基于贝叶斯压缩感知的周跳探测与修复方法
发布时间：2018-10-17 13:55
【摘要】：针对观测噪声对周跳探测与修复性能的影响,提出了一种新的利用贝叶斯压缩感知技术进行周跳探测与修复的方法.在历元间-站间载波相位双差观测模型的基础上,通过挖掘周跳信号的稀疏特性,获取感知矩阵,推导并建立稀疏周跳探测模型,利用稀疏贝叶斯学习中的相关向量机原理,结合周跳相关数据的先验信息,基于主动相关决策理论,进行回归估计获得周跳预测值的分布,进而实现周跳的探测与修复.实验表明,新方法在仅利用单频或双频载波相位观测量的情况下能有效探测并修复周跳,性能优于正交匹配追踪法及l_1范数法.
[Abstract]:Aiming at the effect of observation noise on cycle slip detection and repair performance, a new method of cycle slip detection and repair using Bayesian compression sensing technique is proposed. Based on the double difference observation model of carrier phase between epoch and station, the sparse characteristic of cycle hopping signal is excavated, the perception matrix is obtained, the detection model of sparse cycle slip is deduced and established, and the principle of correlation vector machine in sparse Bayesian learning is used. Based on the prior information of cycle slip correlation data and active correlation decision theory, the distribution of cycle slip prediction value is obtained by regression estimation, and the cycle slip detection and repair is realized. Experiments show that the new method can effectively detect and repair cycle slips with only single or double frequency carrier phase observations, and the performance of the new method is better than that of orthogonal matching tracking method and L _ S _ 1-norm method.
【作者单位】： 哈尔滨工程大学自动化学院;
【基金】：国家自然科学基金(批准号:61273081);国家自然科学基金青年基金(批准号:61304235,61401114) 中央高校基本科研业务费专项资金(批准号:HEUCFD1431) 国家留学基金资助的课题~~
【分类号】：P228.4
[Abstract]:Aiming at the effect of observation noise on cycle slip detection and repair performance, a new method of cycle slip detection and repair using Bayesian compression sensing technique is proposed. Based on the double difference observation model of carrier phase between epoch and station, the sparse characteristic of cycle hopping signal is excavated, the perception matrix is obtained, the detection model of sparse cycle slip is deduced and established, and the principle of correlation vector machine in sparse Bayesian learning is used. Based on the prior information of cycle slip correlation data and active correlation decision theory, the distribution of cycle slip prediction value is obtained by regression estimation, and the cycle slip detection and repair is realized. Experiments show that the new method can effectively detect and repair cycle slips with only single or double frequency carrier phase observations, and the performance of the new method is better than that of orthogonal matching tracking method and L _ S _ 1-norm method.
【作者单位】： 哈尔滨工程大学自动化学院;
【基金】：国家自然科学基金(批准号:61273081);国家自然科学基金青年基金(批准号:61304235,61401114) 中央高校基本科研业务费专项资金(批准号:HEUCFD1431) 国家留学基金资助的课题~~
【分类号】：P228.4
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