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In this paper we demonstrate a methodology to remove the power of the driftinduced from random acceleration on LISA proof mass in the frequency domain.The drift must be cleaned from LISA time series data in advance of any furtheranalysis. The cleaning is usually performed in the time domain by using aquadratic function to fit the time series data, and then removing the fittedpart from the data. Having Fourier transformed the residuals, and thenconvolved with LISA transfer function, LISA sensitivity curve can be obtained.However, cosmic gravitational-wave background cannot be retrieved with thisapproach due to its random nature. Here we provide a new representation ofpower spectrum given by discrete Fourier transform, which is applied to findthe function of the drift power for the cleaning in the frequency domain. Wealso give the probability distribution used to analyze the data in thefrequency domain. We combine several techniques, including Markov Chain MonteCarlo method, simulated annealing, and Gelman & Rubin's method, with Baye'stheorem to build the algorithm. The algorithm is utilized to analyze 24simulations of LISA instrumental noise. We prove that the LISA sensitivity canbe recovered through this approach. It can help us to build algorithms for sometasks which are must accomplished in the frequency domain for LISA dataanalysis. This method can be applied to other space-borne interferometers ifcharges on their proof masses cannot be perfectly cancelled.

Removing the trend of drift induced from acceleration noise for LISA