FPGA Based Kalman Filter for Wireless Sensor Networks

A Wireless Sensor Network (WSN) is a set of tiny and low-cost devices equipped with different kind of sensors, a small microcontroller and a radio transceiver, typically powered by batteries. Target tracking is one of the very important applications of such a network system. Traditionally, KF (Kalman filtering) and its derivatives are used for tracking of a random signal. Kalman filter is a linear optimal filtering approach, to address the problem when system dynamics become nonlinear, researchers developed sub-optimal extensions of Kalman filter, two popular versions are EKF (extended Kalman filter) and UKF (unscented Kalman filter).The rapidly increasing popularity of WSNs has placed increased computational demands upon these systemswhich can be met by FPGA based design. FPGAs offer increased performance compared to microprocessors and increased flexibility compared to ASICs , while maintaining low power consumption