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Sparse Reconstruction Based Robust Near-Field Source Localization Algorithm.

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Summary
This summary is machine-generated.

This study introduces robust algorithms for estimating direction-of-arrival (DOA) and range of near-field signals in non-Gaussian impulsive noise. The methods utilize fractional lower order correlation (FLOC) and nonlinear transform correlation (NTC) for improved accuracy.

Keywords:
direction of arrivalimpulsive noisenear-filedrange estimationrobust correlationsparse reconstruction

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Area of Science:

  • Signal Processing
  • Array Signal Processing
  • Statistical Signal Processing

Background:

  • Non-Gaussian impulsive noise is prevalent in real-world environments.
  • Conventional algorithms struggle with impulsive noise due to reliance on second-order statistics.
  • Accurate estimation of direction-of-arrival (DOA) and range is crucial for near-field signals.

Purpose of the Study:

  • To develop robust algorithms for joint DOA and range estimation of near-field signals in impulsive noise.
  • To address the limitations of conventional methods in non-Gaussian impulsive noise environments.
  • To leverage robust correlation techniques for improved localization accuracy.

Main Methods:

  • Modeling non-Gaussian impulsive noise using the α-stable distribution.
  • Employing fractional lower order correlation (FLOC) and nonlinear transform correlation (NTC).
  • Utilizing array symmetry to construct robust far-field approximate correlation vectors for DOA estimation via sparse reconstruction.
  • Applying sparse reconstruction to virtual array outputs for range estimation.

Main Results:

  • Proposed algorithms demonstrate good noise suppression capabilities.
  • Effective joint DOA and range estimation in the presence of non-Gaussian impulsive noise.
  • Simulation results validate the effectiveness of the developed algorithms.

Conclusions:

  • The proposed FLOC and NTC-based algorithms provide robust solutions for near-field signal localization in impulsive noise.
  • Sparse reconstruction techniques enable accurate DOA and range estimation.
  • The methods offer significant advantages over conventional algorithms in challenging noise conditions.