摘要
低信杂噪比环境中对弱小目标的检测,已经在信号处理、红外图像序列检测等领域中引起人们的广泛关注。动态规划实际上是一个多阶段决策的优化问题,它是检测前跟踪(TBD)处理过程中提出的一种有效检测弱小运动目标的方法。该文分析了动态规划算法进行弱小目标检测的机理,在此基础上对两类动态规划算法进行了革新,并给出了一个统一的递推关系式。仿真结果表明此算法对弱小目标具有较强的检测能力,比一般的弱目标的检测方法SNR性能上约提高3～5dB。
An important problem in the field of signal processing, sequence of infrared image detection which arouses people's attention widely is the detection and tracking of dim moving targets in very low Signal-to-Noise Ratio (SNR) or signal-to-clutter ratio environment. In fact, dynamic programming is a problem of multi-stage decision, and Dynamic Programming Algorithm (DPA) is an effective approach which was adopted during the process of Track-Before-Detect(TBD). In current work, the mechanism of dynamic programming algorithm is analyzed, and a number of technical innovations that improve the performance of DPA are presented. Simulation results show this approach has high ability of detection for dim moving targets, and achieves 3-5dB SNR gains comparable to those of other detection algorithms.
出处
《电子与信息学报》
EI
CSCD
北大核心
2003年第6期721-727,共7页
Journal of Electronics & Information Technology
基金
国家部级资助项目(No:413070301)
