Ojo J S, Adelakun A O, Edward O V
Department of Physics, Federal University of Technology, Akure, Ondo state, Nigeria.
Heliyon. 2019 Aug 5;5(8):e02083. doi: 10.1016/j.heliyon.2019.e02083. eCollection 2019 Aug.
Complexity and nonlinear trend in the internal activities of the troposphere has been a great factor affecting the transmission and receiving of good quality of signals globally. In lieu of this, prediction of chaos and positive refractivity gradients for line-of-sight microwave radio paths is necessary for designing radio systems. Complexity in the troposphere due to changes in meteorological parameters can lead to the strong negative gradient (or super-refraction) which afterward lead to interference between terrestrial links and satellite earth stations. In this paper, a comparative study on the degree of complexity of Radio Refractivity Gradient (RRG) using Chaotic Quantifiers (CQ) such as Phase Plot Reconstruction (PPR), Average Mutual Information (AMI), False Nearest Neighbor (FNN), Lyapunov Exponent (LE), Tsallis Entropy (TS) and Recurrence Plot (RP) are discussed extensively. The RRG data (2011-2012) used in this work were obtained for 0 m to 100 m, from the archives of Tropospheric Data Acquisition Network (TRODAN) from five different stations namely; Akure (. ), Enugu (. ), Jos (. ), Minna (. ) and Sokoto (. ). The chaotic quantifiers are used to investigate the degree of complexity in the 30 minutes interval atmospheric data from the selected locations which is specified into rainy, dry and transition season months. The parallel and short diagonal lines observed depicts the evidence of chaos. However, the observed result shows that the RRG is higher during the rainy season than the dry season. In other words, the information is valid for the proposed data analysis, since the LE is actually directly proportional to the TE. Also, the results further show that the rainy season months exhibit higher chaoticity than the dry season months, which is equivalent to high radio refractivity gradient observed across the selected stations.
对流层内部活动的复杂性和非线性趋势是影响全球高质量信号传输与接收的一个重要因素。鉴于此，对于视距微波无线电路径的混沌和正折射梯度进行预测，对于设计无线电系统而言是必要的。由于气象参数变化导致的对流层复杂性可能会产生强烈的负梯度（或超折射），进而导致地面链路与卫星地球站之间的干扰。本文广泛讨论了使用混沌量化指标（CQ），如相图重构（PPR）、平均互信息（AMI）、伪最近邻（FNN）、李雅普诺夫指数（LE）、Tsallis熵（TS）和递归图（RP），对无线电折射梯度（RRG）的复杂程度进行的比较研究。本研究中使用的RRG数据（2011 - 2012年）是从对流层数据采集网络（TRODAN）的档案中获取的，范围为0米至100米，来自五个不同的站点，分别是阿库雷（. ）、埃努古（. ）、乔斯（. ）、米纳（. ）和索科托（. ）。混沌量化指标用于研究选定地点30分钟间隔大气数据的复杂程度，这些数据被划分为雨季、旱季和过渡季节月份。观察到的平行和短对角线表明存在混沌迹象。然而，观察结果表明，雨季的RRG高于旱季。换句话说，该信息对于所提出的数据分析是有效的，因为李雅普诺夫指数实际上与熵直接成正比。此外,结果进一步表明，雨季月份比旱季月份表现出更高的混沌性，这等同于在选定站点观察到的高无线电折射梯度。
