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SPICE-ML Algorithm for Direction-of-Arrival Estimation.

Yu Zheng^1,2, Lutao Liu¹, Xudong Yang¹

¹College of Information and Communication Engineering, Harbin Engineering University, Harbin 150001, China.

Sensors (Basel, Switzerland)

|December 28, 2019

Summary

This summary is machine-generated.

This study introduces an improved direction-of-arrival estimation algorithm. It enhances signal power accuracy and overcomes grid limitations for better performance in signal processing applications.

Keywords:

covariance fitting criterion direction-of-arrival estimation maximum likelihood estimation sparse iterative covariance-based estimation approach

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Area of Science:

Signal Processing
Array Signal Processing

Background:

Sparse iterative covariance-based estimation (SPICE) estimates signal angle and power.
SPICE suffers from inaccurate power estimation and direction grid limitations.

Purpose of the Study:

To develop an enhanced algorithm for accurate direction-of-arrival (DOA) estimation.
To improve signal power estimation accuracy and overcome grid limitations inherent in SPICE.

Main Methods:

Combines SPICE with maximum likelihood estimation (MLE).
Introduces an iterative process using the asymptotically minimum variance criterion for power correction.
Develops a refinement procedure by minimizing an MLE function to enhance DOA accuracy.

Main Results:

The proposed algorithm achieves more accurate signal power estimation compared to SPICE.
Enhanced estimation performance beyond the limitations of the direction grid.
Simulation results validate the effectiveness of the combined approach.

Conclusions:

The novel algorithm effectively addresses the limitations of SPICE.
It offers superior accuracy in both signal power and direction-of-arrival estimation.
This method provides a significant advancement for array signal processing applications.