Three-dimensional imaging technique of space objects using multipass observations

Abstract: For a space object at stable flight state, its multipass echoes data is sparsely distributed along the elevation. Reconstruction three-dimensional target reflectivity function from these limited observations is ill-posed. Moreover, measurement noise will futhermore degrade the reconstruction, so the ordinary Fourier transform is no longer applied, and the object can’t generate the three-dimensional unless the prior information can be acquired in advance. Aiming at the target orbit motion characteristics, the elevation expression is firstly derived in this paper, and then a three-dimensional imaging technique of space targets using multipass echoes is proposed combined with sparse distribution of target scattering centers and compressed sensing theory. The method employs noisy cells to estimate noise level and when measured model meets the restricted isometry property ,the weighted compressed sensing iterative algorithm is used to produce the three-dimensional radar image of space object. Finally, combining with the real-time orbit data, the simulation results demonstrate that the compressed sensing based on noise estimation can achieve accurate three-dimensional image reconstruction in the low SNR.