An improved particle swarm optimization algorithm is presented in this study. The new method proposes a linear time-varying acceleration co-efficient and brings in two mutations including differential mutation and random mutation. Also, some betterment is made over the bound constraints which keep the escaped particles diversity. At last, this new method is applied to seismic wavelet estimation. Numerical data tests demonstrate that the method is capable of extracting wavelets with relatively higher accuracy.