Joint DOA and DOD Estimation for Bistatic MIMO Radar Systems

This article presents MATLAB simulation code for joint DOA and DOD estimation in bistatic MIMO radar systems. The implementation includes signal processing algorithms for target localization using multiple-input multiple-output radar configurations. Key functions in the code handle signal transmission/reception modeling, covariance matrix computation, and subspace-based estimation techniques like MUSIC or ESPRIT algorithms. For comprehensive understanding of the system architecture and underlying algorithms, please refer to the following two foundational papers: 1. "Multi-Target Identification and Localization Using Bistatic MIMO Radar Systems" by Haidong Yan, Jun Li, and Guisheng Liao, published in EURASIP Journal on Advances in Signal Processing, January 2008. This paper has been cited 106 times, demonstrating its significant contribution to the field. The MATLAB implementation incorporates concepts from this work including transmit/receive array configurations and signal model formulations. 2. "Joint DOD and DOA Estimation for Bistatic MIMO Radar" by Ming Jin, Guisheng Liao, and Jun Li, published in Signal Processing, February 2009. This paper discusses advanced methods for simultaneous DOD and DOA estimation, providing the algorithmic basis for the angle estimation routines in our simulation code. The MATLAB code implements critical signal processing chains including: - Transmit signal waveform generation and modulation - Receive signal processing with array calibration - Covariance matrix estimation and eigen decomposition - Joint angle estimation using 2D spectral search algorithms By studying these references, you can gain deeper insights into the principles and methodologies of joint DOA and DOD estimation in bistatic MIMO radar systems. We hope this information and accompanying code prove valuable for your research and development work.