Title :
Filtering of Randomly Sampled, Time-Stamped Measurements
Author_Institution :
Agilent Labs., Palo Alto, CA
Abstract :
This paper concerns the filtering of measurements that are taken by networked sensors at non-uniform intervals but that are accurately time-stamped. Traditional digital filtering methods are difficult or impossible to use due to the non-uniform sampling. Two filtering methods are described. Both are based on making an assumption about signal behavior between measurements, such as the signal being constant between measurements. In the first method, a filter is formulated as an ordinary differential equation that is solved incrementally as measurements arrive. In the second method, signal convolution with a continuous time, finite impulse response filter is performed efficiently using a spline representation for the filter response. Examples of the operation both sorts of filters are shown on actual measured data
Keywords :
FIR filters; array signal processing; continuous time filters; convolution; differential equations; distributed sensors; signal sampling; splines (mathematics); continuous time filters; data handling; differential equation; digital filters; filter response; finite impulse response filter; intelligent sensors; measurements filtering; networked sensors; nonuniform sampling; randomly sampled measurement; signal behavior; signal convolution; spline representation; time-stamped measurements; Battery charge measurement; Clocks; Digital filters; Finite impulse response filter; IP networks; Information filtering; Information filters; Power measurement; Pressure measurement; Protocols; continuous time filters; digital filters; intelligent sensors; measurement system data handling;
Conference_Titel :
Instrumentation and Measurement Technology Conference, 2006. IMTC 2006. Proceedings of the IEEE
Conference_Location :
Sorrento
Print_ISBN :
0-7803-9359-7
Electronic_ISBN :
1091-5281
DOI :
10.1109/IMTC.2006.328336