Direct Position Determination of Noncircular Sources with Multiple Nested Arrays: Reduced Dimension Subspace Data Fusion | Zendy

Yang Qian | Zendy; Dalin Zhao | Zendy; Haowei Zeng | Zendy

Open Access

Direct Position Determination of Noncircular Sources with Multiple Nested Arrays: Reduced Dimension Subspace Data Fusion

Author(s) -

Yang Qian,

Dalin Zhao,

Haowei Zeng

Publication year - 2021

Publication title -

wireless communications and mobile computing

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.42

H-Index - 64

eISSN - 1530-8677

pISSN - 1530-8669

DOI - 10.1155/2021/9950518

Subject(s) - computer science , subspace topology , position (finance) , dimension (graph theory) , artificial intelligence , sensor fusion , fusion , algorithm , pattern recognition (psychology) , data mining , mathematics , combinatorics , finance , economics , linguistics , philosophy

Direct position determination (DPD) of noncircular (NC) sources with multiple nested arrays (NA) is investigated in this paper. Noncircular sources are used to expand the dimension of the received signal matrix, so the number of identifiable information sources and the accuracy of direct position determination are improved. Furthermore, nested array increases spatial degree of freedom. In this paper, the high-dimensional search problem of noncircular sources is investigated. Therefore, we propose algorithm dimension reduction subspace data fusion (RD-SDF) to reduce complexity and increase positioning accuracy. Simulation results show that the proposed RD-SDF algorithm for multiple nested arrays with noncircular sources has improved positioning accuracy with higher spatial degree of freedom than SDF, Capon, and two-step algorithms with uniform linear array and circular sources (CS).

The content you want is available to Zendy users.

Already have an account? Click here to sign in.

Having issues? You can contact us here

Accelerating Research