Heterogeneous sensor networks (HSN) find a wide range of applications in the field of military and civilian environments, where sensor nodes are utilized to estimate the position of a target with both dynamics and control input being unknown for the purposes of tracking. In the HSN, nodes are considered active depending upon their ability to sense the target output while the others are taken passive. Accurate estimation requires local information exchange among the spatially located sensor nodes, so that the active nodes as well as the passive nodes converge simultaneously to the same value. The local information exchange among the nodes is dictated by a connected graph. By using the criterion of collective observability, a novel distributed adaptive estimation scheme is introduced via adaptive observer where the nodes are allowed to have different sensor modalities. Using the estimated information, a subset of active and passive nodes, referred to as mobile nodes, can track the moving target. By using a constant state feedback controller at each mobile node, the state and parameter estimation as well as the tracking errors are shown to be uniformly ultimately bounded. Simulation results verify theoretical claims.

中文翻译：

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使用主动-被动传感器网络进行分布式自适应状态估计和跟踪

异构传感器网络（HSN）在军事和民用环境领域中找到了广泛的应用，在这些领域中，传感器节点用于估计目标的位置，而动态和控制输入都不为跟踪目的。在HSN中，根据节点感知目标输出的能力将其视为主动节点，而其他节点则被视为被动节点。准确的估计需要在空间上分布的传感器节点之间进行本地信息交换，以便主动节点和被动节点同时收敛到相同值。节点之间的本地信息交换由连接图决定。通过使用集体可观察性标准 通过自适应观测器引入了一种新颖的分布式自适应估计方案，其中节点被允许具有不同的传感器模态。使用估计的信息，主动节点和被动节点的子集（称为移动节点）可以跟踪移动目标。通过在每个移动节点上使用恒定状态反馈控制器，状态和参数估计以及跟踪误差将显示为最终一致的边界。仿真结果验证了理论要求。