Based on the theory of the optimal estimation, this paper proposes a multi-sensors decentralized algorithm to solve the parameter estimation problems in noise environment.
本文基于最优估计理论，提出了一种多传感器分散估计融合算法，以解决测量噪声干扰下参数估计问题。
The three basic problems of two-dimensional (2-d) hidden Markov models (HMMs) are studied, including probability evaluation, optimal states and parameter estimation.
研究了2维隐马尔可夫模型的三个基本问题，包括概率评估问题、最优状态问题和参数估计问题。
The adaptive compensation term of the optimal approximation error is adopted to minimize the influence of the modeling error and the parameter estimation error.
并通过引入最优逼近误差的自适应补偿项来消除建模误差和参数估计误差的影响。
Primary filter accomplishes the fusion of public state vectors about sub filters and time updating, and outputs the credible, precise and optimal estimation of navigation parameter error.
主滤波器(全局滤波器)进行子滤波器的公共状态矢量融合和时间更新，输出可靠、准确的导航参数误差的全局最优估计量。
Primary filter accomplishes the fusion of public state vectors about sub filters and time updating, and outputs the credible, precise and optimal estimation of navigation parameter error.
主滤波器(全局滤波器)进行子滤波器的公共状态矢量融合和时间更新，输出可靠、准确的导航参数误差的全局最优估计量。
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