Distributed state estimation (DSE) and bad data (BD) processing have become increasingly important for the analysis and operation of large-scale power networks. This paper develops a new strategy for decentralized phasor-aided state estimation (DPHASE) to improve the performance of BD processing and, hence, the accuracy of DSE results. Given the recent availability of PMUs, the DPHASE strategy is developed using a parallel multi-stage hybrid approach. The practical challenges in the approach are identified and attributed to the difference between the sets of buses for SCADA- and PMU-based state estimates in sub-areas. Phasor-aided normalized residuals are locally unobtainable and the fusion of local state estimates is unattainable. These challenges are effectively resolved by extending local state vectors. Comparative case studies are performed using the proposed and conventional DSE strategies. The study results confirm that the proposed DPHASE strategy improves the accuracy and robustness of the DSE results under various test network and data measurement conditions.