CAJ | 학술논문

针对超高速、超强机动等特定目标的探测和跟踪问题，雷达等传统传感器的量测值少，难于获得有效的探测跟踪，还需要人工情报、专家库信息等异类信息，对于这些信息的配准融合处理尚无有效方法。基于有限集合统计学(FISST)理论，在对几种异类信息进行统一表示并给出相应的滤波处理方法基础上，提出了焦点目标的匹配概率(匹配度)作为异类信息配准指标，并采用卡尔曼证据滤波方法进行计算。最后给出了仿真实例，验证了方法的有效性和可行性。
침대초고속、초강궤동등특정목표적탐측화근종문제，뢰체등전통전감기적량측치소，난우획득유효적탐측근종，환수요인공정보、전가고신식등이류신식，대우저사신식적배준융합처리상무유효방법。기우유한집합통계학(FISST)이론，재대궤충이류신식진행통일표시병급출상응적려파처리방법기출상，제출료초점목표적필배개솔(필배도)작위이류신식배준지표，병채용잡이만증거려파방법진행계산。최후급출료방진실례，험증료방법적유효성화가행성。
It is hard to detect and track special targets with super high-speed and super strong-maneuverability efficiently, only by traditional sensors such as radar. Therefore, intelligence information and expertise base etc. should be needed. Nevertheless, there are no practicable means for the management of multi-source heterogeneous information registration. The characteristics of special targets are introduced and analyzed firstly. Some kinds of heterogeneous information are expressed in Finite-Set Statistics(FISST) theory and some corresponding filtering algorithms are put forward. The matching probability of focused targets is taken as the registration index of heterogeneous information, and the results are computed with Kalman evidence filter. Numerical simulation validates the feasibility of the proposed method.