1 research outputs found
Sensor Fusion for Magneto-Inductive Navigation
Magneto-inductive navigation is an inexpensive and easily deployable solution
to many of today's navigation problems. By utilizing very low frequency
magnetic fields, magneto-inductive technology circumvents the problems with
attenuation and multipath that often plague competing modalities. Using
triaxial transmitter and receiver coils, it is possible to compute position and
orientation estimates in three dimensions. However, in many situations,
additional information is available that constrains the set of possible
solutions. For example, the receiver may be known to be coplanar with the
transmitter, or orientation information may be available from inertial sensors.
We employ a maximum a posteriori estimator to fuse magneto-inductive signals
with such complementary information. Further, we derive the Cramer-Rao bound
for the position estimates and investigate the problem of detecting distortions
caused by ferrous material. The performance of the estimator is compared to the
Cramer-Rao bound and a state-of-the-art estimator using both simulations and
real-world data. By fusing magneto-inductive signals with accelerometer
measurements, the median position error is reduced almost by a factor of two