We developed a signal processing algorithm to analyze the signals obtained by an OMA system for laser-produced plasmas. This signal processing program is applied for multi-component analysis of trace elements in particulate materials (e.g. soils and industrial wastes) and is designed to overcome signal fluctuations due to instability of the plasma characteristics and due to some of the matrix effects. The program involves a constrained normalization algorithm, an automatic peak assignment, a functional fit of all peaks of interest and their surroundings, and a principal components regression calibration model. These algorithms, together with experimental optimizations, are shown to solve most of the problems present in laser plasma analysis of particulate material and to produce detection limits in the ppm range.