In this paper, we propose a method for designing finite impulse response (FIR) filters with canonic signed digit (CSD) coefficients using particle swarm optimization (PSO). In such a design problem, a large number of local minimums appear in an evaluation function for the optimization. An updating procedure of PSO tends to stagnate around such local minimums and thus indicates a premature convergence property. Therefore, a new framework for avoiding such a situation is proposed, in which the evaluation function is modified around the stagnation point. Several design examples are shown to present the effectiveness of the proposed method.