Fusion Algorithm of Self-adaptive Cubature Kalman Smoothing of Multi-sensor
نویسندگان
چکیده
Aiming at drunk-driving test system of traditional single-point automobile which has neglected the influence of flow of in-car airflow on test precision and accuracy, this paper puts forwards in-car drunkdriving measurement and control method that is based on fusion technology of multi-sensors by exploration. Based on information fusion algorithm of D-S proof theory design, main hardware system and working mode of drunk-driving measurement and control system has been designed; scheme design of automobile drunk-driving test and control system that is based on multi-sensor test has been completed. When system model of cubature Kalman smoothing is instable or abnormal, smoothing divergency will occur. In order to solve this problem, fusion algorithm of self-adaptive cubature Kalman smoothing is put forwarded. Noise system statistical estimator has been designed to carry out on-line real-time estimation about statistical characteristics of noise; smoothing process shall be modified by adopting modified function when measurement is abnormal, so that precision of smoothing estimation and suppression ability for smoothing divergency are both improved.
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