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Direct Localization of Multiple Noncircular Sources With a Moving nested array

IEEE ACCESS 2019年 7卷 101106-101116页

作者： Kumar, Gowri Ponnusamy, Palanisamy Amiri, Iraj Sadegh Natl Inst Technol Dept Elect & Commun Engn Tiruchirappalli 620015 Tamil Nadu India Ton Duc Thang Univ Adv Inst Mat Sci Computat Opt Res Grp Ho Chi Minh City 758307 Vietnam Ton Duc Thang Univ Fac Appl Sci Ho Chi Minh City Vietnam

This paper proposes a subspace data fusion (SDF)-based direct positioning determination (DPD) method for noncircular sources with a moving nested array (NA). The DPD algorithms using a uniform linear array (ULA) and coprime (CP) array are available in the existing literature. Sparse arrays have larger apertures than ULAs, which enhances degrees of freedom (DOFs). However, the existing sparse CP arrays have limited DOF and also have poor detecting ability. In this paper, the physical sensors of NA are rearranged to obtain a difference sum NA (DSNA) and second-order super NA (II-SNA). The rearranged NA sensors are seen to increase array aperture. The noncircular characteristics of the sources are also used to improve accuracy in positioning. To obtain high DOF in NA, DSNA, and II-SNA, the covariance matrices are vectorized. The coherency of the virtual array is resolved by applying the spatial smoothing technique. Finally, the SDF-based DPD is used to establish the cost function and the target is localized. The simulation results are provided for the NA, DSNA, and II-SNA and are compared with the existing CP array DPD algorithm. The results show that the proposed method shows significant enhancement in localization accuracy. The Cramer-Rao lower bound (CRLB), complexity, and performance comparisons are also described in this paper.

关键词： Difference and sum nested array direct position determination nested array second order super nested array

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