Failed Sensor Localization Using Amplitude-Only Near-Field Data

Zhang, Ying; Wang, Wenjing; Wang, Tingjing; Zhao, Huapeng

doi:10.1109/lawp.2018.2821153

Cited by 7 publications

(8 citation statements)

References 14 publications

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“…A convex optimization problem is formulated to restore the array excitation. Array diagnosis of a planar array and a conformal array have been realized using the proposed method and the conventional mathod [17] in the presence of frequency shifting error and element position error. Computer simulation results show that the proposed method gives smaller RMSE and lower DER than those of the conventional method.…”

Section: Discussionmentioning

confidence: 99%

“…Since (9b) leads to a combinational optimization problem, replace it with its convex surrogate: min C( ) tr {C( )}. (9) can be transformed to a semi-definite progamming problem, which can be solved using CVX or ADMM [17].…”

Section: B Array Mismatchmentioning

confidence: 99%

“…It is observed that there are two failing elements in this trial. The middle and right subfigures show the restored array excitation using the proposed and conventional method [17], respectively. It is observed that the proposed method is able to accurately restore the array excitation and locate the failing elements, while the conventional method fails to do so.…”

Section: A Array Diagnosis In the Presence Of Frequency Shifting Errormentioning

confidence: 99%

“…However, phase measuring is usually cumbersome and expensive. Therefore, array diagnosis methods using amplitude-only measurements attracted much interests [17]- [19]. These methods restored array excitation by solving nonlinear optimization problems which are usually transformed or relaxed to convex optimization problems.…”

Section: Introductionmentioning

confidence: 99%

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Robust Array Diagnosis Against Array Mismatch Using Amplitude-Only Far Field Data

Zhang

Wang

2019

IEEE Access

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This paper presents an array diagnosis method using amplitude-only far-field data robust against array mismatch. The considered array mismatch includes frequency shifting error and element position error. The erroneous array manifold is approximated by its first-order Taylor series expansion. To restore the actual array excitation, a convex optimization problem minimizing the 2-norm of the array excitation vector based on Gaussian probability distribution is formulated. Besides, the prior knowledge on ideal array excitation and array mismatch are utilized to facilitate array excitation restoration. The alternating direction method of multipliers which performs well with the large-scale data is applied to solve the proposed optimization problem. Computer simulations are conducted to verify the validity and superiority of the proposed method. It is shown that in the presence of array mismatch, the proposed method provides better accuracy of the restored array excitation and smaller diagnosis error rate than the method which does not consider array mismatch. Furthermore, results using experimental data are also included to verify the validity of the proposed method. INDEX TERMS ADMM, amplitude-only, array diagnosis, array mismatch, far field.

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Section: Discussionmentioning

confidence: 99%

Section: B Array Mismatchmentioning

confidence: 99%

Section: A Array Diagnosis In the Presence Of Frequency Shifting Errormentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Robust Array Diagnosis Against Array Mismatch Using Amplitude-Only Far Field Data

Zhang

Wang

2019

IEEE Access

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“…In real applications, phase measuring is expensive and cubersome. Therefore, array diagnosis methods using amplitude-only field data appear, which have been verified to be able to achieve satisfactory array diagnosis results [8]- [10].…”

Section: Introductionmentioning

confidence: 98%

Convex Optimization for Array Diagnosis Using Amplitude-Only Far Field Data in Impulsive Noise Environment

et al. 2019

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In this paper, an array diagnosis method using amplitude-only far-field data in impulsive noise environment is proposed. For amplitude-only far-field data, the power of the observed field is quadratic with respect to array excitation, which leads to a nonlinear inverse problem to restore array excitation. Such a nonlinear inverse problem is transformed into a linear inverse problem, where array excitation vector is replaced by a lifted vector. Based on the structure of the lifted vector, an absolute array excitation vector that has an identical structure to that of array excitation vector is defined. Since these two vectors share the same structure, it is assumed that they also share the same kind of probability distribution. Specifically, the generalized Gaussian distribution with different parameters to address different element failing rates is used to model the probability distribution of the real array excitation vector and the absolute array excitation vector. To model the impulsive noise, the Laplacian probability distribution function is used. The maximum a posterior criterion is adopted to formulate the optimization problem that is eventually found to be convex. However, this convex optimization problem does not have an analytical solution. To solve it, a proximal gradient method is applied, which yields an iterative update algorithm. Finally, computer simulations and experiment are conducted to verify the validity and superiority of the proposed method.

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A fast failure diagnosis method based on structure features of planar arrays

Sun¹,

Zhang²,

Kernec³

et al. 2023

IET Conf. Proc.

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Array antennas are the basic components which are widely used in radar systems. In this paper, a fast failure diagnosis method is proposed based on structure information of planar arrays when the number of faulty elements is small. The proposed algorithm reduces the time spent locating the failed elements while maintaining the accuracy of the localization. Firstly, the sparse diagnosis model of a failure planar array is introduced. Considering the structure features of planar arrays, the vertical and horizontal elevation plane of the field pattern are used to decide the rows and columns of the failed elements, respectively. Besides, a new smaller subarray is constructed based on the rows and columns above and further diagnosed by the new measured field pattern. With the aid of theoretical analysis and simulation validation, it is shown that the proposed diagnosis method can localize faults faster compared with conventional diagnosis methods.

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Failed Sensor Localization Using Amplitude-Only Near-Field Data

Cited by 7 publications

References 14 publications

Robust Array Diagnosis Against Array Mismatch Using Amplitude-Only Far Field Data

Robust Array Diagnosis Against Array Mismatch Using Amplitude-Only Far Field Data

Convex Optimization for Array Diagnosis Using Amplitude-Only Far Field Data in Impulsive Noise Environment

A fast failure diagnosis method based on structure features of planar arrays

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