| Fuzzy Rule-Based Adaptive Kalman Filter for State Estimation of Anti-Tank Threats |
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Eui-Hyuk Lee, Kyu-Gong Cho, Sang-Soon Park, Youn-Sik Kang |
| 대전차 위협체 상태추정을 위한 퍼지 규칙기반 적응적 칼만필터 |
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이의혁, 조규공, 박상순, 강윤식 |
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국방과학연구소 |
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| Abstract |
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To neutralize fast Anti-Tank Guided Missiles(ATGMs) or Anti-Tank Rockets(ATRs) projected at short ranges, the trajectories and times that the threats arrive at hard-kill systems should be predicted precisely. The trajectories of ATGMs or ATRs are almost stationary but the velocity and acceleration are very changeable in the terminal stage, so that it is needed to predict the characteristics of ATGMs and ATRs for filtering. In this paper the Fuzzy Rule based Adaptive Kalman Filter(FRAKF) is proposed to estimate the position, velocity and acceleration of the threats with accuracy and the performance of it is compared with the existing tracking filter considering the maneuvering characteristics of threats. |
| Key Words:
ATGM, ATR, Tracking, Fuzzy |
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