title: Mine detection using scattering parameters.
abstract: The detection and disposal of antipersonnel land mines is one of the most difficult and intractable problems faced in ground conflict. This paper presents detection methods which use a separated-aperture microwave sensor and an artificial neural network pattern classifier. Several data-specific preprocessing methods are developed to enhance neural network learning. In addition, a generalized Karhunen-Loeve transform and the eigenspace separation transform are used to perform data reduction and reduce network complexity. Highly favorable results have been obtained using the above methods in conjunction with a feedforward neural network.
authors.affiliation: Dept. of Electr. Eng., Stanford Univ., CA.
authors.forename: G L
authors.initials: GL
authors.lastname: Plett
authors.forename: T
authors.initials: T
authors.lastname: Doi
authors.forename: D
authors.initials: D
authors.lastname: Torrieri