An Efficient and Fast Algorithm for Estimating the Frequencies of 2-D Superimposed Exponential Signals in Presence of Multiplicative and Additive Noise

Bian, Jiawen; Li, Hongwei; Peng, Hongxia; Xing, Jing

doi:10.1007/978-3-642-01216-7_20

Cited by 5 publications

(7 citation statements)

References 11 publications

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“…The whole procedure of the TSI algorithm in this study is quite similar to that in [27] and summarized as follows.…”

Section: A Doa Estimation Based On Tsi Algorithmmentioning

confidence: 97%

“…The main advantage of this algorithm is that it could provide consistent and asymptotically efficient estimations using only three steps of iterations. The method has been extended to 2-D conditions in [25] and superimposed exponential signals in [26] and [27]. In this paper, the TSI algorithm is further extended to the complex-valued multiplicative and additive noise condition, and provides a robust DOA estimation in the presence of phase and gain errors.…”

Section: A Doa Estimation Based On Tsi Algorithmmentioning

confidence: 99%

“…For the th snapshot, the 2-D fast Fourier transform (FFT) is employed before the TSI algorithm to provide an original estimation of similar to the method presented in [27]. The maximum of the 2-D FFT spectrum is taken as the original estimation, and the obtained Fourier frequencies take on the forms and for some integer and .…”

Section: A Doa Estimation Based On Tsi Algorithmmentioning

confidence: 99%

“…For the one-source calibration and large URA conditions studied in this paper, the 2-D direction finding could be realized through an efficient TSI algorithm which provides a robust estimation of the source direction. The TSI algorithm was proposed in [24]- [27] to estimate the parameters of the sinusoidal signals coupled with multiplicative and/or additive noises. To estimate the 2-D direction of the calibrator source in the presence of array perturbations, the TSI algorithm presented in [27] is extended from the real-valued multiplicative noise condition to a complex-valued condition in this paper before being adopted.…”

Section: Introductionmentioning

confidence: 99%

“…The TSI algorithm was proposed in [24]- [27] to estimate the parameters of the sinusoidal signals coupled with multiplicative and/or additive noises. To estimate the 2-D direction of the calibrator source in the presence of array perturbations, the TSI algorithm presented in [27] is extended from the real-valued multiplicative noise condition to a complex-valued condition in this paper before being adopted. The gain and phase errors are then estimated using the obtained direction estimation, and adjusted further using a maximum a posteriori (MAP) approach implemented through the second-order cone programming (SOCP) algorithms.…”

Section: Introductionmentioning

confidence: 99%

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Gain and Phase Autocalibration of Large Uniform Rectangular Arrays for Underwater 3-D Sonar Imaging Systems

Yuan

Jiang

Chen

2014

IEEE J. Oceanic Eng.

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In this paper, a new calibration method for gain and phase errors in large uniform rectangle arrays is proposed for underwater 3-D sonar imaging systems. It requires only one calibrator source at an unknown position in the far field. An efficient and speedy three-step-iteration algorithm is performed first to provide a robust direction-of-arrival (DOA) estimator in the presence of gain and phase errors. It then follows with the gain and phase errors estimation using a spatial matched filter. Finally, a maximum a posteriori (MAP) exercise is executed to further adjust the estimated phase parameters and the source direction. The statistical performance of the proposed algorithm will be demonstrated and compared to representative methods. It will be shown that the proposed method is computationally effective and asymptotically efficient in Monte Carlo simulations.Index Terms-Array signal processing, autocalibration, gain and phase error, underwater 3-D sonar imaging, uniform rectangular array (URA).

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“…The whole procedure of the TSI algorithm in this study is quite similar to that in [27] and summarized as follows.…”

Section: A Doa Estimation Based On Tsi Algorithmmentioning

confidence: 97%