scholarly journals Joint Estimation of DOA and Frequency of Multiple Sources with Orthogonal Coprime Arrays

Sensors ◽  
2019 ◽  
Vol 19 (2) ◽  
pp. 335 ◽  
Author(s):  
Kai-Chieh Hsu ◽  
Jean-Fu Kiang
Keyword(s):  
Carrier Frequency ◽  
Joint Estimation ◽  
Orthogonal Complement ◽  
Spatial Smoothing ◽  
Multiple Sources ◽  
Music Algorithm ◽  
Two Stage ◽  
Coprime Arrays ◽  
Esprit Algorithm ◽  
Source Signals

A two-stage method is proposed to jointly estimate the direction-of-arrival (DOA) and carrier frequency (CF) of multiple sources, by using two orthogonal coprime arrays (CPAs). The DOAs of CF-known sources are estimated first by applying a spatial smoothing MUSIC algorithm. The contribution of these source signals is then removed from the originally received signal by applying an orthogonal complement projector. Next, a joint-ESPRIT algorithm is applied to estimate the DOAs and CFs of the remaining CF-unknown sources. With two orthogonal CPA(5, 6), the RMSE of DOA and CF of applying the proposed method to 30 sources, 13 of which have unknown CF, is less than 1% at SNR > 5 dB.

scholarly journals Distributed Super Nested Arrays: Reduce the Mutual Coupling between Array Antennas

2021 ◽  
Vol 2021 ◽  
pp. 1-16
Author(s):  
Hongyong Wang ◽  
Weibo Deng ◽  
Ying Suo ◽  
Xin Zhang ◽  
Yanmo Hu ◽  
...  
Keyword(s):  
Mutual Coupling ◽  
Doa Estimation ◽  
Baseline Length ◽  
Spatial Smoothing ◽  
Estimation Of Parameters ◽  
Signal Parameter ◽  
Array Antennas ◽  
Esprit Algorithm ◽  
Nested Arrays ◽  
Source Signals

In array, mutual coupling between the antennas is inevitable, which has an adverse effect on the estimation of parameters. To reduce the mutual coupling between the antennas of distributed nested arrays, this paper proposes a new array called the distributed super nested arrays, which have the good characteristics of the distributed nested arrays and can reduce the mutual coupling between the antennas. Then, an improved multiscale estimating signal parameter via rotational invariance techniques (ESPRIT) algorithm is presented for the distributed super nested arrays to improve the accuracy of direction-of-arrival (DOA) estimation. Next, we analyze the limitations of the spatial smoothing algorithm used by the distributed super nested arrays when there are multiple-source signals and the influence of the baseline length of distributed super nested arrays on the accuracy of DOA estimation. The simulation results show that the distributed super nested arrays can effectively reduce the mutual coupling between the array antennas, improve the DOA estimation performance, and significantly increase the number of detectable source signals.

scholarly journals Direction of Arrival Estimation Using Augmentation of Coprime Arrays

Information ◽  
2018 ◽  
Vol 9 (11) ◽  
pp. 277 ◽  
Author(s):  
Tehseen Hassan ◽  
Fei Gao ◽  
Babur Jalal ◽  
Sheeraz Arif
Keyword(s):  
Covariance Matrix ◽  
Degrees Of Freedom ◽  
Direction Of Arrival ◽  
Estimation Algorithm ◽  
Doa Estimation ◽  
Spatial Smoothing ◽  
Multiple Signal Classification ◽  
Coprime Arrays ◽  
The Difference ◽  
Source Signals

Recently, direction of arrival (DOA) estimation premised on the sparse arrays interpolation approaches, such as co-prime arrays (CPA) and nested array, have attained extensive attention because of the effectiveness and capability of providing higher degrees of freedom (DOFs). The co-prime array interpolation approach can detect O(MN) paths with O(M + N) sensors in the array. However, the presence of missing elements (holes) in the difference coarray has limited the number of DOFs. To implement co-prime coarray on subspace based DOA estimation algorithm namely multiple signal classification (MUSIC), a reshaping operation followed by the spatial smoothing technique have been presented in the literature. In this paper, an active coarray interpolation (ACI) is proposed to efficiently recovering the covariance matrix of the augmented coarray from the original covariance matrix of source signals with no vectorizing and spatial smoothing operation; thus, the computational complexity reduces significantly. Moreover, the numerical simulations of the proposed ACI approach offers better performance compared to its counterparts.

