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A Computationally Efficient MUSIC Algorithm with an Enhanced DOA Estimation Performance for a Crossed-Dipole Array.

Hao Nan¹, Xiaofeng Ma¹, Yubing Han¹

¹School of Electronic and Optical Engineering, Nanjing University of Science and Technology, Nanjing 210094, China.

Sensors (Basel, Switzerland)

|September 19, 2025

Summary

This summary is machine-generated.

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An improved real-valued dimension-reduction MUSIC (IRDR-MUSIC) algorithm enhances signal processing for crossed-dipole arrays. This novel approach significantly reduces computational complexity and improves multi-target resolution with minimal performance loss.

Area of Science:

Signal Processing
Array Signal Processing
Electromagnetics

Background:

MUSIC algorithm limitations in computational complexity and performance.
Need for efficient algorithms in array signal processing.
Challenges with real-valued processing of complex covariance matrices.

Purpose of the Study:

To propose an improved real-valued dimension-reduction MUSIC (IRDR-MUSIC) algorithm.
To enhance computational efficiency and multi-target resolution for crossed-dipole arrays.
To address information loss in traditional real-valued covariance matrix constructions.

Main Methods:

Derivation of conjugate symmetry in the manifold vector's spatial component.
Construction of real-valued sum and difference covariance matrices.

Keywords:

computationally efficient real-valued operation sum–difference covariance matrix

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Last Updated: Jan 17, 2026

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Development of a joint sum-difference covariance matrix to preserve complete information.

Application of singular-value decomposition in the real-valued domain.

Main Results:

The IRDR-MUSIC algorithm significantly reduces computational complexity.
The proposed algorithm achieves enhanced performance, comparable to complex-valued methods.
Superiority in multi-target resolution and computational efficiency demonstrated.
Reduced spatial spectrum search range by half.

Conclusions:

The IRDR-MUSIC algorithm offers a computationally efficient and high-performance solution for array signal processing.
It effectively overcomes the limitations of existing dimension-reduction MUSIC algorithms.
The joint sum-difference covariance matrix preserves crucial information for improved accuracy.