  For reliable operation, next generation autonomous agents will need enhanced
situational perception as well as precise navigation capabilities. The global
navigation satellite system (GNSS) signals that are utilized by practically all
modern positioning systems cannot satisfy this requirement for heighten
autonomy levels and positioning is becoming a decisive factor for their
proliferation.
  This work investigates how relative positioning can be achieved using signals
that are already accessible in the environment, and derives an online procedure
for the exploitation of these signals for localization in GNSS-challenged
areas. The proposed relative positioning system (RPS) explores the signal
properties over a large spectrum of frequency bands, and derives a vehicle
tracking algorithm to accurately estimate the vehicle's trajectory in space and
time using an arbitrary set of unknown reference positions. Experimental
results demonstrate the applicability of RPS and investigate its performance
over the different parameter values.
