Cognitive Sensor Diagnostics for HF Radio Channels Using Software-Defined Methods and Physical Verification

This study introduces a novel method for evaluating wideband ionospheric dispersive high-frequency (HF) radio channels with bandwidths up to 1 MHz, specifically tailored for near-vertical incidence skywave (NVIS) communication systems. The proposed approach enhances channel availability and covertness through adaptive inverse filtering of the frequency response to mitigate intramode dispersion, leveraging real-time sensor data. The method employs software-defined radio (SDR) technology for dynamic channel diagnostics and adaptive distortion correction. Physical experiments conducted on a 90-km NVIS radio link between Yoshkar-Ola and Lake Yalchik demonstrated significant improvements, including enhanced channel availability and an energy gain of up to 23 dB. These findings establish cognitive sensor diagnostics as a promising approach for modern HF communication systems, ensuring autonomous operation in NVIS mode and maintaining a specified symbol transmission rate.