scholarly journals Coherent Target Direction-of-Arrival Estimation for Coprime Arrays: From Spatial Smoothing Perspective

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Dongming Wu ◽  
Fangzheng Liu ◽  
Zhihui Li ◽  
Zhenzhong Han
Keyword(s):  
Direction Of Arrival ◽  
Doa Estimation ◽  
Spatial Spectrum ◽  
Spatial Smoothing ◽  
Phase Ambiguity ◽  
Coherent Signals ◽  
Music Algorithm ◽  
Multiple Signal Classification ◽  
Common Peak ◽  
Coprime Arrays

In this paper, we investigate the issue of direction-of-arrival (DOA) estimation of multiple signals in coprime arrays. An algorithm based on multiple signal classification (MUSIC) and forward and backward spatial smoothing (FBSS) is used for DOA estimation of this signal caused by multipath and interference. The large distance between adjacent elements of each subarray in the coprime arrays will bring phase ambiguity issues. According to the feature of the coprime number, the ambiguity problem can be eliminated. The correct DOA estimation can be obtained by searching for the common peak of the spatial spectrum and finding the overlapping peaks in the MUSIC spectrum of the two subarrays. For the rank deficit problem caused by the coherent signal, the FBSS algorithm is used for signal preprocessing before the MUSIC algorithm. Theoretical analysis and simulation results show that the algorithm can effectively solve the rank deficiency and phase ambiguity problems caused by coherent signals and sparse arrays in the coprime arrays.

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.

scholarly journals Effect of varying Number of Spacing between Antenna Elements, Snapshots, SNR on AP ML, AP-SSF and ESPRIT Algorithm

2021 ◽  
Vol 11 ◽  
pp. 143-150
Author(s):  
Vinod Kumar ◽  
Sanjeev Kumar Dhull
Keyword(s):  
Signal Processing ◽  
Maximum Likelihood ◽  
Key Words ◽  
Array Signal Processing ◽  
Direction Of Arrival ◽  
Performance Comparison ◽  
Direction Of Arrival Estimation ◽  
Multiple Sources ◽  
Alternating Projection ◽  
Esprit Algorithm

The direction of arrival estimation is the main key problem in array signal processing. In this paper, the alternating projection maximum Likelihood (AP-ML), Alternating projection sub space framework (APSSF) and ESPRIT algorithm are studied. The simulation is performed in MATLAB for single and multiple sources. The effect of the varying number of spacing between antenna elements, number of snapshots and SNR are studied. The performance comparison shows that ESPRIT algorithm performs better as compared to the AP-ML and AP-SSF. Key-Words: - AP-ML, AP-SSF, Direction of Arrival, ESPRIT, Snapshots, SNR

USTC-MUSIC Algorithm for DOA Estimation of Coherent Sources Using Single Vector Hydrophone

2014 ◽  
Vol 530-531 ◽  
pp. 530-533
Author(s):  
Jin Fang Cheng ◽  
Chao Ran Zhang ◽  
Wei Zhang
Keyword(s):  
Correlation Matrix ◽  
Temporal Correlation ◽  
Doa Estimation ◽  
Spatial Smoothing ◽  
Music Algorithm ◽  
Correlation Matrices ◽  
Vector Hydrophone ◽  
Coherent Sources ◽  
Simulation Results ◽  
Spatio Temporal

The MUSIC algorithm cannot deal with the problem of DOA estimation of coherent sources, this paper proposes the USTC (unitary spatio-temporal correlation matrices)-MUSIC algorithm using single vector hydrophone to solve this problem, by utilizing the unitary spatio-temporal correlation matrix instead of the covariance matrix. The simulation results demonstrate that the USTC-MUSIC algorithm has a better ability to distinguish the coherent sources from different directions than the spatial smoothing MUSIC algorithm.

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