Computationally Efficient Sources Location Method for Nested Array via Massive Virtual Difference Co-Array

Area of Science:

• Signal Processing
• Array Signal Processing
• Electromagnetics

Background:

• Direction of Arrival (DOA) estimation is crucial for applications like radar and wireless communications.
• Existing methods, such as spatial smoothing (SS) subspace-based techniques for nested arrays, often reduce effective array aperture.
• Conventional Discrete Fourier Transform (DFT) methods are limited by the Rayleigh threshold and do not fully exploit array geometry.

Purpose of the Study:

• To develop a novel DFT-based method for DOA estimation that maximizes the utilization of the nested array's aperture.
• To enhance DOA estimation accuracy by incorporating a phase rotation operation.
• To reduce computational complexity compared to traditional subspace-based methods.

Main Methods:

• Generating a massive virtual difference co-array from a nested array configuration.
• Applying a phase rotation operation to the DFT of the virtual difference co-array.
• Utilizing the full array aperture, unlike spatial smoothing methods.

Main Results:

• The proposed DFT method achieves superior DOA estimation performance compared to SS subspace-based methods, especially for far-field sources.
• The method effectively leverages massive virtual difference co-arrays with numerous virtual sensors.
• Significant reduction in computational cost is achieved due to the Fast Fourier Transform (FFT) implementation.

Conclusions:

• The novel DFT method offers enhanced accuracy and efficiency for DOA estimation with nested arrays.
• Full array aperture utilization and phase rotation are key to the method's improved performance.
• The proposed approach presents a computationally advantageous alternative to existing subspace-based DOA estimation techniques.