Robust Constraint Extended Kalman Filter (RCEKF) for Parameter Estimation of Bicomponent Parallel Chirp Signals

This paper focuses on the parameter estimation of bicomponent parallel chirp signals with constant amplitude. A nonlinear state-space model is employed to represent the signal, and the Extended Kalman Filter (EKF) is utilized as a state observer to extract estimates from highly noisy measurements. To enhance the performance of previous approaches using EKF, we introduce constraints on the estimated components of the state vector. All simulations were conducted using MATLAB R2018a.