The proposed indoor radar sensing system includes two enabling technology, activity recognitionrespiration rate estimation. In the former, the proposed framework consists of four major components: denosing, enhanced voxelization, data augmentation,dual-view machine-learning to lead to accurateefficient human-activity recognition. In the latter, the proposed system leverages the variation of the phase information of a specific frequency bin of the range profiles,proposes a dynamic adaptive respiration waveform filtering algorithm to improve accuracy.