Accurate Spectral Fitting in the Upper F-Region Using the Randomly Coded Data of the Arecibo 430 MHz Radar

Accurately resolving the ion composition in the upper F2 region and topside ionosphere remains a challenge due to temperature-composition ambiguity and measurement limitations. This study presents a hybrid fitting algorithm that combines exhaustive dictionary search with gradient descent to improve the estimation of incoherent scatter spectrum parameters, particularly He⁺ and H⁺ fractions, ion temperature (T_i), and electron temperature (T_e). The algorithm performs independent height-based fitting while incorporating constraints on T_e and T_i to enhance stability. We apply the method to Arecibo incoherent scatter radar coded-long-pulse (CLP) data to demonstrate its effectiveness. To improve the fitting results, we employ an adaptive thresholding method to reduce the interference from satellites and space debris and allow negative He⁺ concentration to mitigate fitting biases. With various factors considered, we show that parameter estimations, especially H⁺ and He⁺ fractions, can be significantly improved. Comparisons with multi-radar autocorrelation function results further validate our improvements in accuracy and consistency. Although the CLP program was initiated at Arecibo decades ago, this is the first time that the data has been used to derive light ion fractions. This study provides a more robust framework for aeronomy studies in the upper F region.