This paper is concerned with the distributed guaranteed estimation for tracking two interacting mobile targets over a multi-sensor network in the presence of unknown-but-bounded noises and various adversarial attacks. First, a heterogeneous sensor network framework in terms of two distinct groups of sensors is employed to monitor the two targets. Each sensor in either group possesses different sensing, processing and communicating capabilities, thereby leading to distinct communication topologies among intra- and inter-group sensors. Second, a unified attack model is established to skillfully accommodate multiple adversarial attacks including node manipulation attacks and deception attacks. Third, two different groups of distributed consensus-based estimators are delicately constructed to deal with the network heterogeneity. Criteria for designing the desired estimators are then derived such that the true states of the two maneuvering targets are guaranteed to be enclosed by the calculated estimate ellipsoids at each time step regardless of the noises and attacks. Furthermore, two tractable optimization algorithms, in both single- and two-target tracking cases, are applied to recursively calculate the smallest possible ellipsoidal estimate sets. Finally, numerical verification of distributed two-vehicle tracking is carried out to demonstrate the effectiveness and applicability of the obtained results.

本文涉及分布式保证估计，该估计用于在存在未知但有界噪声和各种对抗攻击的情况下，通过多传感器网络跟踪两个交互的移动目标。首先，就两组不同的传感器而言，采用异构传感器网络框架来监视两个目标。每个组中的每个传感器都具有不同的感测，处理和通信功能，从而导致组内和组间传感器之间的通信拓扑不同。其次，建立统一的攻击模型以熟练地应对多种对抗攻击，包括节点操纵攻击和欺骗攻击。第三，精心构造了两组不同的基于分布式共识的估计量，以应对网络的异构性。然后得出设计期望估计量的标准，以确保在每个时间步长，无论噪声和攻击如何，两个机动目标的真实状态都被计算的估计椭球体包围。此外，在单目标跟踪和两目标跟踪情况下，都采用了两种易于处理的优化算法来递归计算可能的最小椭圆估计集。最后，进行了分布式两车跟踪的数值验证，以证明所获得结果的有效性和适用性。在单目标跟踪和两目标跟踪的情况下，都应用递归计算可能的最小椭圆估计集。最后，进行了分布式两车跟踪的数值验证，证明了所得结果的有效性和适用性。在单目标跟踪和两目标跟踪的情况下，都应用递归计算可能的最小椭圆估计集。最后，进行了分布式两车跟踪的数值验证，以证明所获得结果的有效性和适用性。