Constrained robust submodular sensor selection with applications to multistatic sonar arrays
Constrained robust submodular sensor selection with applications to multistatic sonar arrays
复制标题
受约束的鲁棒子模块传感器选择及其在多基地声纳阵列中的应用
DOI：
10.1049/iet-rsn.2017.0075
复制
发表时间：
2016
期刊：
影响因子：
--
通讯作者：
L. Atlas
中科院分区：
文献类型：
--
作者：
Thomas Powers;J. Bilmes;D. Krout;L. Atlas
我们开发了一个框架，用于从传感器具有根深蒂固的独立结构的领域中选择传感器子集。给定任意独立模式，我们构建一个图表来表示传感器之间的成对独立性，这意味着这些传感器可以同时运行。该独立图的所有完全连接的子图（派系）的集合形成了拟阵的独立集合，在该拟阵上我们最大化了一组子模目标函数的最小值。我们提出了一种名为 MatSat 的新颖算法，它利用子模性，从而返回一个接近最优的解决方案，其近似保证在平均情况场景的一小部分范围内。我们通过最大化传感器覆盖范围，将此框架应用于主动多基地声纳阵列的 ping 序列优化，并得出少数目标的最小检测概率的下限。在这些 ping 序列优化模拟中，MatSat 超出了分数下限并达到接近最佳的性能。
We develop a framework to select a subset of sensors from a field in which the sensors have an ingrained independence structure. Given an arbitrary independence pattern, we construct a graph that denotes pairwise independence between sensors, which means those sensors may operate simultaneously. The set of all fully-connected subgraphs (cliques) of this independence graph forms the independent sets of a matroid over which we maximize the minimum of a set of submodular objective functions. We propose a novel algorithm called MatSat that exploits submodularity and, as a result, returns a near-optimal solution with approximation guarantees that are within a small factor of the average-case scenario. We apply this framework to ping sequence optimization for active multistatic sonar arrays by maximizing sensor coverage and derive lower bounds for minimum probability of detection for a fractional number of targets. In these ping sequence optimization simulations, MatSat exceeds the fractional lower bounds and reaches near-optimal performance.
融合获得独立性。
DOI：
10.1085/jgp.200810050
发表时间：
2008
期刊：
The Journal of general physiology
影响因子：
--
作者：
Lindau,Manfred
通讯作者：
Lindau,Manfred