Wideband Direction of Arrival Estimation Based on the Principal Angle Between Subspaces

Zhou, Feng; Liao, Hongshu; Gan, Lu; Yang, Dong; Hu, and Rong

doi:10.2528/pierl18060407

Cited by 4 publications

(6 citation statements)

References 17 publications

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“…The coherent signal space method (CSM) is a class way of wideband DOA estimation [4]. The key idea is to design a cluster of focusing matrices

{bold-italicP}_{1}, {bold-italicP}_{2}, \dots, {bold-italicP}_{N}

, which are then used to transform the manifold at the corresponding frequency

f_{1}, f_{2}, \dots, f_{N}

to that at a predefined reference frequency

f_{0}

as follows:

{bold-italicP}_{n} {bold-italicA}_{n} false(θ false) = {bold-italicA}_{0} false(θ false)

where

{bold-italicA}_{0} false(θ false)

is the manifold of the referenced focusing frequency

f_{0}

.…”

Section: A Novel Methods For Wideband Doa Estimationmentioning

confidence: 99%

“…In view of these advantages, wideband DOA (WDOA) estimation has attracted some research interests and efforts. In the literature, Yu et al [3] proposed a wideband DOA estimator by testing the orthogonality of frequencies, and Feng and Liao [4] offered a wideband DOA estimation approach by using the principal angles between subspaces. However, all of these existing methods hinge on a large number of snapshots.…”

mentioning

confidence: 99%

“…A novel method for wideband DOA estimation: The coherent signal space method (CSM) is a class way of wideband DOA estimation [4]. The key idea is to design a cluster of focusing matrices P 1 , P 2 , .…”

mentioning

confidence: 99%

See 2 more Smart Citations

Wideband DOA estimation with deficient snapshots using low rank Toeplitz structure

2019

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In array signal processing, most existing direction-of-arrival (DOA) estimation methods fail to work given deficient snapshots. To solve this problem, this Letter proposes a novel wideband DOA estimation technique by utilising the sparse representation in terms of the low rank Toeplitz structure presented in uniform array geometries, followed by an enhanced MUSIC method. Specifically, each sub-band segment is first focused into the reference frequency band to collect the coherent covariance matrix even in the lack of sufficient samples. Then, the covariance matrix is denoised through a structure-based sparse reconstruction, which exploits the low rank Toeplitz structure. Finally, the DOAs is efficiently estimated via an enhanced MUSIC method. Simulation result confirms the efficacy of the proposed method that works well in MIMO and radar applications.

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“…The coherent signal space method (CSM) is a class way of wideband DOA estimation [4]. The key idea is to design a cluster of focusing matrices

{bold-italicP}_{1}, {bold-italicP}_{2}, \dots, {bold-italicP}_{N}

, which are then used to transform the manifold at the corresponding frequency

f_{1}, f_{2}, \dots, f_{N}

to that at a predefined reference frequency

f_{0}

as follows:

{bold-italicP}_{n} {bold-italicA}_{n} false(θ false) = {bold-italicA}_{0} false(θ false)

where

{bold-italicA}_{0} false(θ false)

is the manifold of the referenced focusing frequency

f_{0}

.…”

Section: A Novel Methods For Wideband Doa Estimationmentioning

confidence: 99%

mentioning

confidence: 99%

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Wideband DOA estimation with deficient snapshots using low rank Toeplitz structure

2019

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“…It is known that the CSM, which is a classic way of wideband signal processing [ 31 ], can lead to less complexity and better DOA estimation performance. The key point of CSM is to design focusing matrices

, whose purpose are to transform the manifold matrices at frequencies

to that at the pre-selected reference frequency

as follows [ 32 ]

where

denotes the virtual array manifold matrix at the referenced frequency

.…”

Section: Wideband Signal Processing Using Virtual Arraymentioning

confidence: 99%

Underdetermined DOA Estimation for Wideband Signals via Focused Atomic Norm Minimization

Shi

Zhang

Tan

et al. 2020

Entropy

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In underwater acoustic signal processing, direction of arrival (DOA) estimation can provide important information for target tracking and localization. To address underdetermined wideband signal processing in underwater passive detection system, this paper proposes a novel underdetermined wideband DOA estimation method equipped with the nested array (NA) using focused atomic norm minimization (ANM), where the signal source number detection is accomplished by information theory criteria. In the proposed DOA estimation method, especially, after vectoring the covariance matrix of each frequency bin, each corresponding obtained vector is focused into the predefined frequency bin by focused matrix. Then, the collected averaged vector is considered as virtual array model, whose steering vector exhibits the Vandermonde structure in terms of the obtained virtual array geometries. Further, the new covariance matrix is recovered based on ANM by semi-definite programming (SDP), which utilizes the information of the Toeplitz structure. Finally, the Root-MUSIC algorithm is applied to estimate the DOAs. Simulation results show that the proposed method outperforms other underdetermined DOA estimation methods based on information theory in term of higher estimation accuracy.

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“…Recent studies investigated new techniques for enhancing the accuracy of wideband DOA estimation [24][25][26]. In [24], a modern wideband DOA estimation technique was developed by computing the largest principal angle (LPA) between the signal subspace and the subspace spanned by a new augmented array manifold which contains all frequency bins.…”

Section: Introductionmentioning

confidence: 99%

A Compressive Sensing Based Computationally Efficient High-Resolution DOA Estimation of Wideband Signals Using Generalized Coprime Arrays

El-Khamy,

El-Shazly,

Eltrass

2024

Wireless Pers Commun

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Most recent state-of-the-art wideband direction of arrival (DOA) estimation techniques achieve reasonable accuracy at the expenses of high computational complexity. In this paper, a new computationally efficient approach based on compressive sensing (CS) is introduced for high resolution wideband DOA estimation. The low software complexity is achieved utilizing CS with deterministic chaotic Chebyshev sensing matrices that allow reducing the measurement vector dimension, while the high-resolution DOA estimation is acquired utilizing an efficient generalized coprime array configuration. The effectiveness of the introduced approach in enhancing the DOA estimation precision and reducing the computational complexity is studied along with a detailed comparison between three state-of-the-art wideband DOA estimation techniques, namely incoherent signal subspace method (ISSM), focusing signal subspace (FSS), and modified test of orthogonality of projected subspaces (mTOPS) with and without applying the proposed CS technique. The performance is examined utilizing various assessment metrics such as the spatial spectrum, the computational time, and the root mean square error between estimated and actual DOAs when varying the signal-to-noise ratio and number of elements. Results reveal that applying the proposed CS technique to the three algorithms (ISSM, FSS, and mTOPS) provides significant reduction in the execution time needed for the DOA estimation without affecting the resolution accuracy under various set of parameters. This reveals the importance of the proposed approach in wideband wireless communication systems.

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Wideband Direction of Arrival Estimation Based on the Principal Angle Between Subspaces

Cited by 4 publications

References 17 publications

Wideband DOA estimation with deficient snapshots using low rank Toeplitz structure

Wideband DOA estimation with deficient snapshots using low rank Toeplitz structure

Underdetermined DOA Estimation for Wideband Signals via Focused Atomic Norm Minimization

A Compressive Sensing Based Computationally Efficient High-Resolution DOA Estimation of Wideband Signals Using Generalized Coprime Arrays

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