Filter Design And Implementation Of The Algorithm Based On Particle Swarm Optimization

Many scientific, engineering and economic problems involve the optimization of a set of parameters. Nowadays, numerous optimization algorithms, such as Genetic Algorithm (GA) and Simulated Annealing (SA), have been proposed to solve these problems, with varying degree of success. The Particle Swarm Optimization (PSO) is a relatively new technique that has been empirically shown to perform well on many engineering problems.Some modified PSO have been proposed such as Particle Swarm Optimization with Simulated Annealing Strategy (SAPSO). In this thesis, optimal design of FIR filter is completed based on discussing and analysing of SAPSO. Simulation results show the correction and validity of this algorithm.Focused on the actual demand of FIR filter in intermediate frequency (IF) sampling digital receiver of a digital beamforming array radar, design of FIR filter with SAPSO is studied and realized. Experimental measurement shows that FIR filter designed with SAPSO can obtain more restraining stop-band and more narrow transition-band compared with filter based on window function method.