火力与指挥控制2011，Vol.36Issue(3)：98-100,114,4.
基于最小二乘支持向量机的测控数据融合
Research on Fusion of Measurement and Control Data Based on Least Square-Support Vector Machine
摘要
Abstract
A least square-support vector machine data fusion approach for GPS and radar system's joint observation of maneuvering target tracking was presented. After time registration, the measurements from GPS would keep synchronous with the radar measurements, then the steps of sensor registration,coordinate conversion and Kalman filtering were taken. The processed data were then transmitted to the synchronous LS-SVM fusion center as the input data, the output data were considered as the estimated coordinates of the target. Simulation results showed that this algorithm is effective to improve the processed data's precision and stability on the whole, with less amount of training samples than neural network algorithm.关键词
最小二乘支持向量机/测控/数据融合Key words
Least square-support vector machine/,target tracking/data fusion分类
信息技术与安全科学引用本文复制引用
苏思,姜礼平,邹明..基于最小二乘支持向量机的测控数据融合[J].火力与指挥控制,2011,36(3):98-100,114,4.基金项目
海军工程大学科研基金资助课题(hjsk200805) （hjsk200805）
