Title: Performance Trade-Offs in Distributed Detection Networks

Speaker: Nagi Rao, Oak Ridge National Laboratory

Date/Time: Tuesday, October 5, 2010, 10:00 am Mountain - 9:00 am Pacific time       

Location: CSRI Building/Room 90 (Sandia NM) and 905/210 in SNL/CA

Brief Abstract: We consider a network of sensors that measure the scalar intensity due to the background or a source combined with background, inside a two-dimensional monitoring area. The sensor measurements may be random due to the underlying nature of the source and background or due to sensor errors or both. The detection problem is to infer the presence of a source of unknown intensity and location based on sensor measurements. In the conventional approach, detection decisions are made at the individual sensors, and then combined at the fusion center, for example using the majority or Bayesian rule. With increased communication and computation costs, we show that a more complex fusion algorithm based on localization using measurements achieves better detection performance under smooth and non-smooth source intensity functions, Lipschitz conditions on probability ratios and a minimum packing number for the state-space. We show that these conditions for trade-offs between the cyber costs and physical detection performance are applicable for the detection of point radiation sources amidst background radiation.

This work is funded in part by Mathematics of Complex, Distributed Interconnected Systems Program, Office of Advanced Scientific Computing Research, U.S. Department of Energy.

CSRI POC: Jean-Paul Watson, 505-845-8887