC sensors Neural network Abdulsadda et al 2013 [65] , Chen et al 2012 [69,70] 6 IPMC sensors Gauss Newton and Newton Raphson algorithms Ahrari et al 2016 [66] Multiple flow velocity sensors Bi-level optimization methodology Zheng et al 2018 [63] 9 underwater pressure sensors forming a cross Generalized regression neural network Lin et al 2018 [64] 9 pressure sensors in a straight line Least square method Ji et al 2018 [76] 9 pressure sensors in a straight line MUSIC, MVDR Ji et al 2019 [77] 9 pressure sensors in a straight line CRLB model…”

Section: Vortex Street Properties Detectionmentioning

confidence: 99%

“…In 2013, based on an analytical model of flow field produced by the dipole source, they presented another two schemes, Gauss Newton (GN) algorithms which were used to solve the nonlinear estimation problem by means of linear iteration and Newton Raphson (NR) The design of ALL in [63]. (e)The design of ALL in [64]. (f)An experimental prototype of IPMCbased lateral line system used in [65].…”

Section: All Based Dipole Source Detectionmentioning

confidence: 99%

“…Besides, the same group develop another ALL composed of 9 pressure sensors in a straight line (Figure 12(e)) to locate the dipole source. Lin et al modelled the pressure field of the dipole source and obtained the position through least square method by means of the information acquired by the pressure sensors [64]. Ji et al employed the same ALL and put forward a new method named MUSIC (multiple signal classification) for the purpose of locating dipole source with high-resolution based on spatial spectrum estimation.…”

Section: All Based Dipole Source Detectionmentioning

confidence: 99%

“…(d)The design of ALL in[63]. (e)The design of ALL in[64]. (f)An experimental prototype of IPMCbased lateral line system used in[65].…”

mentioning

confidence: 99%

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Fish Lateral Line Inspired Flow Sensors and Flow-aided Control: A Review

2021

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Any phenomenon in nature is potential to be an inspiration for us to propose new ideas. Lateral line is a typical example which has attracted more interest in recent years. With the aid of lateral line, fish is capable of acquiring fluid information around, which is of great significance for them to survive, communicate and hunt underwater. In this paper, we briefly introduce the morphology and mechanism of the lateral line first. Then we focus on the development of artificial lateral line which typically consists of an array of sensors and can be installed on underwater robots. A series of sensors inspired by the lateral line with different sensing principles have been summarized. And then the applications of artificial lateral line systems in hydrodynamic environment sensing and vortices detection, dipole oscillation source detection, and autonomous control of underwater robots have been reviewed. In addition, the existing problems and future foci in this field have been further discussed in detail. The current works and future foci have demonstrated that artificial lateral line has great potentials of applications and contributes to the development of underwater robots.

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Section: Vortex Street Properties Detectionmentioning

confidence: 99%

Section: All Based Dipole Source Detectionmentioning

confidence: 99%

Section: All Based Dipole Source Detectionmentioning

confidence: 99%

“…(d)The design of ALL in[63]. (e)The design of ALL in[64]. (f)An experimental prototype of IPMCbased lateral line system used in[65].…”

mentioning

confidence: 99%

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Fish Lateral Line Inspired Flow Sensors and Flow-aided Control: A Review

2021

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“…In traditional underwater detection technology, acoustic-based underwater localization techniques have been widely studied by researchers [3][4][5]. They have achieved good localization results, but near-field targets are susceptible to mutual interference, such as noise between marks [6,7]. Sonar and visual detection technology in a specific environment (narrow space, turbid waters) is ineffective.…”

Section: Introductionmentioning

confidence: 99%

Bionic Artificial Lateral Line Underwater Localization Based on the Neural Network Method

Hang

Wang

et al. 2022

Applied Sciences

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The lateral line system is an essential mechanosensory organ for organisms such as fish; it perceives the fluid environment in the near-field through the neuromasts on the lateral line system, supporting behaviors (e.g., obstacle avoidance and predation in fish). Inspired by the near-field perception ability of fish, we propose an artificial lateral line system composed of pressure sensors that respond to a target’s relative position by measuring the pressure change of the target vibration near the lateral line. Based on the shortcomings of the idealized constrained modeling approach, a multilayer perceptron network was built in this paper to process the pressure signal and predict the coordinates on a two-dimensional plane. Previous studies primarily focused on the localization of a single dipole source and rarely considered the localization of multiple vibration sources. In this paper, we explore the localization of numerous dipole sources of the same and different frequency vibrations based on the prediction of the two-dimensional coordinates of double dipoles. The experimental results show that the mutual interference of two vibration sources causes an increase in the localization error. Compared with multiple sources of vibration at the same frequency, the positioning accuracies of various vibration sources at different frequencies are higher. In addition, we explored the effects of the number of sensors on the localization results.

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Performance evaluation and analysis for dipole source localization with lateral line sensor arrays

Zhang

Zheng

et al. 2019

Meas. Sci. Technol.

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The unique mechanosensory lateral line system of fish inspires a novel and promising sensing scheme in dealing with the challenges that autonomous underwater vehicles (AUVs) face in underwater localization and navigation. In this paper, the quantitative and method-independent Cramer–Rao lower bound (CRLB) model is established to evaluate the practical performance of a lateral line sensor array (LLSA) for dipole source localization by considering the excitation pattern mismatches and the measurement noises. The effective localization area of the LLSA is studied under varying array lengths and sensor densities. Localizations for the LS (least squares) method and the MUSIC (multiple signal classification) method are compared in simulations. It is shown that the longer and denser the LLSA, the larger the effective localization area. Typically, the too separated sensor-to-sensor spacing deteriorates the near-body localization performance. The effective localization area obtained by employing the LS method matches the CRLB analysis, which also proves the validity of the analytical CRLB model. Besides, the MUSIC method presents smaller effective localization areas than the LS method. Physical experiments are also conducted and agree well with the CRLB analysis. Further study shows that the measurement noises have an equivalent effect on the excitation pattern mismatches, and can be effectively suppressed by choosing a large number of snapshots. In addition, the CRLB gives the perceptual distance that is consistent with the observation. At last, guidance on the design of a simplified LLSA with the least number of sensors and an optimal sensor-to-sensor spacing is provided for AUVs.

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Dipole Source Localization Based on Least Square Method and 3D Printing

Cited by 5 publications

References 8 publications

Fish Lateral Line Inspired Flow Sensors and Flow-aided Control: A Review

Fish Lateral Line Inspired Flow Sensors and Flow-aided Control: A Review

Bionic Artificial Lateral Line Underwater Localization Based on the Neural Network Method

Performance evaluation and analysis for dipole source localization with lateral line sensor arrays

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