To reconstruct the target shape distribution in the distance, full waveform analysis algorithm is utilized by extracting and analyzing the number of the peaks, the time of the peak maximum and other parameters. A novel fast full waveform analysis algorithm (simulated tempering Markov chain Monte Carlo algorithm, STMCMC) is proposed, which is able to process the waveform data automatically. For the different types of the parameters, simulated tempering strategy and the Metropolis strategy are presented. In simulated tempering strategy, due to the demand of speed or accuracy, active intervention tempering is used to control the process of solving the vector parameters. On the other hand, the Metropolis strategy is adopted for non-vector parameters to reduce computation amount. Both the strategies are based on Markov chain algorithm, and meanwhile can hold the convergence of the Markov chain, which makes the STMCMC algorithm robust.