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Gravitational Telescope
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作者 Alexander V. Lukanenkov 《Journal of High Energy Physics, Gravitation and Cosmology》 2016年第2期209-225,共17页
It’s proposed to use a global seismic antenna (GSA) as a gravitational telescope, arbitrary “quiet” seismic stations are its elements, and aperture of GSA must be of the order 10,000 km. The relative displacements ... It’s proposed to use a global seismic antenna (GSA) as a gravitational telescope, arbitrary “quiet” seismic stations are its elements, and aperture of GSA must be of the order 10,000 km. The relative displacements of various points of the Earth are detected by GSA, these displacements are described as quasi-harmonic elliptical signals generated by gravitational waves, their amplitude ≈ 2.5 * 0<sup>?15</sup> m. It is found that these waves cause deformation (strain) of the order h ≈ 10<sup>?21</sup>. Pulsars are a natural source of periodic waves. The fact of confident registration of gravitational wave is confirmed by detection of quasi-harmonic signals in the frequency band near 6.023 Hz for 90 hours (confidence probability of detection is close to 1). It is found that a small part of the rotation energy of associated pulsar (ε ≈ 10<sup>?5</sup>) is expended on the radiation corresponding to the gravitational wave. 展开更多
关键词 Gravitational Waves Gravitational signal Gravitational Telescope Seismic Antenna DEFORMATION optimal signal processing
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DOA estimation via sparse recovering from the smoothed covariance vector 被引量:1
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作者 Jingjing Cai Dan Bao Peng Li 《Journal of Systems Engineering and Electronics》 SCIE EI CSCD 2016年第3期555-561,共7页
A direction of arrival(DOA) estimation algorithm is proposed using the concept of sparse representation. In particular, a new sparse signal representation model called the smoothed covariance vector(SCV) is establ... A direction of arrival(DOA) estimation algorithm is proposed using the concept of sparse representation. In particular, a new sparse signal representation model called the smoothed covariance vector(SCV) is established, which is constructed using the lower left diagonals of the covariance matrix. DOA estimation is then achieved from the SCV by sparse recovering, where two distinguished error limit estimation methods of the constrained optimization are proposed to make the algorithms more robust. The algorithm shows robust performance on DOA estimation in a uniform array, especially for coherent signals. Furthermore, it significantly reduces the computational load compared with those algorithms based on multiple measurement vectors(MMVs). Simulation results validate the effectiveness and efficiency of the proposed algorithm. 展开更多
关键词 array signal processing convex optimization direction of arrival(DOA) estimation sparse representation
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