A low-power filtering scheme for distributed sensor networks

Because the energy required for communications tasks is much greater than that required for computational tasks, estimation algorithms designed for distributed networks of sensors must attempt to reduce the communications overhead that they require. We suggest a simple mechanism for implementing Luenberger observers that allows estimates to be constructed from transmissions generated at a slower rate than the measurements are collected, while maintaining a robustness to communications outages, interruptions and delays.