Research on Anti-Range Migration Sparse Reconstruction Algorithm in Target Parameter Estimation of Frequency-Agile Radar

The frequency agile radar (FAR) target parameter estimation scenario based on sparse reconstruction faces the problem of high-resolution range migration (HRRM), which corresponds to phase interference that matches the target atoms in the dictionary matrix and forms a pseudopeak structure. In this article, we propose an anti-range migration sparse reconstruction (ARMSR) algorithm for recovering the range-Doppler parameters of high-velocity targets. The main feature of this algorithm is its hybrid processing structure, which introduces 1-D high-resolution IFFT processing into the sparse recovery model. Based on the range imaging gain compensated by different Doppler phases, the velocity index set is preliminarily determined, and then the compensation function for the range migration phase is calculated. Using the measurement vector compensated by the migration component as input, a subdictionary matrix was constructed at super-resolution intervals in the neighborhood of the range profile and velocity index set. The proposed algorithm effectively overcomes the influence of range migration components and reduces pseudo peaks in conventional sparse reconstruction planes. In addition, the proposed algorithm performs parameter estimation in a high-resolution neighborhood space, resulting in improved computational efficiency and resolution of target parameters. The simulation results demonstrate that the proposed algorithm has significant reconstruction advantages in scenarios with high-velocity targets and super-resolution.