The interpretation of raw signals in capillary CE can be challenging if there are unknown peaks, or the signal is corrupt due to baseline fluctuations, EOF velocity drift, etc. Signal processing could be required before results can be interpreted. A suite of signal processing algorithms has been developed for CE data analysis, specifically for use in field experiments for the detection of nerve agents using portable CE instruments. Everything from baseline correction and electropherogram alignment to peak matching and identification is included in these programs. Baseline correction is achieved by interpolating a new baseline according to points found using all local extremes, by applying an appropriate outliers test. Irreproducible migration times are corrected by compensating for EOF drift, measured with the aid of thermal marks. Thermal marks are small disturbances in the capillary created by punctual heating that move with the velocity of EOF. Peaks in the sample electropherogram are identified using a fuzzy matching algorithm, by comparing peaks from the sample electropherogram to peaks from a reference electropherogram.