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An Improved Unfolded Coprime Linear Array Design for DOA Estimation with No Phase Ambiguity.

Pan Gong1, Xiaofei Zhang2

  • 1College of Electronic Information and Integrated Circuits, Nanjing Vocational University of Industry Technology, Nanjing 211106, China.

Sensors (Basel, Switzerland)
|October 16, 2024
PubMed
Summary
This summary is machine-generated.

This study introduces an improved unfolded coprime linear array (IUCLA) to accurately estimate direction of arrival (DOA) by solving phase ambiguity. The novel method enhances target detection and reduces computational complexity for sensor array systems.

Keywords:
Cramer–Rao bound (CRB)direction of arrival (DOA) estimationimproved unfolded coprime linear array (IUCLA)multiple signal classification (MUSIC)sparse array

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Area of Science:

  • Signal Processing
  • Array Signal Processing
  • Electromagnetics

Background:

  • Traditional coprime arrays face limitations in direction of arrival (DOA) estimation due to subarray steering vector conflicts.
  • Existing stacking subarray methods are ineffective for unfolded coprime linear arrays (UCLA) when subarrays share identical source angle steering vectors.
  • Phase ambiguity is a significant challenge in DOA estimation for coprime arrays.

Purpose of the Study:

  • To address the phase ambiguity problem in unfolded coprime linear arrays (UCLA).
  • To propose an improved unfolded coprime linear array (IUCLA) design for enhanced DOA estimation.
  • To develop a spectral peak searching method for improved target detection and angle estimation using the IUCLA.

Main Methods:

  • Reconstruction of the UCLA into an improved unfolded coprime linear array (IUCLA) by relocating the reference element.
  • Introduction of a third coprime integer to create multiple coprime inter-pairs, resolving phase ambiguity.
  • Application of a spectral peak searching algorithm to leverage the full aperture and degrees of freedom (DOFs) of the IUCLA.

Main Results:

  • The proposed IUCLA effectively solves the phase ambiguity problem inherent in UCAs.
  • The spectral peak searching method allows for target detection and accurate angle estimation utilizing the entire array aperture.
  • The method demonstrates reduced computational complexity and avoids additional processing for ambiguity elimination.

Conclusions:

  • The developed IUCLA and associated DOA estimation method provide a superior solution compared to existing techniques.
  • Numerical simulations and Cramer-Rao bound (CRB) analysis validate the effectiveness and performance gains of the proposed approach.
  • This research offers a significant advancement in DOA estimation for sensor array applications.