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Multi-Source Weighted Localization Based on Cascaded DOA-TDOA.

Jinshen Fang1, Jianfeng Li1, Shenghui Zhao1

  • 1College of Electronic and Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China.

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Summary
This summary is machine-generated.

This study introduces a novel cascaded Direction of Arrival (DOA) and Time Difference of Arrival (TDOA) localization algorithm to accurately pinpoint multiple signal sources. The method enhances multi-source separation and refines positioning through iterative weighting, improving accuracy and robustness.

Keywords:
DOATDOAbeam formingmulti-source localization

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Area of Science:

  • Signal Processing
  • Localization Algorithms
  • Array Signal Processing

Background:

  • Time Difference of Arrival (TDOA) localization offers stability and accuracy.
  • Multi-source scenarios complicate TDOA by entangling measurements.
  • Accurate source separation and association are crucial for reliable localization.

Purpose of the Study:

  • To propose a cascaded DOA-TDOA algorithm for robust multi-source localization.
  • To leverage DOA for signal separation and TDOA for precise positioning.
  • To enhance localization accuracy and robustness in complex environments.

Main Methods:

  • DOA estimation and geometric consistency matching for initial coarse positioning.
  • Minimum Variance Distortionless Response (MVDR) spatial filtering for signal separation and SNR enhancement.
  • Iterative weighted least-squares (WLS) localization using Difference-Geometric Dilution of Precision (D-GDOP) for refinement.

Main Results:

  • The proposed algorithm effectively separates multi-source signals.
  • Iterative D-GDOP based weighting significantly improves localization accuracy.
  • Simulations demonstrate superior performance compared to existing methods.

Conclusions:

  • The cascaded DOA-TDOA approach provides a robust solution for multi-source localization.
  • The MVDR filtering and iterative WLS refinement enhance estimation precision.
  • The method offers improved accuracy and robustness in challenging multi-source environments.