A Novel Direction-of-Arrival Estimation via Phase Retrieval with Unknown Sensor Gain-and-Phase Errors

Area of Science:

• Signal Processing
• Array Signal Processing
• Electromagnetics

Background:

• High-resolution direction-of-arrival (DOA) estimation algorithms assume perfect system models.
• Practical systems often exhibit sensor gain-and-phase errors, degrading estimation performance.
• Existing methods struggle with these imperfections, particularly gain errors.

Purpose of the Study:

• To develop a novel framework for robust DOA estimation in the presence of sensor gain-and-phase errors.
• To overcome limitations of existing phase retrieval-based approaches.
• To enhance the accuracy and reliability of DOA estimation in real-world scenarios.

Main Methods:

• A compensated covariance matrix is utilized to eliminate gain errors.
• A data preprocessing technique extracts essential magnitude information from a single covariance matrix column.
• The phase retrieval problem is formulated and solved using the sparse feasible point pursuit algorithm.
• Known DOAs are used as reference sources to resolve model ambiguities.

Main Results:

• The proposed method effectively eliminates sensor gain errors.
• Magnitude information is preserved during data preprocessing.
• Accurate DOA estimates are obtained by solving the formulated phase retrieval problem.
• The approach demonstrates superior performance compared to existing state-of-the-art methods in numerical simulations.

Conclusions:

• The novel framework provides an effective solution for DOA estimation with sensor gain-and-phase errors.
• The proposed preprocessing and solving methods are efficient and preserve critical information.
• The technique offers improved accuracy and robustness for DOA estimation in practical array signal processing systems.