An alternative SNR-based weighted-LSM algorithm to classify and measure the concentration of Biological Agents from Laser-Induced Fluorescence

Optical spectroscopic techniques, such as Laser-Induced Breakdown Spectroscopy (LIBS) or Laser-Induced Fluorescence (LIF), have already been used to study and detect Biological Agents (BAs). Unfortunately, BAs usually share similar-shaped emitted spectra and low-signal intensities, making their detection and classification difficult to assess. Least-Square Minimisation (LSM) based algorithms are usually deployed to measure the concentration of agents from spectra. Recently, it has been shown how the use of ad hoc weights can help in improving the performance of the concentration evaluation. More specifically, it has been observed that the “weight matrix” should be modelled as a function of the boundary conditions of the problem. This work proposes a new weight matrix that is based on the Signal-to-Noise Ratio (SNR) of the measurements. The idea is based on the fact that more noisy data are less reliable and therefore weight should be lowered. The paper, after a brief introduction and review of the LSM applied to spectra, will show the new methodology. A systematic analysis of the new algorithm is done and the comparison with the other LSM algorithms is presented. The results clearly show that there is a range of parameters for which the new algorithm performs better.