摘要
针对船舶动力定位的冗余测量系统,基于模糊自适应滤波和滤波器可信度的模糊评判,建立了多传感器数据融合算法。该方法与线性或非线性系统状态估计相结合,构成模糊自适应融合算法。通过监测滤波新息的均值和分歧度,应用模糊推理系统在线调节测量噪声协方差矩阵,从而抑制滤波发散;构建新的数据质量函数和子系统故障检测函数,根据检测结果自适应地选择子系统构建全局融合体系;利用子系统滤波的新息分歧度比值和状态估计误差的协方差,模糊评判各子系统滤波的可信度,由此计算相应的信息分配系数,实现全局融合。通过转台半实物仿真,验证了该算法的有效性。
Aiming at redundant measurement system of a vessel dynamic positioning, based on the fuzzy adaptive filtering and the fuzzy judgement of credibility of filter, a multi-sensor data fusion algorithm is proposed. Combining with the state estimates of linear system or nonlinear system, a fuzzy adaptive fusion algorithm is built. By monitoring the mean and the degree of divergence （ DoD ） of innovation information of a filter, the measurement noise eovarianee matrix is adjusted online by fuzzy reasoning system, and divergence of filtering is suppressed. Data quality control function and fault detection function of subsystems are built. According to the detection results, subsystems are selected adaptively to construct global fusion system. Utilizing the parameter DoD and the estimation error covariance, the credibility of a sub system filtering is evaluated by a fuzzy inference system, and weighted factors are calculated for the global fusion. The semi-physical simulation result indicates the effectiveness of the proposed algorithm.
出处
《传感器与微系统》
CSCD
北大核心
2012年第7期130-134,共5页
Transducer and Microsystem Technologies
基金
国家自然科学基金资助项目(50979017)
中央高校基本科研业务费专项资金引进优秀人才项目(HEUCFR1118)
关键词
数据融合
模糊推理系统
可信度
自适应滤波
data fusion
fuzzy reasoning system
credibility
adaptive filtering
