Second-Order Approximation for DOA Estimation of Near-Field Sources

Adachi, Yumiko; Iiguni, Youji; Maeda, Hajime

doi:10.1007/s00034-004-7032-2

Cited by 4 publications

(2 citation statements)

References 7 publications

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“…For far-field source scenarios, only first-order Taylor series are considered, in which the cosine direction is linear to differences in the array phase. Nevertheless, for near-field source situations, the second-order Taylor series are retained [ 26 ], and this is known as the Fresnel model. Herein, the difference in the array phase is a nonlinear function of the cosine direction and the distances between the source and the sensors.…”

Section: Far-field Near-field and Hybrid-fieldmentioning

confidence: 99%

DOA Estimation in B5G/6G: Trends and Challenges

Ruan

Wang

Wen

et al. 2022

Sensors

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Direction-of-arrival (DOA) estimation is the preliminary stage of communication, localization, and sensing. Hence, it is a canonical task for next-generation wireless communications, namely beyond 5G (B5G) or 6G communication networks. Both massive multiple-input multiple-output (MIMO) and millimeter wave (mmW) bands are emerging technologies that can be implemented to increase the spectral efficiency of an area, and a number of expectations have been placed on them for future-generation wireless communications. Meanwhile, they also create new challenges for DOA estimation, for instance, through extremely large-scale array data, the coexistence of far-field and near-field sources, mutual coupling effects, and complicated spatial-temporal signal sampling. This article discusses various open issues related to DOA estimation for B5G/6G communication networks. Moreover, some insights on current advances, including arrays, models, sampling, and algorithms, are provided. Finally, directions for future work on the development of DOA estimation are addressed.

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Section: Far-field Near-field and Hybrid-fieldmentioning

confidence: 99%

DOA Estimation in B5G/6G: Trends and Challenges

Ruan

Wang

Wen

et al. 2022

Sensors

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“…The in (21) denotes the th-order approximation of the exact temporal delay of (18). Moreover, and are already given in (8) for the Fresnel approximation.…”

Section: A the Th-order Mismatched Measurement-modelmentioning

confidence: 99%

Mismatch of Near-Field Bearing-Range Spatial Geometry in Source-Localization by a Uniform Linear Array

Hsu

Wong

Yeh

2011

IEEE Trans. Antennas Propagat.

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Many near-field source-localization algorithms intentionally simplifies the exact spatial geometry among the emitter and the sensors, in order to speed up the signal-processing involved. For example, the Fresnel approximation is a second order Taylorseries approximation. Such intentional approximation introduces a systemic error in the algorithm's modeling of the actual objective reality from which the measured data arise. A mismatch thus exists between the algorithm's presumptions versus the data it processes. This modeling-mismatch will introduce a systematic bias in the bearing-range estimates of the near-field source-localization algorithm. This bias is non-random, and adds towards the random estimation-errors due to the additive and/or multiplicative noises. The open literature currently offers no rigorous mathematical analysis on this issue. This proposed project aims to fill this literature gap, by deriving explicit formulas of the degrading effects in three-dimensional source-localization, due to approximating the source/sensor geometry by any order of the Taylor's series expansion.Index Terms-Acoustic interferometry, array signal processing, direction of arrival estimation, interferometry, linear arrays, nearfield far-field transformation, phased arrays, sonar arrays, underwater acoustic arrays.

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