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This work studies the multitarget passive location and tracking problem of multiple passive sensors. Since bearing only location of the multisensors will produce a lot of false intersection points in dense environments. In order to eliminate these false intersection points correctly and quickly, a two-level bearing measurement association algorithm is proposed In this work. This method firstly uses a rule to eliminate some false intersection points, so the computation burden is decreased. Then, the maximum likelihood algorithm is used to associate the bearing measurements, which can ensure the true association rate is high. Simulation is also made, and the results reveal the feasibility and validity of the bearing measurements association algorithm presented In this work, and multiple targets can be located and tracked at the same time by passive sensors.