由于单站被动式跟踪稳定性差、动态过程时间长、估计偏差大，且对初值敏感，使得直接在各单站估计基础上做融合效果仍然很差，本文提出多“双站”新概念，推导完成了基于多“双站”的自适应融合算法，提高了系统跟踪精度，保证了算法的快速收敛以及算法的初值不敏感性，仿真结果证明了其正确性。 Due to the poor stability of single-station passive tracking, the long dynamic process, large estimated deviations, and sensitive to the initial values, the integration effect on the basis of single-station estimation is still poor. In this paper, a new concept of “double stations” is proposed and deduced The adaptive fusion algorithm based on multiple “double stations” is completed, the tracking accuracy of the system is improved, the fast convergence of the algorithm and the initial value insensitivity of the algorithm are guaranteed, and the simulation results prove its correctness.