摘要
针对使用常规的基于能量累积最大化的动态规划算法累积能量时效果较差的缺点,结合已有的动态规划算法,提出一种新的基于状态稳定性的动态规划能量累积算法。该算法根据目标运动时灰度值的稳定性和运动轨迹的连续性,分别计算能量稳定概率和方向稳定概率;采用信息融合的思想计算出状态稳定概率;累积状态稳定概率最大的候选累积点的能量。实验结果表明,算法较好的解决了目标能量累积时的能量扩散问题,目标信噪比为2.5时能量扩散区域减少10倍;在累积5帧,目标信噪比小于2.5时,仍能稳定地使信噪比提高1.5倍;使用阈值分离目标时虚警点个数平均减少10倍以上。
In allusion to the flaws of general dynamic programming algorithm with maximizing energy, a new improved method with the most steady states is proposed based on the previous methods. Considering the stabilization of the gray of the targets and the continuity of the movement trajectories, probabilities of the energy stabilization and direction stabilization are computed respectively. Probability of state stabilization is computed with information fusion and energy of candidate point whose stabilization probability is most is accumulated. Simulation results show that the proposed algorithm can well solve the energy scattering problem. The area of energy scattering is decreased by 10 times when targets＇ SNR is 2.5. Targets＇ SNR can be increased stably to 1.5 times when the number of accumulation frames is 5 and the Targets＇ SNR is 2.5. The number of false alarm points is decreased by more than 10 times when the targets are separated by threshold.
出处
《光电工程》
EI
CAS
CSCD
北大核心
2008年第5期23-27,84,共6页
Opto-Electronic Engineering
基金
航空支撑基金(05c52007)
关键词
小目标检测
动态规划
状态稳定
能量累积
small target detection
dynamic programming
state stabilization
energy accumulation
