CAJ | 학술논문

针对概率框架下的航迹航路相关不能有效处理低信噪比跟踪系统中存在的高冲突以及不确定性的问题，考虑到证据推理在度量、处理不确定和高冲突信息的独特优势，提出了在证据推理框架下的航路目标分类算法。为了实现对空中伪装航路目标的识别，提出了一种基于动态证据推理的航迹航路相关算法，并完成相关的仿真验证。针对低信噪比下的雷达跟踪系统进行仿真验证，结果表明，该算法实现了对航迹目标的属性识别，并有效地完成了对异常航路的目标的检测和识别。
침대개솔광가하적항적항로상관불능유효처리저신조비근종계통중존재적고충돌이급불학정성적문제，고필도증거추리재도량、처리불학정화고충돌신식적독특우세，제출료재증거추리광가하적항로목표분류산법。위료실현대공중위장항로목표적식별，제출료일충기우동태증거추리적항적항로상관산법，병완성상관적방진험증。침대저신조비하적뢰체근종계통진행방진험증，결과표명，해산법실현료대항적목표적속성식별，병유효지완성료대이상항로적목표적검측화식별。
Because of the uncertain and high conflict information caused by the low SNR in a tracking system, the previous air target to airline association algorithm in probabilistic framework can't deal with these issues effectively. Considering the special advantage of evidence reasoning in the measurement and combination of uncertain and high conflict information, a classification algorithm in the evidence reasoning framework is proposed. For identifying the abnormal airline targets, a novel air target to airline association algorithm based on dynamic evidence theory is proposed. For radar tracking system with low SNR, this algorithm is adopted to achieve the track classification and the detection of abnormal airline targets. The results show that the algorithm under the framework of dynamic evidence reasoning can deal with the track classification and the detection of abnormal targets effectively.