复杂背景下低信噪比点目标的实时检测算法及实现

为检测复杂背景中的低信噪比 (SNR)点目标 ,提出了一种局部自适应门限检测算法。该算法以低通滤波算法估计背景中的低频成分 ,及图像局部方差估计背景起伏 ,来计算出局部自适应的目标检测判决门限。该算法充分考虑了可实现性和实时性并采用现场可编程门阵列 (FPGA)设计实现该算法。理论分析和试验结果都表明 ,该算法可有效抑制云层、树木、地物等背景杂波、检测出复杂背景下的低信噪比点目标 ,具有恒虚警率和易于工程实现的优点。

A Real-Time Detection Algorithm for Low SNR Point Targets in a Complex Background

In order to detect low SNR point targets under a complex background, this paper presents a local adaptive threshold detection algorithm. The algorithm adopts low pass filter to estimate the background and calculates the standard deviation to estimate the fluctuation of background to get the local adaptive detection threshold. With implementation fully taken into consideration, the algorithm is implemented by adopting FPGA. Experimental results have proved that the algorithm can depress clutters effectively and detect low SNR point targets under a complex background. It features a CFAR and is easy to implement.