针对传感器网络中的动态跟踪问题,提出一种基于Renyi信息增量的机动目标协同跟踪方法,首先利用粒子滤波计算每个传感器Renyi信息增量;然后以Renyi信息增量最大为原则选择传感器进行目标跟踪,并在跟踪时通过多模型的交互作用实现对机动目标状态的准确估计,仿真结果表明,在非线性非高斯环境下,所提出的方法与传统方法相比能够有效提高跟踪精度,动态分配传感器资源,实现协同跟踪。 Aiming at the problem of dynamic tracking in sensor networks, a collaborative tracking method based on Renyi information increment is proposed. Firstly, the particle information is used to calculate the Renyi information increment of each sensor. Then, the sensor is selected based on the principle of Renyi information increment Tracking and accurate estimation of the state of maneuvering target through the interaction of multiple models during the tracking. The simulation results show that the proposed method can effectively improve the tracking accuracy and the dynamic allocation in the non-linear non-Gaussian environment compared with the traditional method Sensor resources, to achieve collaborative tracking.