Localization for mixed far-field and near-field sources utilizing improved symmetric nested array

Shen, Jiajun; Zhou, Tian; Xu, Chao; Zhang, Wanyuan; Du, Weidong

doi:10.1016/j.dsp.2020.102879

Cited by 10 publications

(15 citation statements)

References 37 publications

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“…In the last part, the superiority of the proposed array is verified by some performance simulation experiments, which are compared with the other three array geometries, SNA [29], symmetric double nested array (SDNA) [30], and ISNA [23]. The total number of elements is Q = 31.…”

Section: Simulation Resultsmentioning

confidence: 95%

“…To better quantify the performance of STCA, we compare it with SNA [29], SDNA [30], improve symmetric nested array (ISNA) [23] in four aspects: the number of consecutive lags, the number of unique lags, physical array aperture, and mutual coupling coefficient for different total numbers of physical sensors, Q .…”

Section: Symmetric Thined Coprime Arraymentioning

confidence: 99%

“…Using the consecutive lags of the array will lose the degree of freedom of the array, and the estimation performance of the SS‐MUSIC algorithm is not as good as that of the Sparse Reconstruction algorithm. Therefore, we choose Sparse Reconstruction algorithm as the DOA estimation of this article [2, 23].…”

Section: The Proposed Algorithmmentioning

confidence: 99%

“…But in some applications such as speaker localization with microphone arrays, both NF and FF exist, and the performance of the above methods will decline. In fact, mixed sources localization algorithms have also been proposed [19][20][21][22][23][24], but most of them are based on a symmetric uniform linear or symmetric nested array (SNA), and a symmetric coprime array with a larger inter-sensor spacing is rarely considered.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Symmetric thinned coprime array with reduced mutual coupling for mixed near‐field and far‐field sources localization

Wang

Cui

Yang

et al. 2022

IET Radar Sonar & Navi

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As we all know, the non‐uniform array is widely used in the mixed near‐field (NF) and far‐field sources localization. The nested array contains a uniform linear array, it is easy to be affected by mutual coupling, so we propose a symmetric thinned coprime array (STCA) to reduce the mutual coupling effect of mixed source localization. In this paper, the STCA configuration consists of two sparse uniform linear arrays, the first subarray is composed of 2N − 1 sensors, and the sensor element spacing is Md. The second subarray is composed of 2M+2⌊M2⌋ $2M+2\lfloor \frac{M}{2}\rfloor $ sensors, and the sensor element spacing are Nd and Md respectively. The two subarrays form the symmetric coprime array, which shares a reference sensor. Under the same number of physical array sensors, compared with the latest symmetric nested array, although STCA has lower consecutive lags, the array sensors have larger inter‐sensor spacing and larger physical array aperture, which can significantly reduce the mutual coupling effect between physical sensors, and better estimation performance of direction‐of‐arrival (DOA) estimation can be achieved. Finally, simulation results show that STCA can achieve better performance than other symmetric nested arrays under the same array sensors and mutual coupling effects.

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Section: Simulation Resultsmentioning

confidence: 95%

Section: Symmetric Thined Coprime Arraymentioning

confidence: 99%

Section: The Proposed Algorithmmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Symmetric thinned coprime array with reduced mutual coupling for mixed near‐field and far‐field sources localization

Wang

Cui

Yang

et al. 2022

IET Radar Sonar & Navi

View full text Add to dashboard Cite

show abstract

“…In this section, through the different simulations to assess the performance of the proposed algorithm. Specifically, we compare the proposed algorithm with oblique projection MU-SIC (OPMUSIC) algorithm [14], Mixed-order MUSIC algorithm [19], MSA algorithm [25] and LASSO algorithm [21]. In all simulations, the inter-sensor spacing is d = λ/4, the signal model is e jϕt where the phase is uniformly distributed in [0, 2π], and the parameter ε in ( 17) is set to 10 −8 .…”

Section: Simulation Resultsmentioning

confidence: 99%

A Mixed-Field Sources Localization Algorithm Based on High-order Cumulant Matrix Reconstruction for General Symmetric Array

Lin

Jin

et al. 2023

Preprint

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Sparse arrays have obvious advantages in mixed-field localization applications because the better estimation accuracy can be obtained by using consective lags. However, existing algorithms can not fully utilize the information provided by sparse arrays. In this paper, an interpolation processing method based on atomic norm is proposed to solve the sparse array localization problem. The high-order cumulant matrix is reconstructed by the interpolation method to generate an augmented cumulant matrix without holes, which can make full use of all the lags. Then, the atomic norm minimization (ANM) method is used to recover the sparse matrix after interpolation in a gridless way. The matrix after recovery enables off-grid direction-of-arrival (DOA) estimation. After the interpolation reconstruction, more consecutive lags can be exploited, the degrees of freedom (DOFs) are further increased, and the DOA estimation accuracy is also improved. Numerical simulations verify the superiority of the proposed algorithm compared with the existing algorithms.

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A High-Precision Two-Dimensional DOA Estimation Algorithm with Parallel Coprime Array

Chen

Zang

et al. 2022

Circuits Syst Signal Process

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Localization for mixed far-field and near-field sources utilizing improved symmetric nested array

Cited by 10 publications

References 37 publications

Symmetric thinned coprime array with reduced mutual coupling for mixed near‐field and far‐field sources localization

Symmetric thinned coprime array with reduced mutual coupling for mixed near‐field and far‐field sources localization

A Mixed-Field Sources Localization Algorithm Based on High-order Cumulant Matrix Reconstruction for General Symmetric Array

A High-Precision Two-Dimensional DOA Estimation Algorithm with Parallel Coprime Array

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