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A Robust Direction of Arrival Estimation Method for Coherently Distributed Sources in an Impulsive Noise Environment

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Title: A Robust Direction of Arrival Estimation Method for Coherently Distributed Sources in an Impulsive Noise Environment
Authors: Liu, Yapeng, Gao, Hongyuan, Chen, Menghan, Jakobsson, Andreas, Cheng, Jianhua
Contributors: Lund University, Profile areas and other strong research environments, Lund University Profile areas, LU Profile Area: Natural and Artificial Cognition, Lunds universitet, Profilområden och andra starka forskningsmiljöer, Lunds universitets profilområden, LU profilområde: Naturlig och artificiell kognition, Originator, Lund University, Faculty of Engineering, LTH, LTH Profile areas, LTH Profile Area: AI and Digitalization, Lunds universitet, Lunds Tekniska Högskola, LTH profilområden, LTH profilområde: AI och digitalisering, Originator, Lund University, Profile areas and other strong research environments, Strategic research areas (SRA), ELLIIT: the Linköping-Lund initiative on IT and mobile communication, Lunds universitet, Profilområden och andra starka forskningsmiljöer, Strategiska forskningsområden (SFO), ELLIIT: the Linköping-Lund initiative on IT and mobile communication, Originator, Lund University, Profile areas and other strong research environments, Strategic research areas (SRA), eSSENCE: The e-Science Collaboration, Lunds universitet, Profilområden och andra starka forskningsmiljöer, Strategiska forskningsområden (SFO), eSSENCE: The e-Science Collaboration, Originator, Lund University, Faculty of Science, Centre for Mathematical Sciences, Mathematical Statistics, Lunds universitet, Naturvetenskapliga fakulteten, Matematikcentrum, Matematisk statistik, Originator, Lund University, Faculty of Science, Centre for Mathematical Sciences, Research groups at the Centre for Mathematical Sciences, Statistical Signal Processing Group, Lunds universitet, Naturvetenskapliga fakulteten, Matematikcentrum, Forskargrupper vid Matematikcentrum, -lup-obsolete, Originator
Source: IEEE Sensors Journal. 23(13):14375-14387
Subject Terms: Engineering and Technology, Electrical Engineering, Electronic Engineering, Information Engineering, Signal Processing, Teknik, Elektroteknik och elektronik, Signalbehandling
Description: In this work, a computationally efficient evolutionary algorithm is proposed for estimating the direction of arrival (DOA) of coherently distributed (CD) sources corrupted by additive impulsive noise. The typical method, such as distributed signal parameter estimation (DSPE) method, requires a 2-D spectral peak search and cannot allow for coherent signals. The proposed method in this article uses an infinite norm (IN) normalization combined with the maximum likelihood (ML) criteria. The resulting cost function is solved using the introduced multimodal quantum-inspired benchmarking algorithm (MQBA), which obviously reduces the computational complexity without grid errors. The Cramer-Rao bound (CRB) for the considered DOA estimation problem is also derived. Finally, numerical simulations are conducted to show that our algorithm can perform superior robustness and allow for coherent signals without any additional process compared with alternative approaches for the considered scenarios. In addition, the proposedscheme can be popularized to address other DOA estimation problems and promote the development of DOA estimation.
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  Data: A Robust Direction of Arrival Estimation Method for Coherently Distributed Sources in an Impulsive Noise Environment
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  Data: <searchLink fieldCode="AR" term="%22Liu%2C+Yapeng%22">Liu, Yapeng</searchLink><br /><searchLink fieldCode="AR" term="%22Gao%2C+Hongyuan%22">Gao, Hongyuan</searchLink><br /><searchLink fieldCode="AR" term="%22Chen%2C+Menghan%22">Chen, Menghan</searchLink><br /><searchLink fieldCode="AR" term="%22Jakobsson%2C+Andreas%22">Jakobsson, Andreas</searchLink><br /><searchLink fieldCode="AR" term="%22Cheng%2C+Jianhua%22">Cheng, Jianhua</searchLink>
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  Data: Lund University, Profile areas and other strong research environments, Lund University Profile areas, LU Profile Area: Natural and Artificial Cognition, Lunds universitet, Profilområden och andra starka forskningsmiljöer, Lunds universitets profilområden, LU profilområde: Naturlig och artificiell kognition, Originator<br />Lund University, Faculty of Engineering, LTH, LTH Profile areas, LTH Profile Area: AI and Digitalization, Lunds universitet, Lunds Tekniska Högskola, LTH profilområden, LTH profilområde: AI och digitalisering, Originator<br />Lund University, Profile areas and other strong research environments, Strategic research areas (SRA), ELLIIT: the Linköping-Lund initiative on IT and mobile communication, Lunds universitet, Profilområden och andra starka forskningsmiljöer, Strategiska forskningsområden (SFO), ELLIIT: the Linköping-Lund initiative on IT and mobile communication, Originator<br />Lund University, Profile areas and other strong research environments, Strategic research areas (SRA), eSSENCE: The e-Science Collaboration, Lunds universitet, Profilområden och andra starka forskningsmiljöer, Strategiska forskningsområden (SFO), eSSENCE: The e-Science Collaboration, Originator<br />Lund University, Faculty of Science, Centre for Mathematical Sciences, Mathematical Statistics, Lunds universitet, Naturvetenskapliga fakulteten, Matematikcentrum, Matematisk statistik, Originator<br />Lund University, Faculty of Science, Centre for Mathematical Sciences, Research groups at the Centre for Mathematical Sciences, Statistical Signal Processing Group, Lunds universitet, Naturvetenskapliga fakulteten, Matematikcentrum, Forskargrupper vid Matematikcentrum, -lup-obsolete, Originator
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  Data: In this work, a computationally efficient evolutionary algorithm is proposed for estimating the direction of arrival (DOA) of coherently distributed (CD) sources corrupted by additive impulsive noise. The typical method, such as distributed signal parameter estimation (DSPE) method, requires a 2-D spectral peak search and cannot allow for coherent signals. The proposed method in this article uses an infinite norm (IN) normalization combined with the maximum likelihood (ML) criteria. The resulting cost function is solved using the introduced multimodal quantum-inspired benchmarking algorithm (MQBA), which obviously reduces the computational complexity without grid errors. The Cramer-Rao bound (CRB) for the considered DOA estimation problem is also derived. Finally, numerical simulations are conducted to show that our algorithm can perform superior robustness and allow for coherent signals without any additional process compared with alternative approaches for the considered scenarios. In addition, the proposedscheme can be popularized to address other DOA estimation problems and promote the development of DOA estimation.
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