Abstract
Parameter estimation of Direction of Arrival (DOA) using deterministic and stochastic computing paradigms is an enabling development for underwater acoustic signal processing beside its applications in the field of seismology, astronomy, earthquake and bio-medicine. In this work, the comparative study between state of the art deterministic and heuristics algorithms is presented for viable DOA estimation for different underwater dynamic objects. A Uniform Linear Array (ULA) of eight hydrophones is used for impinging acoustic waves from far-field targets. In order to evaluate the performance, the viability of innovative statistical indices is utilized to explain. Performance analysis of Genetic Algorithm(GA) and Particle Swarm Optimization(PSO) is conducted with standard counterparts including MVDR, MUSIC, ESPRIT and UESPRIT for different number of targets in terms of estimation accuracy, robustness against the number of elements and noise, cumulative distribution function of Root Mean Sqaure Error(RMSE), frequency distribution of the RMSE over the monte carlo trials, the resolution ability and computational complexity in the presence of white Gaussian measurement noise. Crammer Rao Bound (CRB) based analysis is also performed for the validation assessments and results on Monte Carlo simulations depict that the Genetic Algorithm(GA) showed the outperform counterparts on precision, convergence and complexity indices.
Highlights
Acoustics are profoundly used in underwater applications due to its significant characteristics of propagation in water
Comparison of the GA and PSO algorithms under the criteria of performance metrics in terms of probability of resolution, computational complexity, estimation accuracy, variability of RMSE over the monte carlo runs, robustness against noise and elements validate its worth over state of the art counterparts including MINIMUM VARIANCE DISTORTIONLESS RESPONSE (MVDR), Multiple Signal Classification (MUSIC), ESPRIT UESPRIT
MAIN ACHIEVEMENTS We presented the GA and PSO algorithms based on the optimization strength of heurisctics of swarming intelligence for the Direction of Arrival (DOA) parameter estimation of multiple underwater dynamic objects
Summary
Acoustics are profoundly used in underwater applications due to its significant characteristics of propagation in water. The aim of the presented study is to exploit the strength of modern computing paradigm via GA and PSO for accurate and viable DOA estimation and their analysis in terms of estimation accuracy, robustness against elements and noise along with the validation of CRB for minimum variance in case of low SNR based scenarios for multiple underwater dynamic objects. Comparison of the GA and PSO algorithms under the criteria of performance metrics in terms of probability of resolution, computational complexity, estimation accuracy, variability of RMSE over the monte carlo runs, robustness against noise and elements validate its worth over state of the art counterparts including MVDR, MUSIC, ESPRIT UESPRIT. The results of probability of resolution for closely spaced targets reveals that the GA outperform under sever underwater conditions exclusively for low SNR using fewer snapshots
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