A modified algorithm for maneuvering target based on current statistical model algorithm

摘要：

In order to overcome the greater error of Kalman filtering algorithm in tracking non-maneuvering and weak maneuvering targets using current statistical model, a modified algorithm of acceleration variance adaptively adjusting is proposed based on further research on current statistical model. Adopting maneuver detection, the maneuver states of targets are divided into strong maneuver and weak maneuver using the statistical distance of observation residuals, acceleration variance is adjusted using modified rayleigh distribution for strong maneuver and deviation of velocity estimation and forecast for weak maneuver. The match between maneuvering model and system model is improved by using modified algorithm. The capacity of tracking strong maneuvering target is enhanced and good performance of tracking weak maneuvering target is maintained. The simulation results show that the modified algorithm has good capacity of maneuvering adaptation and good performance on tracking maneuvering target. Performance on tracking non-maneuvering and weak maneuvering targets is improved contrasted with the current statistical model conventional algorithms.

关键词： current statistical model strong tracking maneuvering target adaptive filtering

作者: LIU Wang-sheng LI Ya-an

作者单位: College of Marine, Northwestern Polytechnical University, Xian 710072, Shaanxi, China

会议类型: 国际会议

会议名称: 2010 International Conference on Digital Manufacturing and Automation(2010 数字制造与自动化国际会议 ICDMA 2010)

会议地点: 长沙

会议语种:英文

页码: 46-49

在线出版日期: 2010-12-18（万方平台首次上网日期，不代表论文的发表时间）