GNSS Spoofing, Jamming, and Multipath Interference Classification using a Maximum-Likelihood Multi-Tap Multipath Estimator

This paper experimentally evaluates the application of existing multipath mitigation technology in conjunction with in-band power monitoring for the purpose of GNSS interference classification. In particular, GNSS interference detection and classification metrics derived from the output of a multiple-correlation tap, maximum-likelihood multipath estimator are jointly used for the alarming the presence of GNSS spoofing, jamming or multipath. This approach is evaluated against the Texas Spoofing Text Battery (TEXBAT) archive (Humphreys et al., 2012), a dozen sets of deep urban multipath recordings, several recordings of wideband jammers at several different power levels, and clean static data recordings. Two detection approaches are proposed and one is shown to be better at discriminating between spoofing and jamming attacks.