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A Method Exploiting Compressive Sampling for Localization of Radio Frequency Emitters

机译:一种利用射频发射器定位压缩采样的方法

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This article presents a novel method for radio frequency (RF) emitter localization by using wideband spectrum sensors (WSSs) exploiting compressive sampling (CS). The method assumes that receivers with known Cartesian coordinates in the plane are deployed in the area, where the transmitters are expected to be. By using a nonuniform sampling (NUS) scheme, each WSS allows one to relax the throughput requirements for the data acquisition and transmission tasks. The mathematical description followed by numerical analysis is presented. Then, hardware implementation for the receiver was realized, by using commercial off-the-shelf components. The obtained results from simulation tests are reported, and an experimental assessment of the proposed method is provided. The experimental results are compared with those obtained by applying the maximum likelihood (ML) algorithm on the samples acquired according to the Nyquist criteria. As a figure-of-merit, the compression ratio (CR) of the proposed NUS scheme was evaluated and it was experimentally obtained that even for CR & x003D; 64 the spectrum reconstruction is acceptable for being used in the ML algorithm.
机译:本文介绍了利用宽带频谱传感器(WSSS)利用压缩采样(CS)来提出一种用于射频(RF)发射器定位的新方法。该方法假设具有该平面中的已知笛卡尔坐标的接收器部署在该区域中,其中预期发射器是。通过使用非均匀采样(NUS)方案,每个WSS允许一个人放宽数据采集和传输任务的吞吐量要求。提出了数值分析的数学描述。然后,通过使用商业现成部件实现接收器的硬件实现。报道了所得仿真试验的结果,提供了所提出的方法的实验评估。将实验结果与通过在根据奈奎斯特标准获取的样本上施加最大似然(ML)算法而获得的那些。作为优异的象征,评估了所提出的NUS方案的压缩比(Cr),并且实验地获得,即使Cr&x003D也是如此; 64频谱重建可用于在M1算法中使用。

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