文件名称:55953tbd算法动态规划实现
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复杂环境中的微弱目标(如隐身飞机、被地/海/城市杂波淹没的目标等)探测
问题是现代雷达面临的严峻挑战。 与传统的先检测后跟踪( DBT) 技术相比, 检
测前跟踪(TBD)技术是一种新兴的先进信号处理技术,它通过多帧回波数据积
累和联合处理,可以显著提高雷达的微弱目标检测跟踪性能, 是国际雷达界研究
的前沿热点。 TBD 作为一项正在发展中的新技术,还需要解决一些新的技术问题,
例如, 多目标跟踪维数灾难、临近目标相互干扰等,以及处理难度增加和运算量
增大带来的新问题。(The detection and tracking of low observable targets (e.g. stealth targets, targets
buried in strong clutter) in complex environment are great challenges for modern radar
systems. Different from the traditional detect-before-track (DBT) methods,
Track-before-detect (TBD) is a novel and efficient signal processing method which is
proposed in recent years to detect low observable targets, and has got much attention
internationally in radar research area. By jointly processing several data frames, TBD is
able to produce more reliable detection and tracking results. As a developing new
technique, TBD has its own problems and challenges. For example, existing studies on)
问题是现代雷达面临的严峻挑战。 与传统的先检测后跟踪( DBT) 技术相比, 检
测前跟踪(TBD)技术是一种新兴的先进信号处理技术,它通过多帧回波数据积
累和联合处理,可以显著提高雷达的微弱目标检测跟踪性能, 是国际雷达界研究
的前沿热点。 TBD 作为一项正在发展中的新技术,还需要解决一些新的技术问题,
例如, 多目标跟踪维数灾难、临近目标相互干扰等,以及处理难度增加和运算量
增大带来的新问题。(The detection and tracking of low observable targets (e.g. stealth targets, targets
buried in strong clutter) in complex environment are great challenges for modern radar
systems. Different from the traditional detect-before-track (DBT) methods,
Track-before-detect (TBD) is a novel and efficient signal processing method which is
proposed in recent years to detect low observable targets, and has got much attention
internationally in radar research area. By jointly processing several data frames, TBD is
able to produce more reliable detection and tracking results. As a developing new
technique, TBD has its own problems and challenges. For example, existing studies on)
相关搜索: TBD_Viterbi
(系统自动生成,下载前可以参看下载内容)
下载文件列表
文件名 | 大小 | 更新时间 |
---|---|---|
TBD_Viterbi\BackgroundNoise.m | 462 | 2014-03-09 |
TBD_Viterbi\DPTBD_SingleTarget.m | 13571 | 2014-03-19 |
TBD_Viterbi\DPTBD_SingleTarget_complete.m | 9173 | 2014-03-25 |
TBD_Viterbi\KalmanFilter.m | 414 | 2014-03-25 |
TBD_Viterbi\ProduceMeasurement.m | 1993 | 2014-03-25 |
TBD_Viterbi\sample_gaussian.m | 469 | 2014-03-04 |
TBD_Viterbi\StatePrediction.m | 529 | 2014-03-16 |
TBD_Viterbi\TBD_Viterbi.m | 5558 | 2014-03-09 |
TBD_Viterbi\test.m | 1788 | 2014-03-25 |
TBD_Viterbi\test2.m | 4 | 2014-03-25 |
TBD_Viterbi\WhiteGaussian.asv | 358 | 2014-03-07 |
TBD_Viterbi\WhiteGaussian.m | 149 | 2014-03-07 |
TBD_Viterbi\数据结构图.vsd | 77824 | 2014-03-11 |
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