摘要
为了检测低信噪比下的红外弱小目标,本文将方向中值滤波与分层动态规划算法相结合进行检测前跟踪。利用背景杂波在局部空间上的相关性,提取目标在四个方向的中值进行自适应加权滤波,抑制结构性杂波分量,改善信噪比。针对分割后的备选目标点,为了减少跟踪检测的计算量,根据真实目标运动轨迹的连续性与光滑性,利用分层动态规划算法进行多帧检测,进而对多层检测结果进行配准并做出决策。仿真实验表明方向中值滤波有效的提高了信噪比,分层动态规划算法进一步降低了虚警概率,同时大大提升了计算速度。
In order to detect infrared dim targets in low Signal-to-noise Ratio （SNR） background, an adaptive Track-before-detect （TBD） algorithm based on Directional Median Value Filtering （DMVF） and Layered Dynamic Programming （LDP） was proposed. The structure clutter was suppressed using four adaptive Weighted Directional Median Values （WDMV） on the ground of its correlation in the local neighbor. For the out-threshold potential targets, the LDP was implemented for multiframe detection through the continuity and smooth of the trajectories in order to reduce the computation complexity. As to the matching the trajectories detected in every layer, a decision was made. The simulated experiments show that the SNR is effectively improved by DMVF, and LDP reduces the false detection probability and greatly improves the operation speed.
出处
《光电工程》
CAS
CSCD
北大核心
2008年第11期18-23,共6页
Opto-Electronic Engineering
关键词
分层动态规划
红外目标
杂波抑制
方向中值滤波
layered dynamic programming
infrared target
clutter suppression
directional median value filtering
