Multi-Target Parameter Estimation of the FMCW-MIMO Radar Based on the Pseudo-Noise Resampling Method.

Area of Science:

• Radar Systems Engineering
• Signal Processing
• Electromagnetics

Background:

• Subspace methods are crucial for target parameter estimation in FMCW-MIMO radars.
• Existing algorithms suffer performance degradation in non-ideal conditions like low signal-to-noise ratio (SNR) and limited snapshots, leading to inaccurate covariance matrix estimation and subspace leakage.

Purpose of the Study:

• To propose a joint Direction of Arrival (DOA)-range estimation algorithm for FMCW-MIMO radars.
• To address the performance degradation issues in low SNR and limited snapshot scenarios.
• To improve the accuracy of target parameter estimation.

Main Methods:

• Utilizing an improved unitary root-MUSIC algorithm to mitigate non-ideal terms in covariance matrix construction.
• Employing the least squares method for paired range estimation.
• Implementing threshold detection to identify and manage outlier estimators.
• Applying pseudo-noise resampling (PR) technology to create a new data observation matrix for error alleviation.

Main Results:

• The proposed algorithm effectively reduces the influence of non-ideal terms on covariance matrix estimation.
• It successfully overcomes performance degradation in scenarios with limited snapshots and low SNR.
• Outlier detection and PR technology further enhance the accuracy and robustness of DOA-range estimation.

Conclusions:

• The developed joint DOA-range estimation algorithm demonstrates superior performance compared to existing methods.
• It provides a robust solution for accurate target parameter estimation in challenging, non-ideal radar environments.
• Theoretical analysis and simulations validate the algorithm's effectiveness and advantages.