基于选择性注意机理的高空视界覆盖节点选取

基于复杂地形约束的三维高空视界覆盖是空间分析领域中的NP难问题,其求解计算量较大。针对这个问题,提出一种基于注意认知理论的高空视界覆盖节点选取方法。其基本思想是利用认知心理学的选择性注意原理,来模拟人脑处理覆盖问题的机制,即不断有意识的选择性注意有价值的感知节点并进行注意后过滤处理。基于该机制的算法能有效降低高空视界覆盖的计算量。实验表明,提出的高空视界覆盖节点选取算法相对基于粒子群的寻优方法耗时短,且可以让用户根据实际问题要求的视界覆盖率来选择经济的非完全覆盖方案,以节省实地布置节点的开支。

Node selection for upper airspace coverage based on selective attention mechanism

The 3-dimensional upper airspace coverage on the restriction of the terrain is the NP problem in the space analysis.Its solution needs a large amount of calculation.To solve the problem,a method based on attention cognition theory for upper airspace coverage is proposed.This method simulates the mechanism in which the human brain selectively pays attention to valuable nodes in turn and carries out the filtration of the covered space after attention.The filtration can decrease the amount of calculations.The experiment indicates that this method has the advantage that the time spent for optimization is shorter compared with the method based on PSO.It is necessary to point out that users can use the method to select a scheme for un-completed overage according to actual requirements,which can save the expense of setting nodes on the spot.