MIMO Radar Accurate 3-D Imaging and Motion Parameter Estimation for Target with Complex Motions.

Area of Science:

• Radar Systems Engineering
• Signal Processing
• Computational Electromagnetics

Background:

• Accurate localization and imaging of targets with complex motions are crucial for advanced radar applications.
• Traditional methods often struggle with precision and basis mismatch issues in compressive sensing (CS) techniques.
• Characterizing targets requires multi-dimensional signal models that include position, translation, and rotational velocity.

Purpose of the Study:

• To propose a novel three-dimensional (3-D) multiple-input multiple-output (MIMO) radar localization and imaging method.
• To accurately estimate target motion parameters, including translation and rotation, for complex moving targets.
• To enhance precision and avoid basis mismatch issues inherent in traditional CS methods.

Main Methods:

• Development of a multi-dimensional signal model incorporating 3-D position, translation velocity, and angular velocity.
• Transformation of the signal model into three-joint 2-D parametric models based on motion characteristics.
• Application of a gridless atomic norm optimization method for improved precision and basis mismatch avoidance.
• Utilizing the covariance matrix derived from semi-definite programming (SDP) for parameter estimation.
• Employing Estimating Signal Parameters via Rotational Invariance Techniques (ESPRIT) for position estimation.
• Implementing a Least Square (LS) method for motion parameter estimation.
• Performing pairing correction to eliminate registration errors based on resolution performance analysis.

Main Results:

• The proposed method achieves high-precision 3-D localization and imaging without requiring a spectral search process.
• Accurate estimation of motion parameters (translation and rotation) is demonstrated.
• The technique effectively detects subtle changes in target posture.
• Simulation results validate the method's efficiency and accuracy in localization and imaging with motion parameter estimation.

Conclusions:

• The developed 3-D MIMO radar method offers a robust solution for accurate localization and imaging of targets with complex motions.
• The integration of atomic norm optimization and ESPRIT provides enhanced precision and parameter estimation capabilities.
• This approach significantly improves radar performance by enabling detailed characterization of moving targets.