背景变化鲁棒的微弱瞬态信号检测

在微弱瞬态信号检测中,由于信号完全淹没在背景和噪声中,因此当背景信号发生变化时,传统方法的检测性能会急剧降低。针对上述问题,提出一种基于核函数的对连续背景变化鲁棒的微弱瞬态信号检测方法。利用核函数将信号映射到一个高维空间来解决在原始空间中线性不可分的问题。根据信号和噪声特性对核函数加以约束,使检测方法在能检测出瞬态信号的同时还具有对连续背景变化鲁棒特性。将该方法应用于基于高帧频图像序列的微弱运动点目标检测中,实验证明该方法无论是在稳定背景情况下,还是背景连续变换情况下, 相比传统方法都有更好的检测结果,在背景连续变换的情况下优势更加明显。

Robust detection of weak transient signals with changing background

In the detection of a weak transient signal, the signal is completely submerged in the noise, so the detection performance of traditional methods will be dramatically deteriorated when the background changes. To solve this problem, a new weak transient signal based on the kernel function is proposed, which is robust to the continuous background change. The signal is mapped to a higher dimensional feature space by use of the kernel function to solve the problem that there is linear inseparability in the original space. The kernel function is constrained according to characteristics of the signal and noise, so that the detection method is robust to the continuous background change while detecting transient signals effectively. The proposed method is applied to weak moving point target detection based on the high frame rate image sequence. The experiment shows that the proposed method can obtain better detection results in both simulation data and real world data, and that the proposed method is more superior when the background is changing continuously.