从传统的接收机环路多径抑制方法出发,通过纠正码环相关曲线畸变和自适应载波信号更新机制跟踪弱动态载波信号两个层次,并行减缓多径效应对接收机跟踪捕获带来的延迟影响。首先,针对码环内部函数畸变带来的自相关迭代误差问题,利用机器学习领域中的随机霍夫变换(RHT)斜率检测法辅助减小窄相关器的误差;其次,设计了一种自适应阈值载波跟踪信号状态模型,用于解决高遮挡低载噪比(CNR)条件下的信号跟踪受限问题。从不同的角度将该方法与现有方法做了对比和分析,结果表明:应用RHT 斜率抑制法辅助自适应增强载波信号跟踪的定位模型性能相较于传统的高分辨率技术(HRC)和卡尔曼滤波(KF)载波跟踪方法均有明显的提升,其中本文提出的方法可以在1.8 s左右的信号延迟时及时恢复载波信号失锁。此外,从最终的定位结果可知,实验场景中多径(MP)效应较强的D区域,定位误差的均方根误差(RMSE)降低了6.3 m.

Starting from the traditional receiver loop multipath suppression method, the delayeffect of multipath effect on receiver tracking and capture is mitrgated in parallel by correcting thecode loop correlation curve distortion and adaptive carrier signal update mechanism to track theweak dynamic carrier signal at two levels. First, an adaptive threshold carrier tracking signalstate model is designed to solve the problem of limited signal tracking under high occlusion andlow CNR conditions, with the aid of the Random Hough Transform slope detection method in the field of machine learning to reduce the error of narrow correlator. Comparson was made with existingmethods from different perspectives. The results show that the localization modeling propertyof applying the RHT method assisted by adaptive enhanced carrier signal tracking is significantlyimproved compared with both the conventional HRC and Kalman filter carrier trackingmethods, with the method proposed in this paper being able to recover the carrier signal out oflock in time for a signal delay of around 1.8 s. In addition, the final localization results show thatthe root mean square error is reduced by 6.3 m in the D region of the experimental scenario wherethe MP effect is strong.