This paper examines the practicality of concurrent sensor data streaming with backscatter communication applied to modal analysis, which demands accurate data synchronization among streams. The major synchronization error source in concurrent backscatter streaming system is the instability of backscatter sensor clock. Synchronization of the streams by resampling at receiver is necessary but careless implementation may produce artificial delay caused by the difference of anti-Alias filters tailored to the individual clock rates of backscatter sensors. In this paper, a set of signal processing to synchronize concurrent backscatter signals is designed and implemented in a prototype system. The prototype system comprises backscatter sensors, interrogators and modal analyzer, which takes care of the generation of transfer matrix. The signal processing in the modal analyzer features a recursive least square regression to recover instantaneous sampling rate of backscatter sensor and a zero-phase-filtering in overlap-And-Add approach. The proposal is evaluated by comparing the transfer matrices generated from the prototype system and a commercial modal analysis system where wired accelerometers are used. The experimental results show that the proposed signal processing can successfully synchronize concurrent backscatter streams by eliminating the artificial delay.