GNSS自适应阵列天线引入测量误差的补偿技术研究

项目名称： GNSS自适应阵列天线引入测量误差的补偿技术研究

项目编号： No.61301094

项目类型： 青年科学基金项目

立项/批准年度： 2014

项目学科： 无线电电子学、电信技术

项目作者： 赵宏伟

作者单位： 西北工业大学

项目金额： 26万元

中文摘要： 全球卫星导航系统(GNSS)信号在传播过程中容易受到各种干扰的影响。自适应阵列天线作为一种有效的空域滤波工具，被广泛应用于GNSS的抗干扰技术研究中。然而，自适应阵列天线在抑制干扰的过程中，自适应权值的变化破坏了GNSS信号的完整性，这给接收机相位测量引入了误差。在对导航精度要求高的场合，这些误差必须被消除。本项目拟从理论上推导自适应阵列天线引入测量误差的来源；通过建立信号仿真模型估算自适应阵列引入误差的大小，并在干扰抑制性能与导航精度之间寻找一个最佳平衡；拟提出一种基于接收机跟踪环的误差补偿算法，该补偿算法能够在不改变现有接收机架构的情况下，以最小的计算量完成自适应阵列引入误差的补偿，并且补偿性能将不局限于某种特定的自适应波束形成算法；最后通过软件仿真和硬件实验验证提出算法的可行性。该项目的完成将大大提升GNSS接收机的导航精度，有力推动自适应阵列天线在GNSS抗干扰中的应用。

中文关键词： 卫星导航系统；自适应阵列天线；干扰抑制；误差估计；误差补偿

英文摘要： The signals of Global Navigation Satellite System (GNSS) are vulnerable to distort from the radio-frequency interference. As an effective tool for spatial filtering, adaptive antenna array has been widely used in the research of GNSS anti-interference. However, in the process of inteference suppression for GNSS adaptive antenna array, the variation of adaptive weights will destroy the integrity of the GNSS signals, which induced bias errors to GNSS phase measurement. For precise applications, these errors must be cancelled. In this project, the effects of adaptive antenna on GNSS signal will be analyzed, the source of code phase biases and carrier phase biases will be conducted. the values of bias error will be estimated by using signal simulation model, and a balance strategy between navigation accuracy and interference suppression will be addressed; a novel biases compensation algorithm based on the tracking loop of GNSS receivers will be proposed innovatively. this algorithm will mitigate the biases without changing the existing receiver architecture, and the performance of biases compensation will not be limited to certain beamforming algorithm. Finally, the proposed compensation algorithm will be applied on GNSS anti-interference hardware platform, and the real GNSS data will be used to verify the feasibili

英文关键词： Global Navigation Satellite System(GNSS)；Adaptive Antenna Array；Interference Suppression；Biases Estimation；Biases Compensation