Comparative Analysis of ML-PSO DOA Estimation with Conventional Techniques in Varied Multipath Channel Environment

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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“…H are ensemble average and Hermitian operators, respectively. So the correlation matrix [29,30] can be written as…”

Section: Z(t) � G(θ)y(t) + V(t)mentioning

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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“…On the basis of electromagnetic (EM) wave radiated by hostile radiator and propagated by troposcatter, passive surveillance can realize b-LOS location [3,4]. Direction of arrival (DOA) estimation with high performance is the prerequisite of a passive surveillance system [5][6][7][8][9][10][11][12]. Intricate scattering procedure can generate multipath propagation, and scattered signals can be treated as closely spaced sources and own respective power; some signals with low signal to noise ratio (SNR) may be flooded by noises.…”

Section: Introductionmentioning

confidence: 99%

“…e DOA estimation method employed by a passive surveillance system must confront coherent signals owning different power and close DOAs. e maximum likelihood method [7] can overcome the multipath effect. Since multidimensional solution searching, its application is restricted.…”

Section: Introductionmentioning

confidence: 99%

An Efficient DOA Estimation Method for Passive Surveillance System Based on Troposcatter

Liu

Chen

et al. 2021

Mathematical Problems in Engineering

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Direction of arrival (DOA) estimation plays an important role in the passive surveillance system based on troposcatter. Rank deficiency and subspace leakage resulting from multipath propagation can deteriorate the performance of the DOA estimator. In this paper, characteristics of signals propagated by troposcatter are analyzed, and an efficient DOA estimation method is proposed. According to our new method, the invariance property of noise subspace (IPNS) is introduced as the main method. To provide precise noise subspace for INPS, forward and backward spatial smoothing (FBSS) is carried out to overcome rank deficiency. Subspace leakage is eliminated by a two-step scheme, and this process can also largely reduce the computational load of INPS. Numerical simulation results validate that our method has not only good resolution in condition of closely spaced signals but also superior performance in case of power difference.

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“…In recent years, some new bionic intelligent optimization algorithms have been proposed, such as genetic algorithm (GA) [14], particle swarm optimization (PSO) [15], differential evolution (DE) method [16], seeker optimization algorithm (SOA) [17], sine cosine algorithm (SCA) [18], invasive weed optimization (IWO) [19], squirrel search algorithm (SSA) [20], etc.. Some scholars have applied some of intelligent algorithms to ML DOA estimation and achieved better performance.…”

Section: Introductionmentioning

confidence: 99%

“…A modified and refined GA to find the exact solutions to the complex, multi-modal, multivariate and highly nonlinear likelihood function is present in [21]. In [15], a PSO ML estimator with optimizing complex nonlinear multimode functions on high dimensional spaces is presented for linear arrays. The simulation results show that PSO ML estimator has excellent statistical performance compared with the traditional DOA estimation technique in some related and coherent channel environments.…”

Section: Introductionmentioning

confidence: 99%

An Improved Squirrel Search Algorithm for Maximum Likelihood DOA Estimation and Application for MEMS Vector Hydrophone Array

Wang¹,

Kong²,

He³

et al. 2019

IEEE Access

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Maximum likelihood (ML) method for direction of arrival (DOA) estimation achieves an excellent performance in array signal processing, but the complexity and computational load of searching the multidimensional nonlinear function prevented it from practical application. Based on squirrel search algorithm (SSA), an improved SSA (ISSA) for ML DOA estimation is proposed in this paper, which can reduces the computational complexity. The idea of spatial variation and diffuse inspired by the invasive weed optimization(IWO) algorithm is applied to ISSA. The simulation experiments compared ISSA with SSA, IWO, seeker optimization algorithm(SOA), sine cosine algorithm (SCA), genetic algorithm (GA), particle swarm optimization (PSO) and differential evolution (DE) method for ML DOA estimator show that the proposed algorithm has faster convergence speed, fewer iterations and lower root mean square error(RMSE) under different number of signal sources, different signal to noise ratio(SNR) and different population size. Therefor the proposed algorithm does not only ensure the estimation accuracy, but also greatly reduce the computation complexity of multidimensional nonlinear optimization for the ML method. Finally, the test experiment using Micro Electronic Mechanical Systems(MEMS) vector hydrophone array in Fenhe lake show the engineering practicability of proposed ML DOA estimator with ISSA.The results obtained will be valuable in the application of engineering. INDEX TERMS Direction of arrival (DOA) estimation, maximum likelihood (ML), squirrel search algorithm (SSA), invasive weed optimization (IWO), micro electronic mechanical systems (MEMS) vector hydrophone.

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Comparative Analysis of ML-PSO DOA Estimation with Conventional Techniques in Varied Multipath Channel Environment

Cited by 17 publications

References 21 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

An Efficient DOA Estimation Method for Passive Surveillance System Based on Troposcatter

An Improved Squirrel Search Algorithm for Maximum Likelihood DOA Estimation and Application for MEMS Vector Hydrophone Array

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