Landmine detection and localization using chemical sensor array processing

We develop methods for automatic detection and localization of landmines us ing chemical sensor arrays and statistical signal processing techniques. Th e transport of explosive vapors emanating from buried landmines is modeled as a diffusion process in a two-layered system consisting of ground and air . Measurement and statistical models are then obtained from the associated concentration distribution. We derive two detectors (the generalized likeli hood ratio (GLR) test and the mean detector) and determine their performanc e in terms of the probabilities of false alarm and detection. To determine the unknown location of a landmine, we derive a maximum likelihood (ML) est imation algorithm and evaluate its performance by computing the Cramer-Rao bound (CRB). The results are applied to the design of chemical sensor array s, satisfying criteria specified in terms of detection and estimation perfo rmance measures and for optimally selecting the number and positions of sen sors and the number of time samples, To illustrate the potential of the pro posed techniques in a realistic demining scenario, we derive a moving-senso r algorithm in which the stationary sensor array is replaced by a single mo ving sensor. Numerical examples are given to demonstrate the applicability of our results.