We consider a wireless source localization network in which a target node emits localization signals that are used by anchor nodes to estimate the target node position. In addition to target and anchor nodes, there can also exist eavesdropper nodes and jammer nodes which aim to estimate the position of the target node and to degrade the accuracy of localization, respectively. We first propose the problem of eavesdropper selection with the goal of optimally placing a given number of eavesdropper nodes to a subset of possible positions in the network to estimate the target node position as accurately as possible. As the performance metric, the Cramer-Rao lower bound (CRLB) related to the estimation of the target node position by eavesdropper nodes is derived, and its convexity and monotonicity properties are investigated. By relaxing the integer constraints, the eavesdropper selection problem is approximated by a convex optimization problem and algorithms are proposed for eavesdropper selection. Moreover, in the presence of parameter uncertainty, a robust version of the eavesdropper selection problem is developed. Then, the problem of jammer selection is proposed where the aim is to optimally place a given number of jammer nodes to a subset of possible positions for degrading the localization accuracy of the network as much as possible. A CRLB expression from the literature is used as the performance metric, and its concavity and monotonicity properties are derived. Also, a convex optimization problem and its robust version are derived after relaxation. Moreover, the joint eavesdropper and jammer selection problem is proposed with the goal of placing certain numbers of eavesdropper and jammer nodes to a subset of possible positions. Simulation results are presented to illustrate performance of the proposed algorithms.
翻译:我们考虑的是一个无线源本地化网络, 目标节点显示本地化信号, 由锁定节点用来估计目标节点位置。 除了目标和锁定节点之外, 还可以存在与估计目标节点位置和降低本地化精确度相关的eaves窃听器和干扰节点。 我们首先提出窃听器选择问题, 目的是将一定数量的 eavespoper 节点放置到网络中可能的一组位置, 以便尽可能准确地估计目标节点位置 。 此外, 性能衡量标准, Cramer- Rao 较低的约束( CRLB) 显示与估计目标节点位置相关的 eavesdropper 节点节点和 干扰节点节点节点, 旨在分别估计目标节点的位置和降低本地化的精确度。 通过放松整分点限制, eavesdropperproduction 问题被近似地标选取, 和 evolutional 表达 。 此外, 由于参数的准确性能显示的是, 最稳性 的精确性选取 度是, 最稳性选取, 预选取 度 的 的 度是 。