Space Extended Target Tracking Using Poisson Multi-Bernoulli Mixture Filtering with Nonlinear Measurements

The number of space targets in the near-Earth orbit has greatly increased, and space-based radar has the advantage of high resolution and high accuracy tracking to enhance the tracking efficiency of space extended targets (SET). We propose a gamma Gaussian inverse Wishart based on a matched linearization-Poisson multi-Bernoulli mixture (GGIWML-PMBM) filter to estimate the motion state and shape size of the SET. For the random matrix that can only describe the distribution under which the measurements are linear, the measurements of the spatial target are linearized using matched linearization, and the extended information is preserved in the second-order central moments. The transfer density and likelihood function of GGIW are nonlinear for Poisson measurements with nonlinear Gaussian spatial distributions, and the single-target densities and normalizing constants of the PMBM filter are not closed form. The prediction and update of PMBM include Gaussian-weighted integral calculation, for which different nonlinear approximation methods are used to calculate the weighted integral and derive the closed form of GGIWML-PMBM. Finally, the simulation scenarios of low-orbit single-radar sensor tracking near SET and group SET are established, and the results show that the tracking accuracy can reach 2.6 m for near SET and 6.6 m in group SET.