DOA estimation of multiple sources for a moving array in the presence of phase noise

Zhan, Si Yan; Zhang, Xiaofei; Xu, Liang

doi:10.1049/iet-spr.2018.5143

Cited by 8 publications

(3 citation statements)

References 31 publications

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“…However, the spatial constraints on the platform mean that only small aperture radars can be accommodated. With radar beam-width inversely related to antenna aperture, achieving precise angles via traditional DOA estimation techniques poses challenges [3][4][5]. This tension between the demand for precise DOA estimation-especially for coherent source DOA-and radar resource constraints underscores the limitations of current DOA methods.…”

Section: Introductionmentioning

confidence: 99%

High-Precision DOA Estimation Based on Synthetic Aperture and Sparse Reconstruction

Fang,

Wei,

2023

Sensors

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The direction-of-arrival (DOA) estimation is predominantly influenced by the antenna’s aperture size. However, space constraints on flight platforms often necessitate the use of antennas with smaller apertures and fewer array elements. This inevitably imposes limitations on the DOA estimation’s resolution and degrees of freedom. To address these precision constraints, we introduce an accurate DOA estimation method based on spatial synthetic aperture model. This method adopts a two-stage strategy to ensure both efficiency and precision in DOA estimation. Initially, the orthogonal matching pursuit (OMP) reconstruction algorithm processes the original aperture data, providing a rough estimate of target angles that guides the aircraft’s flight direction. Subsequently, the early estimations merge with the aircraft’s motion space samples, forming equivalent spatially synthesized array samples. The refined angle estimation then employs the OMP-RELAX algorithm. Moreover, with the off-grid issue in mind, we devise an estimation method integrating Bayesian parameter estimation with dictionary sequence refinement. The proposed technique harnesses the spatial synthetic aperture for pinpoint estimation, effectively addressing the challenges of atomic orthogonality and angular off-grid on estimation accuracy. Importantly, the efficiency of deploying sparse reconstruction for angle estimation is bolstered by our phased strategy, eliminating the necessity for fine grid analysis across the entire observation scene. Moreover, the poor estimation accuracy caused by coherent source targets and angular-flickering targets is improved by sparse reconstruction. Through simulation and experiment, we affirm the proposed method’s efficacy in angle estimation. The results indicate that target angle estimation errors are limited to within 1°. Furthermore, we assess the impact of variables such as target state, heading angle, spatial sampling points, and target distance on the estimation accuracy of our method, showcasing its resilience and adaptability.

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Section: Introductionmentioning

confidence: 99%

High-Precision DOA Estimation Based on Synthetic Aperture and Sparse Reconstruction

Fang,

Wei,

2023

Sensors

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“…Consequently, the final DOF of the synthetic array can be tripled without increasing the inter-sensor spacing as DNAs do. Moreover, the possible errors brought in by the array motion in the presence of phase noise have also been taken into consideration [25]. Although motions of different SLAs along the direction of the array layout have been discussed and analyzed, array motions along the vertical direction are still rarely mentioned.…”

Section: Introductionmentioning

confidence: 99%

2D DOA Estimation Exploiting Vertical Synthetic Planar Arrays

2021

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In this paper, vertical motions of sparse linear arrays (SLAs) are utilized to generate equivalent synthetic planar arrays for two-dimensional (2D) direction-of-arrival (DOA) estimation. The proposed array geometry named vertical synthetic planar array (VSPA) consists of an arbitrary SLA on the x-axis and a series of its time-shifted arrays in the vertical orientation. With the original linear array and the moving trail known, the difference coarray of VSPA can be easily obtained. By utilizing both the synthetic aperture processing and the coarray technique, VSPA has the ability to construct a synthetic planar array with only an SLA used. Compared with the traditional sparse planar arrays (SPAs), such as 2D nested array and 2D coprime array, VSPA can achieve higher degree-of-freedom and improved 2D DOA estimation performance with the same number of sensors. Moreover, as different original linear arrays and moving trails can be chosen for different applications, the construction of VSPA is of high flexibility. Numerical simulations are presented to verify the superiority of the proposed VSPA geometry over other typical SPAs.

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“…Compared with onedimensional (1-D) DOA, the 2-D DOA needs to estimate both the elevation angle and azimuth angle, so it has more superior performance in locating the directions of incident sources and wider applied situations in practice [2,3]. Over decades, a large number of high-precision algorithms have been proposed for 2-D DOA estimation, including the maximum likelihood (ML) algorithm [4][5][6], multiple signal classification (MUSIC) algorithm [7][8][9][10], Root-MUSIC [11][12][13][14] and estimation of signal parameters via rotational invariance techniques (ESPRIT) algorithm [15][16][17][18].…”

Section: Introductionmentioning

confidence: 99%

Velocity‐independent two‐dimensional direction‐of‐arrival estimation algorithm with three parallel linear arrays

Ning

Zhang

2021

IET Signal Processing

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In order to eliminate the influence of acoustic velocity variable on the estimation accuracy when the signal propagates under water, this paper proposes a velocity‐independent two‐dimensional (2‐D) direction‐of‐arrival (DOA) estimation algorithm with three parallel uniform linear arrays. Based on the double parallel linear arrays (DPLA), this algorithm adds another parallel linear array that is not in the same plane as DPLA, which is called three parallel linear arrays. By employing the matrix signal processing among those three arrays, the acoustic velocity variable can be removed from the expressions of elevation and azimuth. And the azimuth and elevation angles of the target are obtained by linear partitive operation, which does not need spectrum peak search or additional angle matching procedure. The simulation results demonstrate that the proposed algorithm performs better than the traditional 2‐D DOA algorithms in the underwater environment of unknown acoustic velocity. Compared with the velocity‐independent 2‐D DOA algorithm, it has lower computational complexity.

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DOA estimation of multiple sources for a moving array in the presence of phase noise

Cited by 8 publications

References 31 publications

High-Precision DOA Estimation Based on Synthetic Aperture and Sparse Reconstruction

High-Precision DOA Estimation Based on Synthetic Aperture and Sparse Reconstruction

2D DOA Estimation Exploiting Vertical Synthetic Planar Arrays

Velocity‐independent two‐dimensional direction‐of‐arrival estimation algorithm with three parallel linear arrays

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