RF Signal Source Target Detection Method Based on Monte Carlo Algorithm in Distributed Electromagnetic Spectrum Monitoring System

Zhenjia Chen, Lihui Wang
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Abstract

In order to improve the blind localization accuracy of radio signal sources, this paper proposes a radio frequency (RF) signal source target localization method based on Monte Carlo algorithm. Combined with the free-space propagation loss characteristics of electromagnetic waves, real-time electromagnetic spectrum detection data based on distributed detection nodes are analyzed. Based on the spatial distribution of electromagnetic spectrum, the target location method of radio frequency signal source is studied. Distributed detection nodes detect electromagnetic spectrum data of the same radio frequency signal source target at different spatial locations. The Monte Carlo algorithm is used for the cooperative detection target localization method of the RF signal source. With the increase of random times, the estimation result with the smallest cumulative distance error is used as the estimation result of the target position of the radio frequency signal source. The measured data show that the method can improve the blind detection and positioning accuracy of radio signal sources in the target area.
分布式电磁频谱监测系统中基于蒙特卡罗算法的射频信号源目标检测方法
为了提高射频信号源的盲定位精度,提出了一种基于蒙特卡罗算法的射频信号源目标定位方法。结合电磁波的自由空间传播损耗特性,对基于分布式检测节点的实时电磁频谱检测数据进行了分析。基于电磁波谱的空间分布,研究了射频信号源的目标定位方法。分布式检测节点对同一射频信号源目标在不同空间位置的电磁频谱数据进行检测。将蒙特卡罗算法用于射频信号源的协同检测目标定位方法。随着随机次数的增加,使用累积距离误差最小的估计结果作为射频信号源目标位置的估计结果。实测数据表明,该方法可以提高目标区域内无线电信号源的盲检测和定位精度。
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