  A simple and low cost dynamic weight importance sampling (DWIS)
implementation is presented and discussed for spatiotemporal sensing of unknown
correlated signals in sensor field. The spatial signal is compressed into its
contour lines and a partitioned subset of sensors that their observations are
in a given margin of the contour levels, is used for importance sampling. The
selected sensor population is changed dynamically to maintain the low cost and
acceptable spatial signal estimation from limited observations. The estimation
performance, cost and convergence of the proposed approach is evaluated for
spatial and temporal monitoring, using three different contour level definition
schemes. The results show that using DWIS and modeling the spatial signal with
contour lines is low cost. In this study the presence of noise in sensor
observations is ignored. The number of participant sensors is taken as modeling
cost.
