Multi-frame detection has been widely researched in the scenario where the target signal-to-noise is low.However, it becomes a challenging problem under heterogeneous clutter environment. As strong clutter energy is accumulated along with the target in multiple frames, low SNR targets are still annihilated in clutter. To achieve effective clutter suppression and dim targets detection, a novel multi-frame procedure for energy accumulation under heterogeneous clutter is proposed in this paper. The presented architecture concerns a Space-Time Adaptive Processing (STAP) processor and a multi-frame detector. The STAP processor calculates the clutter covariance matrix using multi-frame training samples near the cell under test and extracts data contaminated by the target component. The multi-frame detector is developed to detect dim targets and output estimated target track sequences. Finally, simulation results are given to demonstrate the efficacy of the proposed algorithm.