Dynamic optimization of high-bandwidth multi-receiver signals for civil aircraft flight tests telemetry

Civil aircraft flight tests are distinguished by parallel multi-task operations, multi-sensor collaboration, and high-frequency data acquisition. The exponential growth in telemetry data generated in a single flight imposes stringent requirements on the high-bandwidth transmission capabilities of telemetry systems and the real-time optimization of multi-receiver signals. This study focuses on addressing the dynamic optimization of high-bandwidth multi-receiver signals during flight tests, aiming to enhance demodulation accuracy and ensure stable real-time transmission of large-scale telemetry data. A channel model for complex scenarios was constructed to analyze signal redundancy and dynamic switching in multi-receiver links, while an improved routing protocol integrated with multi-dimensional signal evaluation was investigated. A modular simulation model for the multi-receiver telemetry system was developed within a highly dynamic wireless ad hoc network environment. By enhancing the AODV and LEACH routing protocols, multi-path backup and energy consumption optimization were achieved. A multi-dimensional signal optimization algorithm was utilized to dynamically evaluate and fuse bit synchronization and frame synchronization via voting, enabling real-time selection of the optimal received signal in complex environments. The findings indicate that high-bandwidth multi-receiver signal optimization and enhanced routing strategies effectively alleviate challenges associated with multipath fading, channel obstruction, and high-speed mobility in flight test scenarios, thereby facilitating real-time channel monitoring and dynamic switching while improving data timeliness and accuracy. Simulation results demonstrate that under high-dynamic conditions, the proposed algorithm reduces the average BER to 3e-6 at 10 dB SNR, improves the frame synchronization success rate to 98.9%, and reduces invalid channel switching frequency by approximately 84% compared to traditional methods.