Adding Optical Flow into the GPS/INS Integration for UAV navigation

Autonomously operating unmanned aerial vehicles (UAV) have a great potential for many applications such as reconnaissance, mapping and surveillance. Whilst needing low cost and light weight navigation systems in their implementations, sensors like GPS or low cost inertial sensors can’t separately provide either the complete set of information or the required degree of accuracy. Multi-sensor solutions have to be sought to mitigate the shortcomings of individual sensors. Often in such systems, low cost MEMS INS is aided by GPS to provided position, velocity and attitude (PVA) measurements. Data fusion strategies and techniques like extended Kalman filter (EKF) are the kernel for estimating and compensating individual sensor errors to reach improved performance. One drawback of integrating GPS with low cost MEMS INS is the heavy reliance on GPS signal availability. The accuracy of PVA solutions would degrade sharply during GPS signal drop outs due to the poor performance of low cost MEMS INS, which would limit the UAV applications under heavy canopy or city canyon