DOA estimation based on the difference and sum coarray for coprime arrays

Wang, Xinghua; Chen, Zhenhong; Ren, Shiwei; Cao, Shan

doi:10.1016/j.dsp.2017.06.013

Cited by 72 publications

(84 citation statements)

References 17 publications

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“…a(θ k ) = e jπs 1 sin (θ k ) , e jπs 2 sin (θ k ) , • • • , e jπs N sin (θ k ) T is the steering vector associated with θ k and the superscript [•] T represents the transpose operation. The k-th signal in s(t) has the form s k (t) = u k e jω k t [22,27], where u k is the deterministic complex amplitude and ω k denotes the corresponding small frequency offset. And, this typical signal characteristic can be found in simple pulse radar used for remote search, air traffic control, and so on [1,24,28].…”

Section: System Modelmentioning

confidence: 99%

“…m and n are sensor indexes, which satisfy m n. τ represents the time lag and it is not equal to 0. From [22], we know that R s k s k (τ) = |u k | 2 e jω k τ has the same form as s k (t). Accordingly, it can be seen as the k-th equivalent signal with power |u…”

Section: System Modelmentioning

confidence: 99%

“…In recent years, sum coarray (SCA) of sparse array has attracted much attention since it can improve the DOA estimation performance [22][23][24][25][26]. More specifically, to obtain the virtual array composed of sum-difference coarray (SDCA) in a passive DOA estimation system, researchers in [22] utilized the spatial and temporal information jointly to design a vectorized conjugate augmented MUSIC (VCAM) method. By using the elements of SCA to fill in the holes of DCA, the VCAM method can achieve the increase of continuous DOFs and thus improve the detection performance of CPA.…”

Section: Introductionmentioning

confidence: 99%

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Design of Novel Nested Arrays Based on the Concept of Sum-Difference Coarray

Peng

Hou

et al. 2020

Electronics

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Nested arrays have recently attracted considerable attention in the field of direction of arrival (DOA) estimation owing to the hole-free property of their virtual arrays. However, such virtual arrays are confined to difference coarrays as only spatial information of the received signals is exploited. By exploiting the spatial and temporal information jointly, four kinds of novel nested arrays based on the sum-difference coarray (SDCA) concept are proposed. To increase the degrees of freedom (DOFs) of SDCA, a modified translational nested array (MTNA) is introduced first. Then, by analyzing the relationship among sensors in MTNA, we give the specific positions of redundant sensors and remove them later. Finally, we derive the closed-form expressions for the proposed arrays as well as their SDCAs. Meanwhile, different index sets corresponding to the proposed arrays are also designed for their use in obtaining the desirable SDCAs. Moreover, the properties regarding DOFs of SDCAs and physical apertures for the proposed arrays are analyzed, which prove that both the DOFs and physical apertures are improved. Simulation results are provided to verify the superiority of the proposed arrays.

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Section: System Modelmentioning

confidence: 99%

Section: System Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Design of Novel Nested Arrays Based on the Concept of Sum-Difference Coarray

Peng

Hou

et al. 2020

Electronics

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“…In this section, we improve the Vectorized Conjugate Augmented MUSIC (VCAM) algorithm [30] and apply it onto 2D DOA estimation.…”

Section: D Vectorized Conjugate Augmented Music Algorithmmentioning

confidence: 99%

“…In this paper, we improve the vectorized conjugate augmented MUSIC (VCAM) algorithm [30,31] and apply it to 2D DOA estimation based on the second-order statistics. Firstly, we utilize both the spatial information and the temporal information to construct a conjugate augmented correlation vector.…”

Section: Introductionmentioning

confidence: 99%

Improved 2D Coprime Array Structure with the Difference and Sum Coarray Concept

et al. 2020

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Recently, the difference and sum (diff-sum) coarray has attracted much attention in one-dimensional direction-of-arrival estimation for its high degrees-of-freedom (DOFs). In this paper, we utilize both the spatial information and the temporal information to construct the diff-sum coarray for planar sparse arrays. The diff-sum coarray contains both the difference coarray and the sum coarray, which provides much higher DOFs than the difference coarray alone. We take a planar coprime array consisting of two uniform square subarrays as the array model. To fully use the aperture-extending ability of the diff-sum coarray, we propose two novel configurations to improve the planar coprime array. The first configuration compresses the inter-element spacing of one subarray and results in a larger consecutive area in the coarray. The second configuration rearranges the two subarrays and introduces a proper separation between them, which can significantly reduce the redundancy of the diff-sum coarray and increase the DOFs. Besides, we derive the closed-form expressions of the central consecutive ranges in the coarrays of the proposed array configurations. Simulations verify the superiority of the proposed array configurations.

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