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high dynamic circumstances
    GPS SIGNAL PARAMETERS ESTIMATION ALGORITHM BASED ON DATA TRANSITION DETECTION IN HIGH DYNAMIC CIRCUMSTANCES
    一种基于数据跳变检测的高动态环境GPS信号参数估计方法
    Research on Cross-Ambiguity Function Estimator for GPS Signal and the Performance Analysis in High Dynamic Circumstances
    高动态环境的GPS信号互模糊函数估计器及其性能分析
    GPS signal receiving and its algorithms under high dynamic circumstances
    高动态环境的GPS信号接收及其算法研究
    To track GPS signal in high dynamic circumstances more reliably,the paper presents a new estimator for GPS signal in high dynamic circumstances,that is cross-ambiguity function.
    为了更可靠地跟踪高动态环境GPS信号参数,提出了一种新的适应高动态环境的GPS参数估计方法———互模糊函数方法。
    Under the condition of assuming high signal-to-noise ration,it educes the estimating variance of Cross-Ambiguity function estimator and the Cramer-Rao Bounds. At last,the paper presents the result:It is asymptotically unbiased and asymptotically effective to adopt Cross-Ambiguity function for estimating jointly the delay and Doppler frequency shift of GPS signal in high dynamic circumstances.
    在假定高信噪比的条件下,推导了互模糊函数估计器的估计方差以及Cram er-Rao界,得出了采用互模糊函数法对高动态环境GPS信号的时延和多普勒频移进行联合估计是渐近无偏和渐近有效的结论。
    There is great Doppler frequency shift under high dynamic circumstances,thus the common GPS receiver cannot work reliably without the help of inertial navigation devices.
    高动态环境存在较大的多普勒频移,这使得普通的GPS接收机在没有惯导辅助的情况下很难可靠工作。
    We also studied the theory of three GPS signal parameter estimation algorithms adaptive to high dynamic circumstances,including MLE algorithm,Kalman filter algorithm,and FEKF algorithm.
    为了帮助DSP的设计,本文还研究了3种适应高动态环境的GPS信号参数估计算法,包括最大似然估计算法,卡尔曼滤波算法和频率扩展卡尔曼滤波算法。
    The paper presents a new estimator to catch and track GPS signal in high dynamic circumstances,which is ambiguity function.
    提出了一种新的适用于高动态环境GPS信号捕获跟踪的参数估计方法———模糊函数方法。
    At last,it presents the result: it is asymptotically unbiased and asymptotically effective to adopt ambiguity function for estimating jointly the delay and Doppler frequency shift of GPS signal in high dynamic circumstances.
    通过模拟仿真,得出了采用模糊函数算法对高动态环境GPS信号的时延和多普勒频移进行联合估计是渐近无偏和渐近有效的结论。
 

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