Velocity-assisted multidimensional scaling

Sandeep Kumar, K. Rajawat
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引用次数: 1

Abstract

This paper considers the problem of cooperative localization in mobile networks. In static networks, node locations can be obtained from pairwise distance measurements using the classical multidimensional scaling (MDS) approach. This paper introduces a modified MDS framework that also incorporates relative velocity measurements available in mobile networks. The proposed cost function is minimized via a provably convergent, low complexity majorization algorithm similar to SMACOF. The algorithm incurs low computational and communication cost, and allows practical constraints such as missing measurements and variable node velocities. Simulation results corroborate the performance gains obtained by the proposed algorithm over state-of-the-art localization algorithms.
速度辅助的多维缩放
研究了移动网络中的协同定位问题。在静态网络中,可以使用经典的多维尺度(MDS)方法从两两距离测量中获得节点位置。本文介绍了一种改进的MDS框架,该框架还结合了移动网络中可用的相对速度测量。所提出的代价函数通过一个可证明收敛的,低复杂度的算法最小化,类似于SMACOF。该算法具有较低的计算和通信成本,并允许诸如缺失测量和可变节点速度等实际约束。仿真结果证实了该算法相对于最先进的定位算法所获得的性能提升。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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