红外运动小目标的检测,对提高红外成像系统的作用距离,具有重要意义。文中对先检测后跟踪(De-tect Before Track,DBT)和先跟踪后检测(Track Before Detect,TBD)两类红外运动小目标检测方法进行了对比,指出两类方法在目标检测中的适用场...红外运动小目标的检测,对提高红外成像系统的作用距离,具有重要意义。文中对先检测后跟踪(De-tect Before Track,DBT)和先跟踪后检测(Track Before Detect,TBD)两类红外运动小目标检测方法进行了对比,指出两类方法在目标检测中的适用场合。同时对红外目标检测领域存在的问题进行深入分析,最后指出了该领域可以深入研究的方向,以供后续开展红外目标跟踪与识别工作作为参考。展开更多
Dim target detection from sea clutter is one of the difficult topics in ocean remote sensing application. By aiming at the shortcoming of false alarms when using track before detect （TBD） based on dynamic programmin...Dim target detection from sea clutter is one of the difficult topics in ocean remote sensing application. By aiming at the shortcoming of false alarms when using track before detect （TBD） based on dynamic programming, a new discrimination method called statistics of direction histogram （SDH） is proposed, which is based on different features of trajectories between the true target and false one. Moreover, a new series of discrimination schemes of SDH and Local Extreme Value method （LEV） are studied and applied to simulate the actually measured radar data. The results show that the given discrimination is effective to reduce false alarms during dim targets detection.展开更多
文摘红外运动小目标的检测,对提高红外成像系统的作用距离,具有重要意义。文中对先检测后跟踪(De-tect Before Track,DBT)和先跟踪后检测(Track Before Detect,TBD)两类红外运动小目标检测方法进行了对比,指出两类方法在目标检测中的适用场合。同时对红外目标检测领域存在的问题进行深入分析,最后指出了该领域可以深入研究的方向,以供后续开展红外目标跟踪与识别工作作为参考。
基金supported by the National Natural Science Foundation of China(Grant No.61001137)the Pre-Research Foundation(Grant No.9140A07020311HK0116)
文摘Dim target detection from sea clutter is one of the difficult topics in ocean remote sensing application. By aiming at the shortcoming of false alarms when using track before detect （TBD） based on dynamic programming, a new discrimination method called statistics of direction histogram （SDH） is proposed, which is based on different features of trajectories between the true target and false one. Moreover, a new series of discrimination schemes of SDH and Local Extreme Value method （LEV） are studied and applied to simulate the actually measured radar data. The results show that the given discrimination is effective to reduce false alarms during dim targets detection.
