DOA Estimation with Nonuniform Moving Sampling Scheme Based on a Moving Platform

Hantian Wu; Qing Shen; Wei Cui; Wei Liu

doi:10.1109/LSP.2021.3105035

DOA Estimation with Nonuniform Moving Sampling Scheme Based on a Moving Platform

Hantian Wu^*, Qing Shen, Wei Cui, Wei Liu

^*Corresponding author for this work

School of Information and Electronics

Research output: Contribution to journal › Article › peer-review

14 Citations (Scopus)

Abstract

The generalized linear moving sampling scheme (MSS) exploiting the second-order statistics and also the high-order cumulants is studied, where the set of MSS is defined as the shifted distance offsets involved in estimation based on a moving platform. Then, sparse physical arrays (SPAs) with nonuniform linear moving sampling schemes (NL-MSS), referred to as SPA-NL-MSS, are proposed to optimize the consecutive difference co-arrays. For the same number of sensors and data samples, better performance in terms of both the number of degrees of freedom (DOFs) and estimation accuracy can be achieved by SPA-NL-MSS than existing array structures exploiting array motions at the second order level.

Original language	English
Pages (from-to)	1714-1718
Number of pages	5
Journal	IEEE Signal Processing Letters
Volume	28
DOIs	https://doi.org/10.1109/LSP.2021.3105035
Publication status	Published - 2021

Keywords

DOA estimation
Moving platform
difference co-array
nonuniform moving sampling scheme
sparse array

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10.1109/LSP.2021.3105035

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abstract = "The generalized linear moving sampling scheme (MSS) exploiting the second-order statistics and also the high-order cumulants is studied, where the set of MSS is defined as the shifted distance offsets involved in estimation based on a moving platform. Then, sparse physical arrays (SPAs) with nonuniform linear moving sampling schemes (NL-MSS), referred to as SPA-NL-MSS, are proposed to optimize the consecutive difference co-arrays. For the same number of sensors and data samples, better performance in terms of both the number of degrees of freedom (DOFs) and estimation accuracy can be achieved by SPA-NL-MSS than existing array structures exploiting array motions at the second order level.",

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author = "Hantian Wu and Qing Shen and Wei Cui and Wei Liu",

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AU - Cui, Wei

AU - Liu, Wei

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N2 - The generalized linear moving sampling scheme (MSS) exploiting the second-order statistics and also the high-order cumulants is studied, where the set of MSS is defined as the shifted distance offsets involved in estimation based on a moving platform. Then, sparse physical arrays (SPAs) with nonuniform linear moving sampling schemes (NL-MSS), referred to as SPA-NL-MSS, are proposed to optimize the consecutive difference co-arrays. For the same number of sensors and data samples, better performance in terms of both the number of degrees of freedom (DOFs) and estimation accuracy can be achieved by SPA-NL-MSS than existing array structures exploiting array motions at the second order level.

AB - The generalized linear moving sampling scheme (MSS) exploiting the second-order statistics and also the high-order cumulants is studied, where the set of MSS is defined as the shifted distance offsets involved in estimation based on a moving platform. Then, sparse physical arrays (SPAs) with nonuniform linear moving sampling schemes (NL-MSS), referred to as SPA-NL-MSS, are proposed to optimize the consecutive difference co-arrays. For the same number of sensors and data samples, better performance in terms of both the number of degrees of freedom (DOFs) and estimation accuracy can be achieved by SPA-NL-MSS than existing array structures exploiting array motions at the second order level.

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KW - Moving platform

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KW - sparse array

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SP - 1714

EP - 1718

JO - IEEE Signal Processing Letters

JF - IEEE Signal Processing Letters

ER -

DOA Estimation with Nonuniform Moving Sampling Scheme Based on a Moving Platform

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Keywords

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