Traditional network localization algorithms contain ranging and localization steps, which have systematic disadvantages. We propose an algorithm dubbed direct particle filter based distributed network localization (DiPNet). A node's location is directly estimated from the received signals, incorporating location uncertainty of neighboring nodes. The propagation effects on DiPNet become insignificant for dense networks, due to the massive-link collective physical layer processing. DiPNet achieves a near-optimal performance with low complexity, which is particularly attractive for realtime dense-network localization.

中文翻译：

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适用于密集网络的分布式直接定位

传统的网络定位算法包含测距和定位步骤，具有系统性的缺点。我们提出了一种称为基于直接粒子滤波器的分布式网络定位（DiPNet）的算法。节点的位置直接从接收到的信号中估计出来，并结合了相邻节点的位置不确定性。由于大规模链路集体物理层处理，DiPNet 上的传播效应对于密集网络变得微不足道。DiPNet 以低复杂度实现了接近最优的性能，这对于实时密集网络定位特别有吸引力。