An Efficient Motion Parameters Estimation Method for Ground Maneuvering Targets in Wide-Swath MIMO-SAR

Accurately estimating the motion parameters of ground maneuvering targets in airborne wide-swath multiple-input multiple-output synthetic aperture radar (MIMO-SAR) is challenging under low pulse repetition frequency and strong clutter. Rather than resampling the periodic nonuniform sampling (PNS) sequence for parameter estimation, the proposed method confines spectrum reconstruction to clutter preprocessing and exploits the restored PNS structure to efficiently estimate radial acceleration and radial velocity. First, the azimuth degrees of freedom of the MIMO-SAR are leveraged to construct equivalent dual-channel data, and conjugate-symmetric difference operators suppress clutter, improving the signal-to-clutter-plus-noise ratio while preserving the PNS structure. Then, a parallel differential-phase model with a common slope and group-dependent intercepts is formulated, and a group-coherent generalized likelihood ratio test (GC-GLRT) estimator incorporating coherence-adaptive window selection is designed for robust estimation of radial acceleration. By treating radial velocity as a nuisance parameter through intra-group coherent integration and inter-group noncoherent combination, the original two-dimensional velocity–acceleration search is reduced to a one-dimensional acceleration search. Finally, after acceleration compensation, multi-delay differential-phase observations derived from the PNS structure are combined to form closure-phase observations, yielding an ambiguous radial velocity estimate. The velocity ambiguity is resolved using reference-delay observations together with a coherence-weighted decision rule, and the final estimate is refined through a weighted least-squares (WLS) fit to the residual phase. Simulation results show accuracy comparable to the generalized Radon-Fourier transform (GRFT) with substantially reduced computational complexity, demonstrating the effectiveness of the proposed algorithm.