• Electronics Optics & Control
  • Vol. 26, Issue 11, 6 (2019)
ZHOU Peng1, SU Ji-bin2, LIU Zhan-he1, DI Jin-hong1, and MIAO Nan1
Author Affiliations
  • 1[in Chinese]
  • 2[in Chinese]
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    DOI: 10.3969/j.issn.1671-637x.2019.11.002 Cite this Article
    ZHOU Peng, SU Ji-bin, LIU Zhan-he, DI Jin-hong, MIAO Nan. A Robust Wave Formation Method Based on Convex Optimization About Spatio-Temporal Data in Sensor Network[J]. Electronics Optics & Control, 2019, 26(11): 6 Copy Citation Text show less

    Abstract

    The convex optimization fusion graph theory is used for modeling analysis, the sensor array signal model is constructed, and the noise and interference subspace steering vector correction is designed.The Semidefinite Relaxation(SDR) and S-process convex optimization analysis are used to model the nonlinear non-convex problem as the Semidefinite Programming(SDP)convex optimization problem, and the covariance matrix model of spatial power spectrum matching is constructed.The robust wave formation method based on convex optimization about spatio-temporal data in the sensor network is obtained.The TDOA and FDOA polymorphic fusion algorithm is proposed to significantly improve the quality of multi-target tracking and achieve precise positioning.Through simulation experiments, it is shown that the proposed method has obvious advantages, and the resolution ability is superior to that of traditional positioning algorithms.
    ZHOU Peng, SU Ji-bin, LIU Zhan-he, DI Jin-hong, MIAO Nan. A Robust Wave Formation Method Based on Convex Optimization About Spatio-Temporal Data in Sensor Network[J]. Electronics Optics & Control, 2019, 26(11): 6
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