Analyse of Kalman Algorithm for Different Movement Modes of Land Mobile Object
INS and GPS information complex processing is based mainly on Kalman filtering algorithm. During navigation tasks solving (estimation of velocity and position), tracked object dynamics change occurs quite often. For these cases conventional Kalman algorithm can not be used, as it’s well known that standard Kalman algorithm estimation error increases in cases of quick changes of estimated state parameters. Different methods are being developed to overcome this drawback. The presented Kalman gain correction algorithm (KGCA) decreases estimation error that occurs, during object dynamics alterations. The modeling results of adaptive KGCA algorithm are presented and compared with conventional one. The MSE error reducing benefits for the case of adaptive algorithm use are shown as well. Ill. 9, bibl. 4 (in English; summaries in English, Russian and Lithuanian).
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