基于高阶统计量滤波器的离子浓度信号测量  

Measurement for Ion Concentration Signal Based on High-Order Statistics Filter

作　　者：周安然[1] 杨光永[1,2] 吴海锋[1] 赵锦剑 朱芹[1] 

机构地区：[1]云南民族大学电气信息工程学院,云南昆明650500 [2]华南理工大学机械与汽车工程学院,广东广州510640

出　　处：《仪表技术与传感器》2014年第12期121-123,共3页Instrument Technique and Sensor

基　　金：国家自然科学基金课题(61262091);无线传感器网络云南省高校重点实验室开放基金(ZK2011002);云南民族大学研究生创新项目(2013YCX01)

摘　　要：使用选择性离子电极测量水质分析样品中的离子浓度时,由于溶液中各种离子的相互作用,使信号不可避免地混入超高斯噪声和亚高斯噪声。为了提高离子浓度信号的信噪比和测量精度,采用基于四阶累积量均方误差准则的高阶统计量自适应滤波器(HOSRLS),以抑制离子浓度信号的超高斯噪声和亚高斯噪声。仿真结果表明:较之于低阶统计量的递归最小均方误差自适应滤波器(RLS)方法,HOSRLS方法可有效地消除离子浓度信号的非高斯噪声分量,具有较高的信噪比和收敛速度。When selective ion electrodes are used to measure the ion concentration of samples for analyzing water quality, the output signals are inevitably contaminated with super-Gaussian and sub-Gaussian noise components because of the output signals are inevitably contaminated with super-Gaussian and sub-Gaussian noise components with the interactions of various ions in solu- tion. To improve the SNR and measurement accuracy of ion concentration signal,higher order statistics recursive adaptive filter with least mean square error criterion（HOSRLS） of fourth-order cumulates was implemented to reduce or cancel super-Gaussian and sub-Gaussian noise. Simulation result shows that HOSRLS work well and can effectively eliminate the non-Gaussian noise compo- nent of ion concentration. Compared with the recursive adaptive filter of low-order statistics MMSE criterion, HOSRLS has higher SNR and faster speed of convergence.

关 键 词：高阶统计量 递归最小均方误差自适应滤波器 超高斯噪声 亚高斯噪声 离子浓度 选择性离子电极 

分 类 号：TN911.7[电子电信—通信与信息系统]