现代雷达大多会被安装在可旋转的平台上,其阵面指向可动态调节。但当前主流的目标分配算法通常假定雷达的阵面指向固定不变,忽略了其灵活调整的能力,从而在一定程度上限制了雷达组网在复杂战场环境中的整体作战效能。针对上述问题,一种联合目标分配与指向规划算法被提出。该算法首先通过扩展分配矩阵的维度,将原目标-传感器分配问题细化至阵面指向层面;其次,通过引入新约束条件,确保每部雷达在每个时刻仅选择一种阵面指向;最后,结合模型特性设计遗传算法,实现对该分配问题的高效求解。仿真实验证明:相较于传统假设阵面固定的目标分配方法,这一种联合目标分配与指向规划的新方法可得到更高的目标覆盖率与覆盖重数。

Most modern radars are installed on rotatable platforms, allowing their array orientations to be dynamically adjusted. However, current mainstream target assignment algorithms often assume that the radar array orientations are fixed, neglecting their flexible adjustment capabilities, thereby limiting the overall operational effectiveness of radar networks in complex battlefield environments. To address this issue, a joint target assignment and orientation planning algorithm has been proposed. Firstly, by extending the dimensions of the assignment matrix, the target-sensor assignment is refined to the level of array orientation. Secondly, by introducing new constraint conditions, it ensures that each radar selects only one array orientation at each moment. Finally, a genetic algorithm is designed based on the model characteristics to achieve efficient solution of the assignment problem. Simulations demonstrate that compared to traditional fixed-orientation methods, the proposed assignment method achieves higher target coverage and overlap coverage.

TN957