TY - JOUR
T1 - Intelligent tracking algorithm for manoeuvering target using Kalman filter with fuzzy gain
AU - Noh, S. Y.
AU - Park, J. B.
AU - Joo, Y. H.
PY - 2007
Y1 - 2007
N2 - An intelligent filter with fuzzy gain is proposed, which calculates a manoeuver input into the time-varying variance of the overall process noise and compensates an estimation error by using a fuzzy gain. The proposed technique not necessary to predesign the acceleration levels according to the target manoeuver properities. The manoeuver input is esitmated using the difference between the non-manoeuvering filter and the manoeuvering one. To compensate the estimation error, the fuzzy gain is used to describe the relationship between the filter residual and its variation. A fuzzy system is utilised for an universal approximator. It is optimised by using a genetic algorithm. A computer simulations show that the effectiveness of the proposed method is compared with multiple filters.
AB - An intelligent filter with fuzzy gain is proposed, which calculates a manoeuver input into the time-varying variance of the overall process noise and compensates an estimation error by using a fuzzy gain. The proposed technique not necessary to predesign the acceleration levels according to the target manoeuver properities. The manoeuver input is esitmated using the difference between the non-manoeuvering filter and the manoeuvering one. To compensate the estimation error, the fuzzy gain is used to describe the relationship between the filter residual and its variation. A fuzzy system is utilised for an universal approximator. It is optimised by using a genetic algorithm. A computer simulations show that the effectiveness of the proposed method is compared with multiple filters.
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U2 - 10.1049/iet-rsn:20060030
DO - 10.1049/iet-rsn:20060030
M3 - Article
AN - SCOPUS:34250674359
SN - 1751-8784
VL - 1
SP - 241
EP - 247
JO - IET Radar, Sonar and Navigation
JF - IET Radar, Sonar and Navigation
IS - 3
ER -