Research Online: HF beacon navigation, inertial sensors and GNSS-INS integration

HF Beacon Navigation

Navigation using High-Frequency Ground Beacons and Ionosphere Model Corrections, by Yoav Baumgarten and Mark L. Psiaki, Cornell University.

A new navigation concept relies on passive one-way ranging using pseudorange measurements of high-frequency (HF) beacon signals reflected off the ionosphere.

This is being developed as a possible alternative to GNSS positioning and timing services, with benefits in costs and system redundancy. The HF signals are transmitted from ground-based beacons, traveling from known locations to the unknown user equipment (UE) location along ray paths that reflect off the Earth and the ionosphere. If a set of beacon signals reaches the UE receiver with sufficient geometric diversity, then the three-dimensional position and the clock offset of the receiver can be determined.

Presented at ION GNSS+ 2015.

Inertial Sensors

Dynamic Stochastic Modeling of Inertial Sensors for INS/GNSS Navigation, by M. Wis, Deimos Space, Spain; Ismael Colomina, GeoNumerics, Spain.

Researchers performed a series of experiments with a low-cost inertial device rigidly attached to a navigation-grade reference IMU and found a direct relationship between the low-cost IMU errors and the high-order dynamics. Preliminary results suggest an approach of low-cost sensor modeling that might help reduce some of the errors inherent to the dynamics applied to the sensors.

Presented at ION GNSS+ 2015.

GNSS-INS Integration

Quasi-Tightly-Coupled GNSS-INS Integration with a GNSS Kalman Filter, by Bruno Scherzinger, Applanix Corporation, Canada.

This method, intended for integration of an existing GNSS navigation engine into a GNSS-INS closed-loop configuration with little/no modification of the navigation engine, uses a range measurement model matrix typically used to compute dilutions of precision (DOP) to identify the observable subspace in the time-space frame generated by the available satellites and project the loosely coupled INS-GNSS Kalman filter position measurement into this subspace.

Presented at ION GNSS+ 2015.