【摘要】：本文提出了一種基于位置預(yù)測的動態(tài)規(guī)劃方法,用于快速檢測GEO帶天基觀測圖像中的暗弱碎片。首先對實測數(shù)據(jù)進行分析,得出不同GEO碎片在圖像中的運動速度相似,接著,進一步對數(shù)據(jù)做擬合,得到了GEO碎片速度和觀測衛(wèi)星星下點緯度之間的映射模型,并提出了GEO帶天基觀測圖像中碎片速度估計方法。最后,利用估計速度預(yù)測碎片位置,在傳統(tǒng)動態(tài)規(guī)劃遞歸方程中采取位置信息加權(quán),得到了基于位置預(yù)測的目標搜索范圍,從而減少了遞歸方程中的目標狀態(tài)個數(shù)。實測數(shù)據(jù)驗證了速度映射模型的擬合偏差在1pixel以內(nèi)。選取一個典型觀測周期的實測數(shù)據(jù)進行實驗,結(jié)果表明本文方法的檢測時間比傳統(tǒng)動態(tài)規(guī)劃方法減少了90%以上,虛警率降低了5.9%以上,適合于GEO帶天基觀測圖像中暗弱碎片的檢測。
[Abstract]:In this paper, a dynamic programming method based on position prediction is proposed for fast detection of dark weak debris in space-based observation images of GEO. By analyzing the measured data, it is found that the velocity of different GEO fragments in the image is similar. Then, the mapping model between the velocity of GEO fragments and the latitude of the observation satellite is obtained by further fitting the data. A method for estimating the velocity of debris in GEO space-based observation images is proposed. Finally, the estimated velocity is used to predict the debris position, and the position information is weighted in the traditional dynamic programming recursive equation, and the target search range based on the location prediction is obtained, thus reducing the number of target states in the recursive equation. The measured data verify that the fitting deviation of the velocity mapping model is within 1pixel. The experimental results show that the detection time and false alarm rate of this method are more than 90% and 5.9% less than that of the traditional dynamic programming method. It is suitable for the detection of dark weak debris in GEO space-based observation images.
【作者單位】： 北京跟蹤與通信技術(shù)研究所;
【基金】：國家高技術(shù)863計劃資助項目(No.2015AA7088061)
【分類號】：TP391.41

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