Direction of Arrival Estimation of Coherent Wideband Sources Using Nested Array

Area of Science:

• Array Signal Processing
• Electromagnetics and RF Engineering

Background:

• Sparse arrays like nested and coprime arrays offer high DOA estimation accuracy and degrees of freedom (DOF).
• A key limitation of sparse arrays is their struggle with coherent wideband signals due to the assumption of signal independence, which is often violated in complex environments.

Purpose of the Study:

• To develop a robust DOA estimation method for sparse arrays capable of handling coherent wideband signals.
• To overcome the limitations of traditional sparse array methods when dealing with signal correlation.

Main Methods:

• Exploiting the Coherent Signal Subspace Method (CSSM) for wideband signal focusing and decorrelation without pre-estimations.
• Virtualizing the covariance matrix of the sparse array post-decorrelation.
• Applying an enhanced spatial smoothing algorithm to maximize data covariance matrix utilization and improve decorrelation.
• Employing the Multiple Signal Classification (MUSIC) algorithm for final DOA estimation.

Main Results:

• The proposed algorithm demonstrated satisfactory performance in simulations, with Root Mean Square Error (RMSE) varying with Signal-to-Noise Ratio (SNR).
• Achieved superior results compared to state-of-the-art methods, including traditional Incoherent Signal Subspace Method (ISSM), CSSM, and spatial smoothing algorithms.
• Validated through real data tests, achieving a low error of only 0.2 degrees, outperforming existing methods.

Conclusions:

• The developed method effectively addresses the challenge of DOA estimation with coherent wideband signals in sparse arrays.
• The technique offers a significant improvement in accuracy and robustness for direction of arrival estimation in practical scenarios.