检索规则说明:AND代表“并且”;OR代表“或者”;NOT代表“不包含”;(注意必须大写,运算符两边需空一格)
检 索 范 例 :范例一: (K=图书馆学 OR K=情报学) AND A=范并思 范例二:J=计算机应用与软件 AND (U=C++ OR U=Basic) NOT M=Visual
机构地区:[1]北京理工大学信息与电子学院,北京100081
出 处:《系统工程与电子技术》2014年第2期376-381,共6页Systems Engineering and Electronics
基 金:国家高技术研究发展计划(863计划)(2012AA121604)资助课题
摘 要:针对传统卡尔曼滤波器用于高动态载波跟踪时性能不够理想的问题,提出一种基于机动目标模型匹配的卡尔曼滤波载波跟踪算法,能够在载波参数剧烈变化的条件下实现稳定的载波同步。所提算法较传统算法更加契合实际环境,具有实用价值高、应用范围广等优点。使用线性卡尔曼滤波器,无需矩阵求逆运算,计算复杂度低,便于工程实现。仿真结果表明,所提算法在跟踪具有剧烈动态特性的载体信号时能够显著提高跟踪精度,且跟踪门限信噪比能够降低约3dB。For the problem then the traditional Kalman filter does not perform well enough when it is used in high-dynamic carrier tracking, an improved Kalman filter based on the matched maneuvering target model is proposed, which could achieve stable carrier synchronization under high dynamic conditions. Compared with traditional algorithms, the proposed algorithm is more realistic, with high practical value, and a wide range of applications. Moreover, the tracking system uses a linear Kalman filter without matrix inverse operation, which has low computational complexity and is easy to implement in the real system. Simulation results show that the proposed algorithm is more suitable for the high-dynamic environment, which could significantly improve the tracking accuracy and reduce about 3 dB of the tracking threshold on signal-to-noise ratio.
分 类 号:TN911[电子电信—通信与信息系统]
正在载入数据...
正在载入数据...
正在载入数据...
正在载入数据...
正在载入数据...
正在载入数据...
正在载入数据...
正在链接到云南高校图书馆文献保障联盟下载...
云南高校图书馆联盟文献共享服务平台 版权所有©
您的IP:216.73.216.154