Grid‐less coherent DOA estimation based on fourth‐order cumulants with Gaussian coloured noise

Zhang, Yuying; Zhang, Gong; Leung, Henry

doi:10.1049/iet-rsn.2019.0329

Cited by 12 publications

(7 citation statements)

References 39 publications

(48 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…However, with the continuous in-depth research on subspace class algorithms, the limitations of the algorithms have gradually emerged. Most subspace class algorithms assume that the noise is ideal Gaussian white noise with independent homogeneous distribution, while the noise in the real environment is usually colour noise that does not satisfy this distribution [5][6][7][8][9]. All of these situations lead to degradation of the performance of traditional super-resolution subspace class algorithms and are extremely computationally intensive.…”

Section: Introductionmentioning

confidence: 99%

Design of a low-complexity DOA estimation method based on fourth-order cumulants

Lin

2023

International Conference on Optical Technology, Semiconductor Materials, and Devices (OTSMD 2022)

View full text Add to dashboard Cite

To address the problem that the conventional algorithm has a very high complexity in estimating the direction of arrival (DOA) of coherent sources in the background of colour noise, this paper proposes a low-complexity DOA estimation method based on the fourth-order cumulant and Toeplitz matrix reconstruction. Firstly, a fourth-order cumulant (FOC) matrix is constructed from the received signal vector to suppress the noise component, and the redundant information in the FOC matrix is removed by storing the matrix to obtain the reduced dimensional FOC matrix. Afterwards, the Toeplitz matrix is reconstructed to extend the array aperture and to achieve decoherence. Finally, the DOA estimation of the reconstructed matrix is performed using the MUSIC algorithm. Simulations demonstrate that the DOA estimation of coherent signals in a colour-noise background is less complex and maintains a higher accuracy than conventional algorithms.

show abstract

Section: Introductionmentioning

confidence: 99%

Design of a low-complexity DOA estimation method based on fourth-order cumulants

Lin

2023

International Conference on Optical Technology, Semiconductor Materials, and Devices (OTSMD 2022)

View full text Add to dashboard Cite

show abstract

“…Extensions and variations of NA and CPA have been developed to increase the DOFs for DOA estimation [3][4][5][6]. Sparse arrays offer larger apertures and higher DOFs compared to traditional ULAs with the same number of antennas.…”

Section: Introductionmentioning

confidence: 99%

An enhanced expanding and shift sparse array based on the coprime array and nested array

Qin,

Yang,

Dang

et al. 2023

IET Radar Sonar & Navi

View full text Add to dashboard Cite

In recent years, sparse arrays based on the fourth‐order difference coarray (FODCA) have received increased research attention due to their small number of array elements and large consecutive virtual arrays. The expanding and shift structure based on the nested array (NA) and coprime array (CPA) (EAS‐NA‐CPA) is the representative one. The EAS‐NA‐CPA comprises two sparse subarrays, wherein the NA is expanded and shifted according to the second‐order difference coarray of the CPA. Although the number of consecutive elements is large, there are many redundant elements in the FODCA of the EAS‐NA‐CPA. To decrease the number of redundant elements and increase the number of consecutive elements in the FODCA, the authors proposed the enhanced EAS‐NA‐CPA (EEAS‐NA‐CPA). Compared with the original EAS‐NA‐CPA, the EEAS‐NA‐CPA increases the adjacent physical sensor spacing further by using more fourth‐order cross‐correlation coarrays in the FODCA, which are not considered in the original EAS‐NA‐CPA. By performing a theoretical analysis of the FODCA provided by the proposed EEAS‐NA‐CPA, the sensor spacing in the expanded NA was further increased to obtain a larger number of consecutive elements compared with the original EAS‐NA‐CPA. Furthermore, the relationship between the number of physical sensors and corresponding number of consecutive elements provided by the FODCA was explicitly expressed. Experimental simulations were conducted to verify the effectiveness of the proposed sparse array for the fourth‐order cumulant‐based direction of arrival estimation.

show abstract

“…In the wake of developments in compressed sensing (CS), the theory of sparse reconstruction has been widely used in the DOA estimation [3,4]. Generally, CS algorithms have high accuracy and good performance with deficient snapshots and low SNR.…”

Section: Introductionmentioning

confidence: 99%

A novel wideband DOA estimation method based on a fast sparse frame

et al. 2021

View full text Add to dashboard Cite

In this study, a novel fast wideband direction of arrival (DOA) estimation algorithm is proposed to reduce the computational complexity. First, a multiple measurement vector (MMV)-based compact structure for a wideband signal is established. Combined with the focus operation, the array manifolds of different frequency bins are transformed into the dictionary of the reference frequency. Then, two efficient novel methods named adaptive step-size-based null space tuning with hard thresholding and feedback (ASNHF) and MMV-ASNHF are proposed to process single measurement vector and MMV problem, respectively. Finally, wideband DOA estimation can be achieved by MMV-ASNHF algorithm. Compared with other algorithms, the proposed algorithm has higher accuracy at a low signal-to-noise ratio and lower computational complexity. Simulation results show that the proposed estimator is effective and feasible.

show abstract

Grid‐less coherent DOA estimation based on fourth‐order cumulants with Gaussian coloured noise

Cited by 12 publications

References 39 publications

Design of a low-complexity DOA estimation method based on fourth-order cumulants

Design of a low-complexity DOA estimation method based on fourth-order cumulants

An enhanced expanding and shift sparse array based on the coprime array and nested array

A novel wideband DOA estimation method based on a fast sparse frame

Contact Info

Product

Resources

About