Localization for Mixed Near-Field and Far-Field Sources by Interlaced Nested Array

Liu, Sheng; Zhao, Jing; Yuan, Zhiyong; Z, Ren; Xiao, Min; Lu, and Chunyan

doi:10.2528/pierm19042501

Cited by 5 publications

(5 citation statements)

References 18 publications

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“…In recent years, the location parameter estimation of radiation near-field (RNF) sources or radiation mixed sources has become a key research direction. Among the existing results, most of them are based on the ideal environment of the RNF source or the mixed source localization algorithm in the radiation field [10][11][12][13][14][15].…”

Section: Introductionmentioning

confidence: 99%

A High Degree of Freedom Radiation Near-Field Source Localization Algorithm with Gain–Phase Error

Zhang,

Li,

et al. 2024

Journal of Sensors

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The limitation of the number of estimable sources in the localization of radiation near-field sources with gain–phase error is examined in this paper. When only the reference element has no gain–phase error, a new method based on an accurate model is proposed to enhance the maximum number of estimable sources. Based on the location parameter details of the auxiliary source, the method first derives the gain–phase error estimate matrix. Second, the source steering vector including errors is estimated using the total least square estimating signal parameter via rotational invariance techniques (TLS-ESPRIT), and the time-shifted data matrix is built utilizing the space–time combination idea, thus increasing the degree of freedom of the array. Then, the source steering vector containing the error is modified by the error compensation matrix constructed according to the moment of gain–phase error estimation. Finally, the estimated values of the source position parameters are obtained by using the closed formula of the gain phase of the modified source steering vector and the source position parameters. The experimental results show that the maximum estimable source number of the proposed algorithm is significantly improved compared with the previous results when only the reference array element has no gain–phase error. When the array number is 5 and 9, the maximum estimable source number of the algorithm is 9 and 17, respectively.

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Section: Introductionmentioning

confidence: 99%

A High Degree of Freedom Radiation Near-Field Source Localization Algorithm with Gain–Phase Error

Zhang,

Li,

et al. 2024

Journal of Sensors

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“…By constructing a fourth‐order cumulant matrix, DOA and range can be estimated. In [21], Liu et al. proposed a fourth‐order cumulants algorithm for mixed‐field localization.…”

Section: Introductionmentioning

confidence: 99%

“…By constructing a fourth-order cumulant matrix, DOA and range can be estimated. In [21], Liu et al proposed a fourth-order cumulants algorithm for mixed-field localization. By constructing a fourth-order cumulant matrix to estimate all the DOAs, and use 1-D to estimate the range of the NF.…”

Section: Introductionmentioning

confidence: 99%

Improved symmetric flipped nested array for mixed near‐field and far‐field non‐circular sources localization

Wang

Cui

et al. 2023

IET Communications

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At present, there are few sparse arrays used in the mixed near-field (NF) and far-field (FF) localization based on non-circular (NC) signals. Inspired by the symmetric flipped nested array (SFNA) used in the existing mixed NF and FF NC source, in order to further improve the parameter estimation accuracy of the mixed NF and FF NC signal, an improved symmetric flipped nested array (ISFNA) for mixed NF and FF NC sources localization was developed. First, the uniform subarrays in the SFNA are rearranged, ⌈ N 2 2⌉ − 1 elements are extracted from the uniform subarrays and rearranged into ISFNA. ISFNA is more sparse, the array aperture is larger, and the array degree of freedom (DOF) is higher; second, the formula of the maximum consecutive lags of ISFNA is given; third, a special fourth-order cumulant is used to eliminate the range parameter and then use a one-dimensional (1-D) spectral peak search to obtain all Directions of Arrival (DOAs). By defining the range search, the range can be obtained by bringing in estimated DOAs. Finally, the superiority of the proposed array is proved by simulation.

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“…In the past years, many algorithms have emerged to solve this problem [9][10][11][12][13][14][15][16][17][18]. However, in some scenarios, such as a system for locating a speaker using a microphone array and guidance (homing), NF and FF signals exist at the same time [14].…”

Section: Introductionmentioning

confidence: 99%

Symmetric flipped nested array for mixed near‐field and far‐field non‐circular source localisation

Wang

Cui

Ba³

et al. 2022

IET Radar Sonar & Navi

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Localization for Mixed Near-Field and Far-Field Sources by Interlaced Nested Array

Cited by 5 publications

References 18 publications

A High Degree of Freedom Radiation Near-Field Source Localization Algorithm with Gain–Phase Error

A High Degree of Freedom Radiation Near-Field Source Localization Algorithm with Gain–Phase Error

Improved symmetric flipped nested array for mixed near‐field and far‐field non‐circular sources localization

Symmetric flipped nested array for mixed near‐field and far‐field non‐circular source localisation

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