Continuous and stable tracking of the ground maneuvering target is a challenging problem due to the complex terrain and high clutter. A collaborative tracking method of the multisensor network is presented for the ground maneuvering target in the presence of the detection blind zone (DBZ). First, the sensor scheduling process is modeled within the partially observable Markov decision process (POMDP) framework. To evaluate the target tracking accuracy of the sensor, the Fisher information is applied to constructing the reward function. The key of the proposed scheduling method is forecasting and early decision-making. Thus, an approximate method based on unscented sampling is presented to estimate the target state and the multi-step scheduling reward over the prediction time horizon. Moreover, the problem is converted into a nonlinear optimization problem, and a fast search algorithm is given to solve the sensor scheduling scheme quickly. Simulation results demonstrate the proposed non-myopic scheduling method (Non-MSM) has a better target tracking accuracy compared with traditional methods.

中文翻译：

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存在检测盲区的地面机动目标跟踪传感器调度

由于地形复杂、杂波高，对地面机动目标的连续稳定跟踪是一个具有挑战性的问题。针对存在检测盲区（DBZ）的地面机动目标，提出了一种多传感器网络协同跟踪方法。首先，传感器调度过程在部分可观察马尔可夫决策过程 (POMDP) 框架内建模。为了评估传感器的目标跟踪精度，Fisher 信息被应用于构建奖励函数。所提出的调度方法的关键是预测和早期决策。因此，提出了一种基于无味采样的近似方法来估计目标状态和预测时间范围内的多步调度奖励。而且，将问题转化为非线性优化问题，给出快速搜索算法，快速求解传感器调度方案。仿真结果表明，与传统方法相比，所提出的非近视调度方法（Non-MSM）具有更好的目标跟踪精度。