Optimal Scheduling and Filtering of Distorted Multi-Sensor Data
Sugathevan Suranthiran, Suhada Jayasuriya · Dynamic Systems and Control · 2002
In this paper, a framework to schedule and filter distorted multi-sensor outputs is developed. The distortion caused by sensor nonlinearity is considered. As the distorted signal is not a true representation of the original signal, it is often necessary to develop and incorporate signal recovery schemes. Once such a scheme is developed, implementation may be straightforward if the system is employed with a single sensor. When the bandwidth of a signal of interest is very high, the use of a single sensor may not be feasible. High cost and accuracy are major concerns worth noting. It is proposed that a good practical solution to this problem is to employ an array of low bandwidth sensors. Practical Implementation of recovery schemes is very challenging and difficult in this case due to a possible overlapping of multi-source data. This sensor scheduling problem is investigated in detail and a data fusion scheme based on the optimization of weighted error function is initiated and developed for the two-sensor case. Simulation results are presented to validate the fusion procedure developed.