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A High-Resolution and Low-Complexity DOA Estimation Method with Unfolded Coprime Linear Arrays.
Wei He1, Xiao Yang2, Yide Wang2
1School of Information Engineering, Guangdong University of Technology, Guangzhou 510006, China.
Sensors (Basel, Switzerland)
|January 8, 2020
Summary
This study introduces an improved direction-of-arrivals (DOA) estimation for unfolded coprime linear arrays (UCLA). The new method enhances resolution and accuracy while significantly reducing computational complexity.
Area of Science:
- Signal Processing
- Array Signal Processing
- Electromagnetics
Background:
- Direction-of-Arrivals (DOA) estimation is crucial for applications like radar and sonar.
- Unfolded Coprime Linear Arrays (UCLA) offer large apertures and full degrees of freedom (DOFs).
- Existing DOA methods for UCLA face challenges with low resolution and high computational cost.
Purpose of the Study:
- To propose an improved DOA estimation method for UCLA.
- To enhance resolution and reduce computational complexity compared to existing techniques.
- To leverage the uniform properties of UCLA subarrays for better performance.
Main Methods:
- Averaging diagonal elements of self-covariance matrices to improve accuracy.
- Utilizing a polynomial root finding method to replace exhaustive peak searching.
- Exploiting the inherent uniform properties within UCLA subarrays.
Main Results:
- The proposed method achieves higher resolution in DOA estimation.
- Demonstrates improved estimation performance compared to conventional approaches.
- Significantly reduces computational complexity.
Conclusions:
- The novel DOA estimation method offers superior performance for UCLA.
- Provides a more efficient and accurate solution for array signal processing.
- Addresses the limitations of existing methods in terms of resolution and complexity.
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