Commercial off-the-shelf (COTS) Global Navigation Satellite System (GNSS) receivers face significant limitations under high-dynamic conditions, particularly in high-acceleration environments such as those experienced by launch vehicles. These performance degradations, often observed as discontinuities in the navigation solution, arise from the inability of traditional tracking loop bandwidths to cope with rapid variations in synchronization parameters. Software-Defined Radio (SDR) receivers overcome these constraints by enabling flexible reconfiguration of tracking loops; however, manual tuning involves a complex, multidimensional search and seldom ensures optimal performance. This work introduces a genetic algorithm-based optimization framework that autonomously explores the receiver configuration space to determine optimal loop parameters for phase, frequency, and delay tracking. The approach is validated within an SDR environment using realistically simulated GPS L1 signals for three representative dynamic regimes -guided rocket flight, Low Earth Orbit (LEO) satellite, and static receiver-processed with the open-source GNSS-SDR architecture. Results demonstrate that evolutionary optimization enables SDR receivers to maintain robust and accurate Position, Velocity, and Time (PVT) solutions across diverse dynamic conditions. The optimized configurations yielded maximum position and velocity errors of approximately 6 m and 0.08 m/s for the static case, 12 m and 2.5 m/s for the rocket case, and 5 m and 0.2 m/s for the LEO case.

翻译：商用现货（COTS）全球导航卫星系统（GNSS）接收机在高动态条件下，尤其是在运载火箭等经历高加速度的环境中，面临显著性能限制。这些性能下降通常表现为导航解算的不连续性，源于传统跟踪环路带宽无法适应同步参数的快速变化。软件定义无线电（SDR）接收机通过灵活重构跟踪环路克服了这些限制；然而，手动调谐涉及复杂的多维搜索，且很少能确保最优性能。本研究提出了一种基于遗传算法的优化框架，能够自主探索接收机配置空间，以确定相位、频率和延迟跟踪的最优环路参数。该方法在SDR环境中通过开源GNSS-SDR架构，使用真实模拟的GPS L1信号对三种典型动态场景——制导火箭飞行、低地球轨道（LEO）卫星和静态接收机——进行了验证。结果表明，进化优化使SDR接收机能够在不同动态条件下保持稳健且精确的位置、速度与时间（PVT）解算。优化配置在静态场景中实现了约6米和0.08米/秒的最大位置与速度误差，在火箭场景中为12米和2.5米/秒，在LEO场景中为5米和0.2米/秒。