For the problem of passive location under low detection probability, a multi-sensor fusion tracking algorithm based on sliding window batch technique is presented. Multiple low detection probability passive sensors are networked to spatially accumulate the target information and improve the detection probability. The nonlinear measurement is transformed to pseudo linear measurement by using pseudo linear estimation，and then the local optimal estimation of target state is achieved by a least squares sliding window batch algorithm. Simulations verify the validity of algorithm and analyze the effect of parameter. Results show that, the proposed method greatly improves the detection probability of the sensor network with acceptable tracking precision and real time requirement.