Phased Array Calibration by Binary Compressed Sensing

Baburs, Galina; Caratelli, Diego; Mirmanov, Arman B.

doi:10.2528/pierm18052907

Cited by 3 publications

(3 citation statements)

References 20 publications

(22 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…It is well known that the AM algorithm [22] is an effective tool to solve the optimization problem involved several different subsets of variables, which is employed to solve the optimization problem in Eq. (10) in this paper. Without loss of generality, the off-grid errors are estimated first by fixing the gain-phase uncertainties.…”

Section: The Proposed Algorithmmentioning

confidence: 82%

“…To further verify the convergence of the proposed algorithm, the values of the cost function in Eq. (10) versus iteration number at different SNRs are plotted in Fig. 6.…”

Section: Simulation Results and Rmse Analysismentioning

confidence: 99%

“…Unfortunately, antenna arrays usually suffer from imperfections including the gain-phase uncertainties, mutual couplings, and antenna position errors in practice [9][10][11]. Thus, DOA estimation performance, especially for the antenna sensitive algorithms, will be significantly degraded with the array imperfections.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Self-Calibration Algorithm With Gain-Phase Errors Array for Robust Doa Estimation

Wei¹,

Wang²,

Dong³

et al. 2021

PIER M

View full text Add to dashboard Cite

The performance of direction-of-arrival (DOA) estimation algorithms degrades when a partly calibrated array is adopted due to the existing unknown gain-phase uncertainties. In addition, the spatial discretized searching grid also limits the performance improvement and effectiveness of subspacebased DOA estimation algorithms, especially when the true angles do not lie on the grid points which is referred to the off-grid problem alike. In this paper, a self-calibration DOA estimation algorithm is proposed which solves the array calibration and off-grid problems simultaneously. Firstly, the signal model for a partly calibrated array with gain-phase uncertainties is established. To suppress the offgrid errors, an optimization problem for joint parameters estimation is constructed by substituting the approximation of the steering vector into a newly constructed objective function. The alternative minimization (AM) algorithm is employed to calculate the joint DOA and gain-phase uncertainty estimations. Within each iteration step of the optimization problem, a closed-form solution is derived that guarantees the convergence of the proposed algorithm. Furthermore, the Cramér-Rao bound (CRB) for the partly calibrated arrays with unknown gain-phase uncertainties is also derived and analyzed in the paper. Simulation results demonstrate the effectiveness of the proposed algorithm.

show abstract

Section: The Proposed Algorithmmentioning

confidence: 82%

“…To further verify the convergence of the proposed algorithm, the values of the cost function in Eq. (10) versus iteration number at different SNRs are plotted in Fig. 6.…”

Section: Simulation Results and Rmse Analysismentioning

confidence: 99%

See 1 more Smart Citation

Self-Calibration Algorithm With Gain-Phase Errors Array for Robust Doa Estimation

Wei¹,

Wang²,

Dong³

et al. 2021

PIER M

View full text Add to dashboard Cite

show abstract

Array Excitation Error Calibration

He,

Gao,

Zhang

et al. 2023

Modern Antenna

View full text Add to dashboard Cite

Impact Analysis and Calibration Methods of Excitation Errors for Phased Array Antennas

Gao

Zhang

2021

IEEE Access

View full text Add to dashboard Cite

Phased array antennas have played a very important role in many different areas and applications. It requires precise excitation of each antenna element by various synthesis techniques to obtain desired array pattern features. However, due to reasons such as manufacturing imperfections, component aging, and temperature variation, the realistic antenna element excitation inevitably differs from their expected values in practice. This paper presents a tutorial-like review to deal with excitation errors for phased array antennas. Two kinds of analysis methods, probabilistic methods and interval arithmetic (IA) based methods, are presented to evaluate the effects of excitation errors for phased array antennas. State-ofthe-art calibration methods along with various signal processing techniques are reviewed, their advantages and challenges are discussed in a comparative manner. Some other common errors and open research directions are also presented.INDEX TERMS Phased array antenna, excitation error, interval arithmetic, array calibration.

show abstract

Phased Array Calibration by Binary Compressed Sensing

Cited by 3 publications

References 20 publications

Self-Calibration Algorithm With Gain-Phase Errors Array for Robust Doa Estimation

Self-Calibration Algorithm With Gain-Phase Errors Array for Robust Doa Estimation

Array Excitation Error Calibration

Impact Analysis and Calibration Methods of Excitation Errors for Phased Array Antennas

Contact Info

Product

Resources

About