The present invention discloses a Low-computation complexity Bernoulli filter for single-object tracking. The whole Bayes derivation process is simplified, and the target state transfer function and a target measurement likelihood function are optimized. The target measurement and the state independent clutter statistics characteristics are analyzed to derive an improved sequential Monte Carlo realization process so as to effectively extract the real goal in the clutter environment. The filter can effectively track the maneuvering single goal in the clutter environment and has low computation complexity and high tracking precision.