Nonuniform sparse array design for active sensing

Weng, Ching-Chih; Vaidyanathan, P.P.

doi:10.1109/acssc.2011.6190175

Cited by 25 publications

(16 citation statements)

References 16 publications

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“…Unfortunately, the number of elements N in these Reduced Redundancy Arrays (RRAs) scales linearly with aperture L, although generally N ∝ √ L should be achievable. A related case was studied in [16], [17], where MIMO arrays using second-order statistics were considered. However, the resulting optimization problem involved the difference sum co-array, whereas linear processing and the sum co-array [2], [15] are of main interest in this paper.…”

Section: Introductionmentioning

confidence: 99%

Sparse linear nested array for active sensing

Rajamäki

Koivunen

2017

2017 25th European Signal Processing Conference (EUSIPCO)

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Abstract-Sparse sensor arrays can match the performance of fully populated arrays using substantially fewer elements. However, finding the array configuration with the smallest number of elements is generally a computationally difficult problem. Consequently, simple to generate array configurations that may be suboptimal are of high practical interest. This paper presents a novel closed-form sparse linear array configuration designed for active sensing, called the Concatenated Nested Array (CNA). The key parameters of the CNA are derived. The CNA is also compared to the optimal Minimum-Redundancy Array (MRA) in numerical simulations. The CNA is shown to require only about 10% more elements than the MRA in the limit of large apertures.

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Section: Introductionmentioning

confidence: 99%

Sparse linear nested array for active sensing

Rajamäki

Koivunen

2017

2017 25th European Signal Processing Conference (EUSIPCO)

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“…In this regard, C.C. Weng proposed a minimum redundant MIMO array [7], which uses the minimum redundant array as the transmitting and receiving arrays, and performs the difference processing on sum coarray of the MIMO array to obtain the virtual extension of the number of receiving array elements. It can greatly improve the DOF of the array, but usually involves a large amount of computation.…”

Section: Introductionmentioning

confidence: 99%

“…It can greatly improve the DOF of the array, but usually involves a large amount of computation. E. Boudaher proposed a coprime MIMO array [8], which replaced the minimum redundant array [7] with the coprime array. Although the calculation is reduced and the DOF of the array is improved, his difference array is a line array with hole, which leads to the inability to use the Spatial Smoothing (SS) algorithm to decorrelate the signal for accurate DOA estimation.…”

Section: Introductionmentioning

confidence: 99%

An optimizing nested MIMO array with hole-free difference coarray

Liu

Wang

et al. 2018

MATEC Web Conf.

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According to the newly proposed nested MIMO (Multiple-Input Multiple-Input Multiple Output Multiple Array) array design method, we propose to replace the traditional nested array into an optimizing nested array, ie, to optimizing nested MIMO array design. It not only retains the original advantage of nested MIMO array design closed expression with array element position and degree of freedom(DOF), but also greatly improves the array aperture and DOF. Optimizing nested MIMO array firstly uses the optimizing nested array as the transmitting and receiving arrays, and then make the difference set processing for the coarray of MIMO array (coarray, CA). By properly designing the array spacing of the transmitting and receiving arrays, we can obtain a non-porous difference array. When the total number of array elements is given, by analyzing the characteristics of the array structure, the best array element number of the transmitting and receiving arrays can be obtained. Simulation experiments show that compared with the nested MIMO array design, the proposed method can effectively expand the array aperture, increase the DOF, and increase the DOA estimation accuracy of the MIMO radar without increasing the number of actual array elements.

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“…Taking the two level nested arrays as an example, it can obtain ( 2 ) DOF using only ( ) physical sensors. The aforementioned MR array [9] and coprime array [10] are combined with the MIMO array to generate the difference co-array of the sum coarray (DCSC), which further improves the DOFs greatly. Recently, a novel structure of this type, which is called nested MIMO array, is proposed [11].…”

Section: Introductionmentioning

confidence: 99%

Novel Diagonal Reloading Based Direction of Arrival Estimation in Unknown Non-Uniform Noise

Zhou

Shi

et al. 2018

Mathematical Problems in Engineering

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Nested array can expand the degrees of freedom (DOF) from difference coarray perspective, but suffering from the performance degradation of direction of arrival (DOA) estimation in unknown non-uniform noise. In this paper, a novel diagonal reloading (DR) based DOA estimation algorithm is proposed using a recently developed nested MIMO array. The elements in the main diagonal of the sample covariance matrix are eliminated; next the smallest MN-K eigenvalues of the revised matrix are obtained and averaged to estimate the sum value of the signal power. Further the estimated sum value is filled into the main diagonal of the revised matrix for estimating the signal covariance matrix. In this case, the negative effect of noise is eliminated without losing the useful information of the signal matrix. Besides, the degrees of freedom are expanded obviously, resulting in the performance improvement. Several simulations are conducted to demonstrate the effectiveness of the proposed algorithm.

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Nonuniform sparse array design for active sensing

Cited by 25 publications

References 16 publications

Sparse linear nested array for active sensing

Sparse linear nested array for active sensing

An optimizing nested MIMO array with hole-free difference coarray

Novel Diagonal Reloading Based Direction of Arrival Estimation in Unknown Non-Uniform Noise

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