scholarly journals Two-Dimensional Direction-of-Arrival Fast Estimation of Multiple Signals with Matrix Completion Theory in Coprime Planar Array

Sensors ◽  
2018 ◽  
Vol 18 (6) ◽  
pp. 1741 ◽  
Author(s):  
Haiyun Xu ◽  
Yankui Zhang ◽  
Bin Ba ◽  
Daming Wang ◽  
Xiangzhi Li
Keyword(s):  
Matrix Completion ◽  
Direction Of Arrival ◽  
Two Dimensional ◽  
Multiple Signals ◽  
Fast Estimation ◽  
Planar Array

scholarly journals Fast Two-Dimensional Direction-of-Arrival Estimation of Multiple Signals in Coprime Planar Array

2019 ◽  
Vol 2019 ◽  
pp. 1-9 ◽  
Author(s):  
Haiyun Xu ◽  
Yankui Zhang ◽  
Bin Ba ◽  
Daming Wang ◽  
Peng Han
Keyword(s):  
Direction Of Arrival ◽  
Doa Estimation ◽  
Low Complexity ◽  
Two Dimensional ◽  
Multiple Signals ◽  
Subspace Algorithm ◽  
Signal Parameters ◽  
Planar Array ◽  
The Common ◽  
The Relationship

Two-dimensional direction-of-arrival (DOA) estimation in coprime planar array involves problems that the complexity of spectral peak search is huge and the noncircular feature of signals is not considered. Considering that unitary estimating signal parameters via rotational invariance techniques (Unitary-ESPRIT) is a low complexity subspace algorithm, an approach to estimate DOA fast for multiple signals is proposed in this paper. We first apply Unitary-ESPRIT to solve one possible value of each signal. Given the relationship between the ambiguous values and real values, we then have all possible values belonging to each subarray. Through finding the common values of two subarrays, we finally obtain the highly precise true DOAs. Moreover, when the signals are noncircular, we present an improved method using noncircular Unitary-ESPRIT, which is favorable in terms of accuracy and degree of freedom. Simulation results demonstrate the effectiveness of our proposed methods.

scholarly journals Two-Dimensional Direction-of-Arrival Estimation of Noncircular Signals in Coprime Planar Array with High Degree of Freedom

2019 ◽  
Vol 2019 ◽  
pp. 1-10 ◽  
Author(s):  
Haiyun Xu ◽  
Daming Wang ◽  
Size Lin ◽  
Bin Ba ◽  
Yankui Zhang
Keyword(s):  
Covariance Matrix ◽  
Direction Of Arrival ◽  
Low Complexity ◽  
Degree Of Freedom ◽  
Spectral Peak ◽  
Two Dimensional ◽  
Rectangular Array ◽  
Planar Array ◽  
Noncircular Signals ◽  
Peak Search

In estimating the two-dimensional (2D) direction-of-arrival (DOA) using a coprime planar array, there are problems of the limited degree of freedom (DOF) and high complexity caused by the spectral peak search. We utilize the time-domain characteristics of signals and present a high DOF algorithm with low complexity based on the noncircular signals. The paper first analyzes the covariance matrix and ellipse covariance matrix of the received signals, vectorizes these matrices, and then constructs the received data of a virtual uniform rectangular array (URA). 2D spatial smoothing processing is applied to calculate the covariance of the virtual URA. Finally, the paper presents an algorithm using 2D multiple signal classification and an improved algorithm using unitary estimating signal parameters via rotational invariance techniques, where the latter solves the closed-form solutions of DOAs replacing the spectral peak search to reduce the complexity. The simulation experiments demonstrate that the proposed algorithms obtain the high DOF and enable to estimate the underdetermined signals. Furthermore, both two proposed algorithms can acquire the high accuracy.

scholarly journals Thermos Array: Two-Dimensional Sparse Array with Reduced Mutual Coupling

