A unique and powerful paradigm or methodology for the design of nonlinear dynamical systems and signal processing algorithms is reported. Some aspects of this approach are discussed, and the results of the application of this approach in signal estimation are given. The results are compared with that of Kalman filtering, which is essentially filtering using a filter with a time-varying coefficient (Kalman gain). The results indicate that the new nonlinear signal processing (NLSP) approach is superior and more robust as compared to Kalman filtering. >