Narayanan Ram M, Pooler Richard K, Martone Anthony F, Gallagher Kyle A, Sherbondy Kelly D
Department of Electrical Engineering, The Pennsylvania State University, University Park, PA 16802, USA.
RF and Millimeter-Wave Engineering Group, Johns Hopkins University Applied Physics Laboratory, Laurel, MD 20723, USA.
Sensors (Basel). 2018 Feb 22;18(2):652. doi: 10.3390/s18020652.
This paper describes a multichannel super-heterodyne signal analyzer, called the Spectrum Analysis Solution (SAS), which performs multi-purpose spectrum sensing to support spectrally adaptive and cognitive radar applications. The SAS operates from ultrahigh frequency (UHF) to the S-band and features a wideband channel with eight narrowband channels. The wideband channel acts as a monitoring channel that can be used to tune the instantaneous band of the narrowband channels to areas of interest in the spectrum. The data collected from the SAS has been utilized to develop spectrum sensing algorithms for the budding field of spectrum sharing (SS) radar. Bandwidth (BW), average total power, percent occupancy (PO), signal-to-interference-plus-noise ratio (SINR), and power spectral entropy (PSE) have been examined as metrics for the characterization of the spectrum. These metrics are utilized to determine a contiguous optimal sub-band (OSB) for a SS radar transmission in a given spectrum for different modalities. Three OSB algorithms are presented and evaluated: the spectrum sensing multi objective (SS-MO), the spectrum sensing with brute force PSE (SS-BFE), and the spectrum sensing multi-objective with brute force PSE (SS-MO-BFE).
本文介绍了一种名为频谱分析解决方案（SAS）的多通道超外差信号分析仪，它执行多用途频谱感知，以支持频谱自适应和认知雷达应用。SAS工作在超高频（UHF）至S波段，具有一个宽带通道和八个窄带通道。宽带通道用作监测通道，可用于将窄带通道的瞬时频段调谐到频谱中的感兴趣区域。从SAS收集的数据已被用于为新兴的频谱共享（SS）雷达领域开发频谱感知算法。带宽（BW）、平均总功率、占用百分比（PO）、信号与干扰加噪声比（SINR）以及功率谱熵（PSE）已作为表征频谱的指标进行了研究。这些指标用于为不同模式在给定频谱中确定用于SS雷达传输的连续最优子带（OSB）。提出并评估了三种OSB算法：频谱感知多目标（SS-MO）、带强力PSE的频谱感知（SS-BFE）以及带强力PSE的频谱感知多目标（SS-MO-BFE）。
