Background The inversion calculation using monitoring information is a key step in source term inversion work, and selecting an appropriate inversion algorithm is the core issue of the inversion process. Purpose This study constructs a three-dimensional radiation field model using Micro Shield software to generate simulated observation data, and implements a comparative analysis of inversion algorithms through coding. Methods: By employing the control variable method, the inversion performance of the least squares method, regularized least squares method, and Bayesian inference method is compared under the same simulated data conditions. Conclusions The results indicate that the least squares method is fast in computation under low noise conditions but is sensitive to noise; the regularized least squares method improves stability by introducing a regularization term, making it suitable for scenarios with higher noise levels; and Bayesian inference, which combines prior knowledge with observation data, can maintain high accuracy even in the presence of complex noise.