Parallel filtering is a solution for dealing with errors in a UAV. In this approach, integration of aiding sensor measurements in the navigation solution is delayed until a period equal to the fault detection time has elapsed. If no faults are detected during this period, then the delayed measurements are extrapolated forward in time and integrated into the navigation solution. Alternately, we can rewind the dead-reckoning solution backwards in time, integrate the delayed measurements and fast-forward the integrated solution up to the current time epoch. When these filters detected a fault, they immediately inflated the faulted sensor's output noise covariance matrix. As such, it has some drawbacks when compared to traditional approaches. First, the computational overhead associated with this approach can be high especially if a large number of parallel Filters are used. Thus, methods for streamlining the computations so that they are not computer-resource intensive will be important. The second issue that needs further exploration is the way in which blending weights are computed.
|Original language||English (US)|
|Number of pages||8|
|Specialist publication||GPS World|
|State||Published - May 2015|