Distributed target tracking under communication constraints

In distributed tracking, communication bandwidth is one of the most expensive resources when we require to send measurements to other locations for processing. Furthermore, bandwidth requirement increases when tracking in clutter is considered due to transmission of target as well as clutter measurements. This paper describes the tracking in clutter under bandwidth constraints. The main idea is that instead of sending all target and clutter measurements we combine them into a weighted sum and transmit the resultant measurement. A novel Bayesian filter is proposed utilising the received measurement information. We observe some loss of performance as compared to local tracker, however it is considerably small.