Transform Domain: Design of Closed-Form Joint 2-D DOA Estimation Based on QR Decomposition

Cao, Hui; Liu, Qi; Wu, Yuntao

doi:10.1007/s00034-020-01416-8

Cited by 3 publications

(3 citation statements)

References 22 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…where f r ,k (1) and f r ,k (2) account for the first and second entities of f r ,k , respectively. Although Br is corrupted by D p {C t }, which means there is a scalar effect on the estimated B r (the k-th column of Br is scaled by the k-th element of D p {C t }).…”

Section: Azimuth Angle Estimationmentioning

confidence: 99%

“…As a nonlinear problem, direction finding has attracted extensive attention. Various estimation algorithms have been reported, for example, the method for estimating signal parameters via the rotational invariance technique (ESPRIT) [2], the spatial spectrum search method, the optimization estimator [14][15][16], and the cumulant-based approach [9,10].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Joint 2D-DOD and 2D-DOA Estimation for Coprime EMVS–MIMO Radar

Wang

Huang

Wan

2021

Circuits Syst Signal Process

View full text Add to dashboard Cite

The issue of two-dimensional (2D) direction-of-departure and direction-of-arrival estimation for bistatic multiple-input multiple-output (MIMO) radar with a coprime electromagnetic vector sensor (EMVS) is addressed in this paper, and a tensor-based subspace algorithm is proposed. Firstly, the covariance measurement of the received data is arranged into a fourth-order tensor, which can maintain the multi-dimensional characteristic of the received data. Then, the higher-order singular value decomposition is followed to get an accurate signal subspace. By utilizing the uniformity of the subarrays in coprime EMVS-MIMO radar, the rotation invariant technique is adopted to achieve ambiguous elevation angle estimation. Thereafter, the unambiguous elevation angles are recovered by exploring the coprime characteristic of the subarrays. Finally, all azimuth angles are achieved by using the vector cross-product strategy. The tensor nature inherited from the array measurement is fully explored, and the coprime geometry enables EMVS-MIMO radar to achieve larger array aperture than the existing uniform linear configuration; thus, the proposed method offers better estimation performance than current state-of-the-art algorithms. Several computer simulations validate the effectiveness of the proposed algorithm.

show abstract

Section: Azimuth Angle Estimationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Joint 2D-DOD and 2D-DOA Estimation for Coprime EMVS–MIMO Radar

Wang

Huang

Wan

2021

Circuits Syst Signal Process

View full text Add to dashboard Cite

show abstract

“…Real-time acquisition is of vital importance as it enables field engineers to adaptively modify the acquisition parameters and minimize logistical costs [4], [5]. Knowing the direction of arrival (DOA) of the transmitted signal and the position of the transmitter is paramount to geophysical and communication purposes [6], [7], [8].…”

Section: Introductionmentioning

confidence: 99%

DOA-based Localization Using Deep Learning for Wireless Seismic Acquisition

Aliyu

Alawsh

Muqaibel

et al. 2021

Preprint

View full text Add to dashboard Cite

Oil and gas companies consider transforming conventional cable-based seismic acquisition to wireless acquisition as a promising step for cost and weight reduction in reservoir exploration. Wireless seismic acquisition requires large number of wireless geophone (WG) sensors to be deployed in the field. The locations of the WG sensors must be known when processing the collected data. The application of direction of arrival (DOA) estimation helps in localizing WGs and improves received signal level through beam steering and interference avoidance. Conventional DOA algorithms require high computational complexity which renders them inefficient for real-time response. In this paper, deep neural network (DNN) is proposed for DOA estimation of WGs at wireless gateway node (WGN) under different channel conditions. The estimated angle and corresponding coordinates of WGNs are used in least square estimation (LSE) to estimate the position of the WGs. The simulation results depict reasonable estimation and position accuracy in real-time.

show abstract

Ultra-Fast Accurate AoA Estimation via Automotive Massive-MIMO Radar

Wang

Jun

et al. 2022

IEEE Trans. Veh. Technol.

View full text Add to dashboard Cite

Transform Domain: Design of Closed-Form Joint 2-D DOA Estimation Based on QR Decomposition

Cited by 3 publications

References 22 publications

Joint 2D-DOD and 2D-DOA Estimation for Coprime EMVS–MIMO Radar

Joint 2D-DOD and 2D-DOA Estimation for Coprime EMVS–MIMO Radar

DOA-based Localization Using Deep Learning for Wireless Seismic Acquisition

Ultra-Fast Accurate AoA Estimation via Automotive Massive-MIMO Radar

Contact Info

Product

Resources

About