An Enhanced Spatial Smoothing Technique of Coherent DOA Estimation with Moving Coprime Array

Area of Science:

• Signal Processing
• Array Signal Processing
• Electromagnetics

Background:

• Direction of Arrival (DOA) estimation is crucial for various applications.
• Coherent signals and sparse arrays pose challenges for traditional DOA estimation methods.
• Existing spatial smoothing techniques are incompatible with sparse arrays like Moving Coprime Arrays (MCA).

Purpose of the Study:

• To develop an enhanced spatial smoothing method for DOA estimation of coherent signals using MCA.
• To overcome the limitations of traditional methods in sparse array configurations.
• To enable the application of super-resolution algorithms like MUSIC in challenging scenarios.

Main Methods:

• Combining signals from MCA at different times to create a virtual dense array.
• Computing the covariance matrix and deriving the signal subspace via eigenvalue decomposition.
• Applying enhanced spatial smoothing to the signal subspace for rank recovery.

Main Results:

• The proposed method successfully estimates the DOA of coherent signals using the MUSIC algorithm.
• Simulation results demonstrate superior performance compared to conventional techniques.
• Significant improvements are observed in low signal-to-noise ratio conditions.

Conclusions:

• The enhanced spatial smoothing method effectively addresses DOA estimation challenges with coherent signals in MCA.
• This technique broadens the applicability of super-resolution algorithms in sparse array systems.
• The proposed algorithm offers a robust solution for improved DOA estimation accuracy.