Attractor dynamics to fuse strongly perturbed sensor data

Presents a new approach to multi-sensor fusion which is based on coupled nonlinear attractor dynamics. The state of the dynamics represents the fused estimate of a physical entity measured by multiple sensors. Each sensor-reading but also general expert knowledge about the measured system specifies a local stable fixed point (attractor) with a limited basin of attraction of the dynamics. The dynamic state variable converges to a global stable state which is the system's fused estimate. For the example of measuring the oil film thickness on seawater by means of multispectral radiometer measurements gathered during flights across a polluted area, the authors show that their approach is particularly useful for fusing multimodal strongly perturbed sensor data.