Compressed Sensing MIMO Radar Parameter Estimation

Compressed Sensing MIMO radar parameter estimation represents a fascinating and critically important research domain. In this field, we primarily investigate monostatic MIMO radar scenarios where parameter estimation techniques enable deeper understanding and mastery of radar system performance characteristics. Practical implementations require accurate parameter estimation algorithms for optimizing radar system performance and enhancing target detection capabilities. The implementation typically involves sparse signal recovery algorithms using optimization techniques like L1-norm minimization, where MATLAB's optimization toolbox or custom CVX routines can be employed. Key functions often include dictionary matrix construction for sparse representation and orthogonal matching pursuit (OMP) algorithms for parameter extraction. Therefore, comprehensive research and exploration are essential to develop more efficient and precise parameter estimation algorithms. Through these efforts, we can significantly advance radar technology development, enabling broader applications and innovations across various domains.