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We present a Bayesian parameter estimation progress to infer the stellar massbinary black hole properties by TianQin, LISA, and TianQin+LISA.Two typicalstellar mass black hole binary systems, GW150914 and GW190521 are chosen as thefiducial sources. In this work, we establish the ability of TianQin to inferthe parameters of those systems and first apply the full frequency response inTianQin's data analysis. We obtain the parameter estimation results and explainthe correlation between them. We also find the TianQin+LISA could marginallyincrease the parameter estimation precision and narrow the $1\sigma$ areacompared with TianQin and LISA individual observations. We finally demonstratethe importance of considering the effect of spin when the binaries have anonzero component spin and great deviation will appear especially on mass,coalescence time and sky location.

Parameter Estimation of Stellar Mass Binary Black Holes under the Network of TianQin and LISA