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A high-performance standalone planar field asymmetric waveform ion mobility spectrometry (p-FAIMS) system with a deconvolution algorithm (two-step particle swarm optimization algorithm, TSPSO) for overlapping peaks was developed to effectively detect chemical warfare agents (CWAs). Four CWA simulants were applied in this study to systemically evaluate the performance of the standalone p-FAIMS system. The experimental results showed that each CWA simulant in the mixture can be positively identified by carefully comparing the compensation voltage (CV) value of each peak in the FAIMS spectra for the mixture to the ones in the spectra acquired by using the same FAIMS system for the pure CWA simulant standards. The FAIMS spectrum of the CWA simulant mixture might consist of multiple overlapping peaks, which would be difficult to accurately determine the CV value for each CWA simulant peak. This problem has been effectively resolved in this study by deconvoluting the overlapping peaks via the TSPSO algorithm. As the effective peak deconvolution via TSPSO requires the degree of overlap between each FAIMS peak to be lower than a specific value, the flow rate of FAIMS carrier gas was decreased to further improve the resolution of the p-FAIMS system. After the accurate deconvolution, the resolution of original FAIMS spectrum can also be enhanced to achieve baseline separation by using TSPSO algorithm to narrow the peak width of each peak. The experimental results in this study demonstrated the possibility of using TSPSO algorithm to achieve high-resolution on a typically low-resolution standalone FAIMS. The concept in this study can potentially be applied to any low-resolution instruments to achieve high-resolution results. [Display omitted] • A high-performance standalone FAIMS system was developed in this study. • The chemical warfare agent mixtures were effectively analyzed by using FAIMS. • The overlaid peaks in FAIMS spectra can be effectively deconvoluted via TSPSO algorithm. • The FAIMS spectra can be enhanced to achieve baseline separation using TSPSO algorithm. [ABSTRACT FROM AUTHOR]