Coherent DOA Estimation Algorithm with Co-Prime Arrays for Low SNR Signals

Area of Science:

• Signal Processing
• Array Signal Processing
• Electromagnetics

Background:

• Direction of Arrival (DOA) estimation is crucial for applications like radar and wireless communications.
• Traditional methods struggle with coherent signals, low signal-to-noise ratio (SNR), and limited snapshots.
• Co-prime arrays offer advantages but require robust estimation techniques.

Purpose of the Study:

• To develop an improved algorithm for Direction of Arrival (DOA) estimation of coherent signals in co-prime arrays.
• To overcome the limitations of existing spatial smoothing and subspace algorithms under challenging conditions.
• To enhance the performance of DOA estimation in terms of accuracy, resolution, and robustness.

Main Methods:

• An Enhanced Spatial Smoothing (ESS) algorithm was developed, incorporating a space-time correlation matrix.
• The ESS algorithm utilizes de-noising and decoherence techniques.
• The Estimating Signal Parameter via Rotational Invariance Techniques (ESPRIT) algorithm is applied for final DOA estimation.

Main Results:

• The proposed ESS algorithm demonstrates superior performance compared to other decoherence methods.
• At -8 dB SNR and 150 snapshots, the Mean Square Error (MSE) approaches the Cramér-Rao bound (CRB).
• The probability of resolution (PoR) exceeds 88%, and estimation accuracy surpasses 90% for angular resolutions greater than 4°.

Conclusions:

• The Enhanced Spatial Smoothing (ESS) algorithm effectively addresses DOA estimation challenges with coherent signals.
• The algorithm provides significant improvements in low SNR and limited snapshot scenarios.
• ESS offers a robust and accurate solution for DOA estimation in co-prime arrays.