The increasing demand for a better quality of service in radar and wireless communication has attracted research on interference suppression. Nonlinear filtering methods based on spline architecture have been widely utilized in signal processing due to their effectiveness against alpha-stable interference. How- ever, existing nonlinear spline adaptive filter algorithms suffer from high steady-state misalignment. To achieve lower steady- state misalignment along with having comparable computational complexity, we propose a nonlinear spline Versoria prioritiza- tion optimization adaptive filter (SPOAF-MVC) for alpha-stable clutter in this paper. Further, we study the bound on learning rate and computational complexity for the proposed algorithm. Numerical simulations confirm the effectiveness and efficiency of the proposed SPOAF-MVC algorithm for alpha-stable clutter under Wiener system identification.

A filtering algorithm based on frequency domain spline type, frequency domain spline adaptive filters (FDSAF), effectively reducing the computational complexity of the filter. However, the FDSAF algorithm is unable to suppress non-Gaussian impulsive noises. To suppression non-Gaussian impulsive noises along with having comparable operation time, a maximum correntropy criterion (MCC) based frequency domain spline adaptive filter called frequency domain maximum correntropy criterion spline adaptive filter (FDSAF-MCC) is developed in this paper. Further, the bound on learning rate for convergence of the proposed algorithm is also studied. And through experimental simulations verify the effectiveness of the proposed algorithm in suppressing non-Gaussian impulsive noises. Compared with the existing frequency domain spline adaptive filter, the proposed algorithm has better performance.

A new flight control law for unmanned aerial vehicles based on robust servo linear quadratic regulator control and Kalman filtering is proposed. This flight control law has a simple structure with high dependability in engineering. The pitch angle controller, which is designed based on the robust servo linear quadratic regulator control, is given to show the flight control law. Simulation results show that the pitch angle controller works well under noise-free conditions. Finally, Kalman filtering is applied to the pitch angle controller under noisy conditions, and the simulation results show that the proposed method reduces the influence of noise.