基于rss的辐射源定位迭代网格搜索

Suzan Ureten, A. Yongaçoğlu, E. Petriu
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引用次数: 6

摘要

在本文中,我们提出了一种降低复杂度的迭代网格搜索技术,用于使用接收信号强度(RSS)测量定位认知无线电网络中不合作的主发射器。该技术基于将搜索空间划分为较小数量的候选子区域,选择最小代价函数的最佳候选区域,并在选择上迭代重复该过程。我们评估了该算法在独立阴影场景下的性能,并表明其性能接近完整搜索的性能,特别是在小阴影扩展值下,计算复杂度显著降低。当基于使用传感器测量的两种不同的数据辅助方法指定初始搜索空间时,我们还查看了算法的性能。仿真结果表明,数据辅助初始化方案并不比盲初始化方案提供性能改进。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Iterative grid search for RSS-based emitter localization
In this paper, we present a reduced complexity iterative grid-search technique for locating non-cooperating primary emitters in cognitive radio networks using received signal strength (RSS) measurements. The technique is based on dividing the search space into a smaller number of candidate subregions, selecting the best candidate that minimizes a cost function and repeating the process iteratively over the selections. We evaluate the performance of the proposed algorithm in independent shadowing scenarios and show that the performance closely approaches to that of the full search, particularly at small shadowing spread values with significantly reduced computational complexity. We also look at the performance of our algorithm when the initial search space is specified based on two different data-aided approaches using sensor measurements. Our simulation results show that the data-aided initialization schemes do not provide performance improvement over blind initialization.
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