Sparse Decomposition of Radar Signals Using Matching Pursuit
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The method presented in this paper employs matching pursuit for sparse decomposition of radar signals, thereby obtaining their sparse representations. This approach effectively decomposes radar signals into a set of sparse basis elements using the matching pursuit algorithm, enabling better understanding of signal characteristics and structures. The algorithm operates by iteratively selecting the basis function that best matches the signal residual at each step, progressively building the sparse representation through greedy optimization. This decomposition technique finds extensive applications in radar signal processing, including target detection, target tracking, and signal recovery. Therefore, using matching pursuit for sparse decomposition represents an effective and commonly employed processing method that can be implemented through iterative correlation calculations and residual updates in practical code implementations.
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