Title :
Applied research of location fingerprint positioning system based on the improved AUKF algorithm
Author :
Cao Chunping ; Chen Ping ; Wang Yagang
Author_Institution :
Sch. of Opt.-Electr. & Comput. Eng., Univ. of Shanghai for Sci. & Technol., Shanghai, China
Abstract :
Because of the signal error existing in mine personnel positioning when using location fingerprint positioning, the paper proposes self-adaptive unscented Kalman filter (Adaptive UKF, AUKF) algorithm. The filtering algorithm can actively suppress signal diverging and compensate for the signal loss brought about by the noise, and further improve the accuracy of the sample signal in location fingerprint positioning method. By associating the accurate signal positioning with the position algorithm, the system can obtain more accurate target location.
Keywords :
Kalman filters; fingerprint identification; improved AUKF algorithm; location fingerprint positioning system; position algorithm; sample signal accuracy; self-adaptive unscented Kalman filter algorithm; signal diverging suppression; signal loss compensation; Adaptive optics; Educational institutions; Electronic mail; Fingerprint recognition; Kalman filters; Optical computing; Optical filters; Adaptive Unscented Kalman Filter; location fingerprint positioning; real-time tracking;
Conference_Titel :
Control Conference (CCC), 2013 32nd Chinese
Conference_Location :
Xi´an
