Based on stochastic process theory, the bounded convergence of forgetting factor least square algorithm (FFLS for short) is studied and the upper bound of the parameter tracking error is given.

利用随机过程理论研究了遗忘因子最小二乘法(FFLS)的有界收敛性，给出了参数估计误差的上界。

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The theory shows that correlator space is an important factor of measure error.

根据理论分析，相关间隔是影响伪码测距的重要因素。

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