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Direction of Arrival Estimation of Generalized Nested Array via Difference-Sum Co-Array.

Yule Zhang1,2, Guoping Hu2, Hao Zhou2

  • 1Graduate College, Air Force Engineering University, Xi'an 710051, China.

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|January 21, 2023
PubMed
Summary
This summary is machine-generated.

A new generalized nested array via difference-sum co-array (GNA-DSCA) configuration enhances direction of arrival (DOA) estimation. This novel approach offers more degrees of freedom (DOFs) and a wider virtual aperture than existing methods.

Keywords:
atomic normdegrees of freedomdifference–sum co-arraydirection of arrival estimationgeneralized nested arraysparse array

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Area of Science:

  • Array Signal Processing
  • Electromagnetics
  • Statistical Signal Processing

Background:

  • Difference Co-Array (DCA) methods offer limited enhancement in degrees of freedom (DOFs) for Direction of Arrival (DOA) estimation.
  • Existing sparse array configurations face challenges in maximizing virtual aperture and estimation performance.

Purpose of the Study:

  • To propose a novel Generalized Nested Array via Difference-Sum Co-Array (GNA-DSCA) configuration for improved DOA estimation.
  • To systematically analyze the properties of the GNA-DSCA, including its DOFs and virtual aperture.
  • To enhance the accuracy of DOA estimation by addressing performance degradation caused by non-uniform virtual arrays.

Main Methods:

  • Construction of the Difference-Sum Co-Array (DSCA) model utilizing both temporal and spatial information.
  • Systematic analysis of the Difference Co-Array (DCA) and Sum Co-Array (SCA) for the Generalized Nested Array (GNA).
  • Derivation of closed-form expressions for DOFs under determined dilation factors.
  • Application of an Atomic Norm Minimization (ANM) based hole-filling strategy.

Main Results:

  • The GNA-DSCA configuration provides a more flexible design and significantly more DOFs compared to the GNA-DCA.
  • Larger dilation factors in GNA-DSCA result in a substantially wider virtual aperture, outperforming existing DSCA-based sparse arrays.
  • The ANM hole-filling strategy effectively mitigates performance degradation from non-uniform virtual arrays, enabling accurate DOA estimation.

Conclusions:

  • The proposed GNA-DSCA configuration offers superior virtual array properties and enhanced DOA estimation performance.
  • The GNA-DSCA presents a more attractive and flexible alternative for high-resolution DOA estimation applications.
  • The combination of GNA-DSCA and ANM hole-filling provides a robust solution for accurate direction finding.