Observing Movments Of Target Using Edge Detecting Algorithm In WSN
As the wireless sensor network are used to bring the interaction in humans, their surrounding and machines to a
new level. Wireless sensor network initially used for military purpose ground surveillance, but usefulness of wireless sensor
network have gain attention in industries, observing a target in the field, health care applications. Observing the movement
of the target is one of the key applications, i.e. target tracking we can gather information the sensor node. The sensor node
iteratively estimate the resent target location or state by using information collected when target is in range of sensor node.
So for this purpose, there are target motion model and measurement model are created. Then by using energy measurement
model, average signal energy of the received signal is calculated in which there are two terms received signal strength from
the target and noise energy are mentioned. From this collected information at sensor node target locations are estimated and
predicted with the help of Extended Kalman Filter. As our aim is to estimate velocity and position of an object emitting
energy, sensor selection strategies that minimize the error in estimate are computationally more efficient. The extended
Kalman Filter minimizes the estimation error. In practices, the main difference between Kalman Filter and Extended Kalman
Filter is that the value in Jacobean matrix must be calculated at iteration.
Keywords - Wireless Sensor Network, Sensor Selection.