Date of Award


Document Type


Degree Name

Master of Science in Electrical Engineering


Department of Electrical and Computer Engineering

First Advisor

Meir Pachter, PhD.


A method human operated INS aiding is explored in which the pilot identifies and tracks a ground feature of unknown position over a short measurement epoch using an E/O sensor. One then refers to Visual-INS. In contrast to current research trends, a human operator is entrusted with visually tracking the ground feature. In addition, a less conventional measurement linearization technique is applied to generate “converted” measurements. A linear regression algorithm is then applied to the converted measurements providing an estimate of the INS horizontal velocity error and accelerometer biases. At the completion of the measurement epoch, the INS is corrected by subtracting out the estimated errors. Aiding the INS in this manner provides a significant improvement in the accuracy of the INS-provided aircraft navigation state estimates when compared to those of a free/unaided INS. A number of scenario are simulated including with and without a constrained flight path, with single vs. multiple ground feature tracking sessions, and with a navigation vs. tactical grade INS. Applications for this autonomous navigation approach include navigation in GPS denied environments and/or when RF emitting/receiving sensors are undesirable.

AFIT Designator


DTIC Accession Number