Particle filter for range-only tracking in airborne radar

Particle filtering is a sequential Monte Carlo simulation based on nonlinear filtering algorithm. The method may cope with any nonlinear and non-Gaussian model without any limitations of linearization error and Gaussian noise assumption. In this paper, a range-only tracking in airborne inverse synthetic aperture radar model is constructed by using a method of chord length approximation, based on which, a particle filter algorithm is presented for real-time tracking to the relative range. Finally, based on a theoretical optimal error performance Cramer-Rao bound, the new algorithm and other filtering algorithms are compared in computational complexity and accuracy, the simulation results show that the former have higher accuracy.