关键词: 卡尔曼滤波, 状态空间模型, 连续性抽样调查, 样本轮换

Abstract: According to how to improve the precision of successive data under successive sampling survey, this paper uses the time series theory. State-space model under successive survey is constructed on the basis of repeated sample and rotation sample and the estimators about population total are presented through these methods of Kalman filter analysis. These estimators would be more precise because more bypassed information can be used through state-space model and the estimation of Kalman filter. Therefore, the precision of estimation under successive sampling survey would be improved further more.

Key words: Kalman Filter, State-space Model, Successive Sampling Survey, Sample Rotation