Performance Analysis of Efficient Computing Techniques for Direction of Arrival Estimation of Underwater Multi Targets

Ahmed, Nauman; Wang, Qianqian; Raja, Muhammad Asif Zahoor; Ali, Wasiq; Zaman, Fawad; Khan, Wasim; He, Yigang

doi:10.1109/access.2021.3060819

Cited by 21 publications

(4 citation statements)

References 66 publications

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“…Swarming intelligence of evolutionary algorithms is a signi cant development in signal processing for direction of arrival (DOA) estimation of underwater multitargets [1,2]. For solving such problems, subspace-based methods were used like multiple signal classi cation (MUSIC) [3]. If used in a constraint environment like assuming incoherent sources, with a specified number of snapshots and high SNR signals, these methods give good results.…”

Section: Introductionmentioning

confidence: 99%

High-Resolution Direction of Arrival Estimation of Underwater Multitargets Using Swarming Intelligence of Flower Pollination Heuristics

Ahmed

Wang

et al. 2022

Shock and Vibration

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Developing the parameter estimation, particularly direction of arrival (DOA), utilizing the swarming intelligence-based flower pollination algorithm (FPA) is considered an optimistic solution. Therefore, in this paper, the features of FPA are applied for viable DOA in the case of several robust underwater scenarios. Moreover, acoustic waves impinging from the far-field multitarget are evaluated using the different number of hydrophones of uniform linear array (ULA). The measuring parameters like robustness against noise and element quantity, estimation accuracy, computation complexity, various numbers of hydrophones, variability analysis, frequency distribution and cumulative distribution function of root mean square error (RMSE), and resolution ability are applied for analyzing the performance of the proposed model with additive white Gaussian noise (AWGN). For this purpose, particle swarm optimization (PSO), minimum variance distortion-less response (MVDR), multiple signal classification (MUSIC), and estimation of signal parameter via rotational invariance technique (ESPRIT) standard counterparts are employed along with Crammer–Rao bound (CRB) to improve the worth of the proposed setup further. The proposed scheme for estimating the DOA generates efficient outcomes compared to the state-of-the-art algorithms over the Monte Carlo simulations.

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Section: Introductionmentioning

confidence: 99%

High-Resolution Direction of Arrival Estimation of Underwater Multitargets Using Swarming Intelligence of Flower Pollination Heuristics

Ahmed

Wang

et al. 2022

Shock and Vibration

Self Cite

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“…In future, the accessible MWNN-GA-ASA is promoted to solve the singular higher order, fractional models, smart cities model, and fluid dynamics systems [126][127][128][129][130][131][132][133][134][135][136][137][138][139][140][141][142][143].…”

Section: Acknowledgmentmentioning

confidence: 99%

IoT Technology Enabled Heuristic Model With Morlet Wavelet Neural Network for Numerical Treatment of Heterogeneous Mosquito Release Ecosystem

Sabir

Nisar²,

Raja

et al. 2021

IEEE Access

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The utmost advancements of artificial neural networks (ANNs), software-defined networks (SDNs) and internet of things (IoT) technologies find beneficial in different applications of the smart healthcare sector. Aiming at modern technology's use in the future development of healthcare, this paper presents an advanced heuristic based on Morlet wavelet neural network for solving the mosquito release ecosystem in a heterogeneous atmosphere. The mosquito release ecosystem is dependent of six classes, eggs density, larvae density, pupae density, mosquitoes searching for hosts density, resting mosquito's density and mosquitoes searching for ovipositional site density. An artificial neural network with the layer structure of Morlet wavelet (MWNN) kernel is presented using the global and local search optimization schemes of genetic algorithm (GA) and active-set algorithm (ASA), i.e., MWNN-GA-ASA. The accurateness, reliability and constancy of the proposed MWNN-GA-ASA is established through comparative examinations with Adams method based numerical results to solve the proposed nonlinear system with matching of order 10 -06 to 10 -09 . The accuracy and convergence of the proposed MWNN-GA-ASA is certified using the statistical operators based on root mean square error (RMSE), Theil's inequality coefficient (T.I.C) and mean absolute deviation (MAD) operators.INDEX TERMS Mosquito release ecosystem, IoT, SDN, artificial neural networks, heuristic algorithm, Adams's method.

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“…Ahmed et al conducted a comparative study of deterministic and heuristic algorithms for viable DOA estimation for different dynamic objects in underwater environments. To achieve the precise positioning of underwater targets at a close range [22], Ahmed et al utilized the Cuckoo Search Algorithm (CSA) and swarm intelligence to optimize DOA estimation with a Uniform Linear Array (ULA) in various underwater scenarios [23]. An et al proposed a combination of a linear array composed of multiple mutually perpendicular sub-arrays, overcoming the ambiguity of a single linear array's port and starboard orientation [24].…”

Section: Introductionmentioning

confidence: 99%

Research on High Robustness Underwater Target Estimation Method Based on Variational Sparse Bayesian Inference

Wang

et al. 2023

Remote Sensing

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Pulse noise (such as glacier fracturing and offshore pile driving), commonly seen in the marine environment, seriously affects the performance of Direction-of-Arrival (DOA) estimation methods in sonar systems. To address this issue, this paper proposes a high robustness underwater target estimation method based on variational sparse Bayesian inference by studying and analyzing the sparse prior assumption characteristics of signals. This method models pulse noise to build an observation signal, completes the derivation of the conditional distribution of the observed variables and the prior distribution of the sparse signals, and combines Variational Bayes (VB) theory to approximate the posterior distribution, thereby obtaining the recovered signal of the sparse signals and reducing the impact of pulse noise on the estimation system. Our simulation results showed that the proposed method achieved higher estimation accuracy than traditional methods in both single and multiple snapshot scenarios and has practical potential.

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Performance Analysis of Efficient Computing Techniques for Direction of Arrival Estimation of Underwater Multi Targets

Cited by 21 publications

References 66 publications

High-Resolution Direction of Arrival Estimation of Underwater Multitargets Using Swarming Intelligence of Flower Pollination Heuristics

High-Resolution Direction of Arrival Estimation of Underwater Multitargets Using Swarming Intelligence of Flower Pollination Heuristics

IoT Technology Enabled Heuristic Model With Morlet Wavelet Neural Network for Numerical Treatment of Heterogeneous Mosquito Release Ecosystem

Research on High Robustness Underwater Target Estimation Method Based on Variational Sparse Bayesian Inference

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