CAJ | 학술논문

针对被动传感器采样非周期且采样数据缺乏距离信息等特点，提出了一种用于解决目标航迹与传感器量测相关联的模糊综合贴近度的数据关联算法。由于被动传感器的量测没有距离信息且传感器探测范围小，本算法首先设置两个关联波门进行量测筛选；然后采用航向确定法得出航向角信息，并综合方位角、俯仰角信息，使用模糊综合的方法进行最终的关联，以解决关联错误率高的问题；最后使用扩展卡尔曼滤波进行目标状态与协方差的更新。实验结果证明了该算法方法的有效性。
침대피동전감기채양비주기차채양수거결핍거리신식등특점，제출료일충용우해결목표항적여전감기량측상관련적모호종합첩근도적수거관련산법。유우피동전감기적량측몰유거리신식차전감기탐측범위소，본산법수선설치량개관련파문진행량측사선；연후채용항향학정법득출항향각신식，병종합방위각、부앙각신식，사용모호종합적방법진행최종적관련，이해결관련착오솔고적문제；최후사용확전잡이만려파진행목표상태여협방차적경신。실험결과증명료해산법방법적유효성。
In the passive sensor networks ,the sampling data are aperiodic and lack of distance information ,a data association algorithm is proposed based on fuzzy synthetic closeness .Because the measurements of passive sensor were lack of distance infor-mation and the detection ranges of passive sensor were small ,the algorithm used two thresholds to select the effective measure-ments;then the heading-angle was obtained by the heading-angle definition method;at last the fuzzy synthetic closeness algorithm was used for the final data association ,which combined the information of the azimuths and the elevations to resolve the problem of high error rate of association .The extended Kalman filter is used to update the target state and covariance .The experimental results show the validity of this algorithm .