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中文摘要：
准确的先验信息对于经典Kalman滤波和自适应滤波都非常重要。应用Kalman滤波时，先验模型的确定往往具有一定的随意性和较强的经验性，缺乏理论基础。以GNSS／INS组合导航为例，利用时频特性分析的方法由惯性元件数据提取出误差的随机特性，得到较为准确的先验信息，避免了实际应用Kalman滤波时繁琐的调试。
英文摘要：
Exact prior information is of great importance to both classical Kalman filtering and adaptive filte- ring. In applications concerned with Kalman filtering, prior model is generally determined arbitrarily and experien- tially, lacking methodology. Taking the GNSS/INS integrated navigation as an example, the stochastic character of errors, which is subsequently transformed into proper prior information, is obtained from inertial data based on time-frequency analysis. This method avoids the complicated tuning in utilizing Kalman filtering.
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