Two-Dimensional Direction of Arrival Estimation for Coprime Planar Arrays via Polynomial Root Finding Technique

Zhang, Dong; Zhang, Yongshun; Deng, Bangming; Feng, Cunqian; Tang, Jun

doi:10.1109/access.2018.2821919

Cited by 31 publications

(14 citation statements)

References 26 publications

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“…On the basis of electromagnetic (EM) wave radiated by hostile radiator and propagated by troposcatter, passive surveillance can realize b-LOS location [3,4]. Direction of arrival (DOA) estimation with high performance is the prerequisite of a passive surveillance system [5][6][7][8][9][10][11][12]. Intricate scattering procedure can generate multipath propagation, and scattered signals can be treated as closely spaced sources and own respective power; some signals with low signal to noise ratio (SNR) may be flooded by noises.…”

Section: Introductionmentioning

confidence: 99%

An Efficient DOA Estimation Method for Passive Surveillance System Based on Troposcatter

Liu

Chen

et al. 2021

Mathematical Problems in Engineering

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Direction of arrival (DOA) estimation plays an important role in the passive surveillance system based on troposcatter. Rank deficiency and subspace leakage resulting from multipath propagation can deteriorate the performance of the DOA estimator. In this paper, characteristics of signals propagated by troposcatter are analyzed, and an efficient DOA estimation method is proposed. According to our new method, the invariance property of noise subspace (IPNS) is introduced as the main method. To provide precise noise subspace for INPS, forward and backward spatial smoothing (FBSS) is carried out to overcome rank deficiency. Subspace leakage is eliminated by a two-step scheme, and this process can also largely reduce the computational load of INPS. Numerical simulation results validate that our method has not only good resolution in condition of closely spaced signals but also superior performance in case of power difference.

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Section: Introductionmentioning

confidence: 99%

An Efficient DOA Estimation Method for Passive Surveillance System Based on Troposcatter

Liu

Chen

et al. 2021

Mathematical Problems in Engineering

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“…In [7] and [8], a CPA is treated as two uniform planar subarrays, which simplifies the system model, but leads to a significant loss of DOFs. In [9], the CPA geometry is generalized, resulting in higher DOFs than [7] and [8] with same number of sensor elements. However, it also deals with the subarrays and the significant advantage in terms of DOFs is sacrificed.…”

Section: Introductionmentioning

confidence: 99%

Hole Locations and a Filling Method for Coprime Planar Arrays for DOA Estimation

2021

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Coprime linear arrays (CLAs) have drawn lots of attention. Efforts have been made to reveal the hole locations in the difference coarrays of CLAs, based on which many methods have been proposed to fill the holes, lengthening the consecutive difference coarray part and increasing the effective degrees of freedom (DOFs). Compared with CLAs, two dimensional (2D) coprime planar arrays (CPAs) are more relevant to real applications. However, no closed-form expressions for the hole locations in the difference coarray of a CPA have been found in the open literature, and the advantage in terms of DOFs of CPAs has not been well explored. In this letter, the structure of the difference coarrays of CPAs is investigated and the exact expressions of all hole positions are provided. Then, a holesfilling method is proposed, by which the most critical holes in the difference coarray can be filled such that a difference coarray with more consecutive lags as well as higher effective DOFs can be obtained.

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“…To address this issue, a reduced dimensional-based PSS method (RD-PSS) was proposed in [ 19 ], where only a one-dimensional partial spectral search is performed. For co-prime planar arrays, a polynomial root finding-based method was proposed in [ 20 ], which can avoid the spectral search step. Then, the co-prime array concept was extended to multiple input multiple output radars to estimate 2D DOAs with enhanced degrees-of-freedom (DOFs) [ 21 ].…”

Section: Introductionmentioning

confidence: 99%

“…However, the methods in [ 17 , 18 , 19 , 20 ] require that each subarray estimates the DOAs individually by their own data and obtains the estimate by combining the results of the two subarrays. For the individual estimate of each subarray, the mutual information of the received data between the two subarrays is lost; therefore, the estimation accuracy is degraded, and the DOFs are sacrificed.…”

Section: Introductionmentioning

confidence: 99%

“…In this paper, we present a computationally-efficient reduced dimension-based DOA estimation method for generalized co-prime planar arrays. Different from the separate processing for each subarray [ 17 , 18 , 19 , 20 ], we use the received data of the two subarrays as a whole, which can avoid mutual information loss. In terms of the achievable DOFs, the methods in [ 17 , 18 , 19 , 20 ] only utilize their own data for each subarray, and the DOFs will be halved.…”

Section: Introductionmentioning

confidence: 99%

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Reduced Dimension Based Two-Dimensional DOA Estimation with Full DOFs for Generalized Co-Prime Planar Arrays

Sun

Lan

Zhang

2018

Sensors

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In this paper, we investigate the problem of two-dimensional (2D) direction-of-arrival (DOA) estimation for generalized co-prime planar arrays. The classic multiple signal classification (MUSIC)-based methods can provide a superior estimation performance, but suffer from a tremendous computational burden caused by the 2D spectral search. To this end, we reduce the 2D problem into a one-dimensional (1D) one and propose a reduced dimension partial spectral search estimation method, which can compress the search region into a small 1D sector. Moreover, the proposed method can utilize the full information of the entire array without degrees-of-freedom loss. Furthermore, an iterative approach is also proposed to reduce complexity and improve performance. Simulation results show that the proposed methods can provide improved performance with substantially reduced complexity, as compared to other state-of-the-art methods.

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Two-Dimensional Direction of Arrival Estimation for Coprime Planar Arrays via Polynomial Root Finding Technique

Cited by 31 publications

References 26 publications

An Efficient DOA Estimation Method for Passive Surveillance System Based on Troposcatter

An Efficient DOA Estimation Method for Passive Surveillance System Based on Troposcatter

Hole Locations and a Filling Method for Coprime Planar Arrays for DOA Estimation

Reduced Dimension Based Two-Dimensional DOA Estimation with Full DOFs for Generalized Co-Prime Planar Arrays

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