Unitary ESPRIT-Based DOA Estimation Using Sparse Linear Dual Size Spatial Invariance Array

Vasylyshyn, Volodymyr

doi:10.1109/eurad.2005.1605589

Cited by 11 publications

(10 citation statements)

References 6 publications

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“…where the superscript H is the Hermitian operator. Following [4], let E s ∈ C N×K be the signal subspace matrix composed of the K eigenvectors corresponding to the K largest eigenvalues ofR. And E s has the same signal Algorithm 1 Proposed DOA estimation algorithm 1: Estimate the two sets of high-accuracy but cyclically ambiguous y-axis direction cosine v estimations by the two sub-arrays placed along the y-axis using the ESPRIT algorithm [33].…”

Section: Esprit-based Methods To Estimate the Two Sets Of High-accuracmentioning

confidence: 99%

“…It can be observed that both u final and v final improve significantly from their coarse estimates, u coarse and v coarse , respectively; both of them are getting closer to their CRB. Moreover, the disambiguation described in Section 3.3 is similar to that of dual-size ESPRIT [4]. There exists a SNR threshold in the process of disambiguation [39].…”

Section: Performance Versus Snrmentioning

confidence: 99%

“…In order to mitigate this issue, various sparse array configurations and the corresponding DOA estimation algorithms have been developed. One *Correspondence: mlyang@xidian.edu.cn 1 National Laboratory of Radar Signal Processing, Xidian University, Xi'an, China Full list of author information is available at the end of the article type of sparse array is constructed by multiple widely separated sub-arrays [3][4][5], and the corresponding estimation of signal parameters via rotation invariant technique (ESPRIT)-based algorithms which used the dual-size or multiple-size invariance within these arrays were developed therein. Another type is designed to obtain as many as degrees-of-freedom (DOFs) to resolve more sources than sensors, such as the minimum-redundancy array [6], the nested array [7], and the co-prime array [8].…”

Section: Introductionmentioning

confidence: 99%

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A single triangular SS-EMVS aided high-accuracy DOA estimation using a multi-scale L-shaped sparse array

Ding¹,

Yang²,

Chen³

et al. 2019

EURASIP J. Adv. Signal Process.

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We propose a new array configuration composed of multi-scale scalar arrays and a single triangular spatially spread electromagnetic-vector-sensor (SS-EMVS) for high-accuracy two-dimensional (2D) direction-of-arrival (DOA) estimation. Two scalar arrays are placed along x-axis and y-axis, respectively, each array consists of two uniform linear arrays (ULAs), and these two ULAs have different inter-element spacings. In this manner, these two scalar arrays form a multi-scale L-shaped array. The two arms of this L-shaped scalar array are connected by a six-component SS-EMVS, which is composed of a spatially spread dipole-triad plus a spatially spread loop-triad. All the inter-element spacings in our proposed array can be larger than a half-wavelength of the incident source, thus to form a sparse array to mitigate the mutual coupling across antennas. In the proposed DOA estimation algorithm, we perform the vector-cross-product algorithm to the SS-EMVS to obtain a set of low-accuracy but unambiguous direction cosine estimation as a reference; we then impose estimation of signal parameters via rotation invariant technique (ESPRIT) algorithm to the two scalar arrays to get two sets of high-accuracy but cyclically ambiguous direction cosine estimations. Finally, the coarse estimation is used to disambiguate the fine but ambiguous estimations progressively and therefore a multiple-order disambiguation algorithm is developed. The proposed array enjoys the superiority of low redundancy and low mutual coupling. Moreover, the thresholds of the inter-sensor spacings utilized in the proposed array are also analyzed. Simulation results validate the performance of the proposed array geometry.

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Section: Esprit-based Methods To Estimate the Two Sets Of High-accuracmentioning

confidence: 99%

Section: Performance Versus Snrmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

A single triangular SS-EMVS aided high-accuracy DOA estimation using a multi-scale L-shaped sparse array

Ding¹,

Yang²,

Chen³

et al. 2019

EURASIP J. Adv. Signal Process.

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show abstract

“…where bdiag(·) denotes the block-diagonal matrix operator [15], ω μ p = (2π/λ)Δ e μ p , ω v p = (2π/λ)Δ e v p are the spatial frequencies along the y-axis and the z-axis respectively, and…”

Section: Derivation Of the Coarse Estimates Of μ P And V Pmentioning

confidence: 99%

An eigenstructure-based 2D DOA estimation method using dual-size spatial invariance array

Xue-ya

Chen

2010

Sci. China Inf. Sci.

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A sparse planar array vertically placed in y − z plane is proposed to improve the angle estimation accuracy of sources in low angle region with reflection multipath. With two sizes of spatial invariances along both dimensions, the array estimates the azimuth and elevation angles using unitary ESPRIT (estimation of signal parameters via rotational invariance techniques). The first spatial invariance with a displacement of half-wavelength yields unambiguous coarse estimates of high-variance, while the second spatial invariance with much larger a displacement of subarrays obtains cyclically ambiguous fine estimates of low-variance. The final estimates are obtained by disambiguating fine estimates with coarse estimates. A novel pairing scheme is proposed to pair both the azimuth and elevation, coarse and fine angle estimates of the same signal. In addition, a new method is presented to calculate 2D angles, which substitutes the estimated elevation angle into the sin relative to the y-axis to get the azimuth angle. Employing real-valued processing and array aperture extension, the new DOA measuring method de-correlates the multipath signals and enhances angle resolution with no extra antennas and computational complexity. Simulation results show the effectiveness of the proposed technique and its advantages over the conventional methods.

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“…Further in [6]- [8], it was shown that the performance is improved by using multi-scale method, where the short are, respectively, utilized to derive the coarse unambiguous and fine ambiguous estimates for each signal. The final DOA estimate in this case is determined by using the coarse estimate to disambiguate the fine estimate.…”

Section: Introductionmentioning

confidence: 99%

Resolving Cyclic Ambiguities and Increasing Accuracy and Resolution in DOA Estimation Using Array Rotation

Djouadi¹,

Jaksic²

2017

Computer Science &Amp; Information Technology (CS &Amp; IT)

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A method to resolve cyclic ambiguities and increase the accuracy and the resolution in the direction-of-arrival (DOA) estimation using the Estimation of Signal Parameters via Rotational Invariance Technique (ESPRIT)algorithm is proposed. It is based on rotating the array and sampling the received signal at multiple positions. Using this approach, the gain in accuracy and resolution is addressed as function of the mean and variance of the DOA. Simulations results are provided as a means of verifying this analysis.

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Unitary ESPRIT-Based DOA Estimation Using Sparse Linear Dual Size Spatial Invariance Array

Cited by 11 publications

References 6 publications

A single triangular SS-EMVS aided high-accuracy DOA estimation using a multi-scale L-shaped sparse array

A single triangular SS-EMVS aided high-accuracy DOA estimation using a multi-scale L-shaped sparse array

An eigenstructure-based 2D DOA estimation method using dual-size spatial invariance array

Resolving Cyclic Ambiguities and Increasing Accuracy and Resolution in DOA Estimation Using Array Rotation

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