Introduction - If you have any usage issues, please Google them yourself
We propose an approximation framework for distributed target
localization in sensor networks. We represent the unknown
target positions on a location grid as a sparse vector,
whose support encodes the multiple target locations.
The location vector is linearly related to multiple sensor
measurements through a sensing matrix, which can be locally
estimated at each sensor. We show that we can successfully
determine multiple target locations by using linear
dimensionality-reducing projections of sensor measurements.
The overall communication bandwidth requirement
per sensor is logarithmic in the number of grid points and
linear in the number of targets, ameliorating the communication
requirements. Simulations results demonstrate the performance
of the proposed framework.