2018 ◽  
Vol 2018 ◽  
pp. 1-8 ◽  
Author(s):  
Lei Sun ◽  
Minglei Yang ◽  
Baixiao Chen
Keyword(s):  
Closed Form ◽  
Degrees Of Freedom ◽  
Mutual Coupling ◽  
Doa Estimation ◽  
Two Dimensional ◽  
Spatial Smoothing ◽  
Planar Arrays ◽  
Half Wavelength ◽  
Planar Array ◽  
Small Spacing

Sparse planar arrays, such as the billboard array, the open box array, and the two-dimensional nested array, have drawn lots of interest owing to their ability of two-dimensional angle estimation. Unfortunately, these arrays often suffer from mutual-coupling problems due to the large number of sensor pairs with small spacing d (usually equal to a half wavelength), which will degrade the performance of direction of arrival (DOA) estimation. Recently, the two-dimensional half-open box array and the hourglass array are proposed to reduce the mutual coupling. But both of them still have many sensor pairs with small spacing d, which implies that the reduction of mutual coupling is still limited. In this paper, we propose a new sparse planar array which has fewer number of sensor pairs with small spacing d. It is named as the thermos array because its shape seems like a thermos. Although the resulting difference coarray (DCA) of the thermos array is not hole-free, a large filled rectangular part in the DCA can be facilitated to perform spatial-smoothing-based DOA estimation. Moreover, it enjoys closed-form expressions for the sensor locations and the number of available degrees of freedom. Simulations show that the thermos array can achieve better DOA estimation performance than the hourglass array in the presence of mutual coupling, which indicates that our thermos array is more robust to the mutual-coupling array.

scholarly journals Fast Estimation Method of Space-Time Two-Dimensional Positioning Parameters Based on Hadamard Product

2018 ◽  
Vol 2018 ◽  
pp. 1-9 ◽  
Author(s):  
Haiwen Li ◽  
Nae Zheng ◽  
Xiyu Song ◽  
Yinghua Tian
Keyword(s):  
Frequency Domain ◽  
Orthogonal Frequency Division Multiplexing ◽  
Hadamard Product ◽  
Estimation Method ◽  
Space Time ◽  
Joint Estimation ◽  
Two Dimensional ◽  
Music Algorithm ◽  
Fast Estimation ◽  
Response Vector

The estimation speed of positioning parameters determines the effectiveness of the positioning system. The time of arrival (TOA) and direction of arrival (DOA) parameters can be estimated by the space-time two-dimensional multiple signal classification (2D-MUSIC) algorithm for array antenna. However, this algorithm needs much time to complete the two-dimensional pseudo spectral peak search, which makes it difficult to apply in practice. Aiming at solving this problem, a fast estimation method of space-time two-dimensional positioning parameters based on Hadamard product is proposed in orthogonal frequency division multiplexing (OFDM) system, and the Cramer-Rao bound (CRB) is also presented. Firstly, according to the channel frequency domain response vector of each array, the channel frequency domain estimation vector is constructed using the Hadamard product form containing location information. Then, the autocorrelation matrix of the channel response vector for the extended array element in frequency domain and the noise subspace are calculated successively. Finally, by combining the closed-form solution and parameter pairing, the fast joint estimation for time delay and arrival direction is accomplished. The theoretical analysis and simulation results show that the proposed algorithm can significantly reduce the computational complexity and guarantee that the estimation accuracy is not only better than estimating signal parameters via rotational invariance techniques (ESPRIT) algorithm and 2D matrix pencil (MP) algorithm but also close to 2D-MUSIC algorithm. Moreover, the proposed algorithm also has certain adaptability to multipath environment and effectively improves the ability of fast acquisition of location parameters.

Direction-of-arrival estimation of multiple speakers using a planar array

2014 ◽  
Author(s):  
Dongwen Ying ◽  
Ruohua Zhou ◽  
Junfeng Li ◽  
Jielin Pan ◽  
Yonghong Yan
Keyword(s):  
Direction Of Arrival ◽  
Direction Of Arrival Estimation ◽  
Planar Array
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