山区信号遮挡环境无人机应急通信信号捕获优化算法

Optimized signal acquisition algorithm for UAV emergency communication in mountainous signal-occluded environments

  • 摘要: 多径衰落、阴影效应、多普勒频移等因素相互耦合,使得山区信号遮挡环境下的应急通信信号捕获面临较大难度与挑战,因此开展山区信号遮挡环境无人机(unmanned aerial vehicle, UAV)应急通信信号捕获优化算法设计研究. 接收并缓冲离散时间数字中频信号,利用自适应谱峭度滤波对信号段进行增强处理,基于广义似然比检验(generalized likelinhood ratio test, GLRT)信号段中是否存在应急通信信号,融合先验信息构建动态导向搜索空间,再通过导向并行循环获取应急通信信号的相关功率谱. 采用有序统计量构建鲁棒性更强的自适应门限,对应急通信信号进行判决,得到初始估计的码相位与多普勒频率. 确定应急通信信号的连续观测微小区域,计算检验统计量,判定应急通信信号是否捕获成功,并明确最终的码相位与多普勒频率,将其传递给跟踪环,进而实现山区信号遮挡环境UAV应急通信信号的有效捕获与精准跟踪. 实验结果显示:设计算法捕获应急通信信号的码相位/多普勒频率与实际码相位/多普勒频率高度吻合,应急通信信号误捕率最小值达到了2%.

     

    Abstract: The coupling effects of multipath fading, shadowing, and Doppler shift make signal acquisition extremely challenging for unmanned aerial vehicle (UAV) emergency communication in mountainous environments. To address this issue, an optimized acquisition algorithm is proposed. The algorithm first buffers discrete-time digital intermediate frequency signals and enhances signal segments using adaptive spectral kurtosis filtering. The generalized likelihood ratio test (GLRT) is then employed to detect the presence of emergency communication signals. By integrating prior information, a dynamic guided search space is constructed, and the correlation power spectrum is obtained through guided parallel cycling. An ordered statistic-based adaptive threshold, which offers stronger robustness, is established to acquire initial estimates of code phase and Doppler frequency. Subsequently, a small continuous observation region is determined to calculate test statistics, confirm successful acquisition, and refine the final code phase and Doppler frequency for handover to the tracking loop. Experimental results demonstrate that the code phase and Doppler frequency acquired by the proposed algorithm closely match the actual values, achieving a minimum false acquisition rate of 2%.

     

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