Dynamic Compensation of Micro-silicon AccelerometersBased on Error Whitening and Kalman Filtering
JIANG Nai-Song1,2,LIU Qing1,2
1. School of Computer Science and Technology, Nanjing Normal University, Nanjing, Jiangsu 210098, China
2. Jiangsu Research Center of Information Security & Confidentical Engineering, Nanjing, Jiangsu 210098, China
Abstract：A dynamic compensator of micro-silicon accelerometer can be modeled with model reference and system identification.The compensator has severely noisy input/output by measurement noise and frequency response of compensator.Conventional techniques based on the mean squared-error criterion can at best provide a biased parameter estimate of the unknown system being modeled with noisy input/output.The output of compensator has severely distortion and noisy disturbance by biased parameter and widened frequency band. A new approach to solve the problem of compensator parameter estimation and noisy disturbance is proposed.With this approach,the parameter of the compensator is optimized by the error whitening criterion,according to the measurement data of the step response of the sensor and reference model. At the same time, Kalman filter is constructed with reference mode for eliminating the high frequency effects.
［1］Wu D H, Huang S L, Zhao W, et al. Infrared thermometer sensor dynamic error compensation using Hammerstein neural network［J］.Sensors and Actuators A,2009,149(3):152–158.
［2］Yu D H,Liu F,Lai P Y.Nonlinear dynamic compensation of sensors using inverse-model-based neural network［J］.IEEE Trans Instrum Meas,2008,57(10):2364–2376.
［3］Schoen M P.Dynamic compensation of intelligent sensors［J］.IEEE Trans Instrum Meas,2007,56(5):1992-2001.
［4］刘清,曹国华.基于微粒群算法优化的微硅加速度传感器动态补偿研究［J］.仪器仪表学报,2006,27(12):1707-1710.
［5］Jafaripanah M,Al-Hashimi B,White N M.Application of analog adaptive filters for dynamic sensor compensation［J］.IEEE Trans Instrum Meas,2005,54(1):245-251.
［6］Ferdousi F,Connie A T,Sharmin M,et al. System identification at an extremely low SNR using energy density in DCT domain［J］.IEEE Signal Processing Letters,2005,12(4):289-292.
［7］Feng D Z,Zheng W X. Bilinear equation method for unbiased identification of linear FIR systems in the presence of input and output noises［J］. Signal Processing,2007,87(5):1147–1155.
［8］Suzuki H,Sugie T. System identification based on quantized I/O data corrupted with noises and its performance improvement［C］//45th IEEE Conference Decision and Control,San Diego,CA,2006.
［9］Rao Y N,Erdogmus D,Principe J C. Error whitening criterion for adaptive filtering:theory and Algorithms［J］.IEEE Trans Signal Proces,2005,53(3):1057–1069.
［10］Rao Y N,Erdogmus D,Rao G Y,et al. Fast error whitening algorithms for system identification and control with noisy data［J］.Neurocomputing,2005,69(1-3):158-181.
2012, Vol. 33 
