Estimation and Control of Large-Scale Networked Systems

Chapter 5

State Estimation With Random Data Droppings

Abstract

Kalman filtering is of great importance in networked systems due to its various applications ranging from tracking and detection to control. Recently, much attention has been paid to the Kalman filtering with intermittent observations under various settings. A motivating example is given by sensor and estimator/controller communicating over a wireless channel for which the quality of the communication channel varies over time because of random fading and congestion. This happens in resource limited wireless sensor networks where communications between devices are power constrained and therefore limited in range and reliability. In this chapter, we discuss the Kalman filtering ...