Study on the filtering algorithm of photon correlation spectroscopy based on singular value decomposition

During the measurement of the ultrafine nanoparticles's size with the method of PCS (Photon Correlation Spectroscopy), the fitting results are always susceptible to the noise and have quite large errors. To solve the problem, the filtering algorithm of photon correlation spectroscopy based on singular value decomposition is proposed. Its procedure is: the Hankel matrix H with the intensity autocorrelation data is constructed; the singular value decomposition of H is calculated; the reconstruction parameters r with the singular value of H are determined; the filtered light intensity autocorrelation data from the reconstruction matrix H₁ are extracted, and fitting with the traditional method, and then the particle size distribution is obtained. The experiment is carried out in two different particle dispersions, one is 30nm standard monodisperse latex particle dispersion, and another is 30nm and 100nm standard double dispersion latex particle dispersion. The results show that, the filtering algorithm of photon correlation spectroscopy based on singular value decomposition can improve the measurement accuracy effectively.