State Estimation under Communication Uncertainties

Mon, 01 Jan 0001 00:00:00 +0000

Problem

Air traffic surveillance, like many tracking systems, relies on measurements sent over imperfect communication links. Packets get dropped, sometimes at random and sometimes in predictable places, such as regions with poor coverage or radio jamming. A standard Kalman filter assumes every measurement arrives, so its estimates degrade exactly where losses cluster. When many sensors track the same aircraft, each sees only part of the picture and has to agree with its neighbours over a network whose connections keep changing.

Sensor-Networks on Omanshu Thapliyal

State Estimation under Communication Uncertainties

Problem