研究了分布式不确定性系统的状态估计。以两部雷达构成的分布式系统为对象，考虑杂波环境、量测噪声和目标不确定性机动下的多目标跟踪。针对其中的两类不确定性问题，提出了机动目标自回归统计模型，并将它与联合概率数据关联相结合，给出了一种新的分布式多目标跟踪算法。仿真结果证明了其快速性和自适应性。 The state estimation of distributed uncertain systems is studied. Taking the distributed system composed of two radars as the object, we consider the clutter environment, the measurement noise and the multi-target tracking under the maneuver of the target uncertainty. Aiming at the two types of uncertainties, this paper proposes a maneuvering target autoregressive statistical model, and combines it with the joint probabilistic data association to give a new distributed multi-target tracking algorithm. Simulation results prove its fastness and adaptability.