基于局部梯度强度图的动态规划检测前跟踪算法

Dynamic Programming Track-Before-Detect Algorithm Based on Local Gradient and Intensity Map

针对传统动态规划检测前跟踪(DP-TBD)算法在背景复杂度高且信噪比低的红外弱小目标图像中检测概率低的问题,提出了一种基于局部梯度强度图的动态规划检测前跟踪(LIG-DP-TBD)算法。该算法首先采用局部梯度强度算法(LIG)对帧序列图像进行预处理,从而得到一个新的量测模型;再根据相邻帧值函数的相关性,构造一种全新的值函数;利用动态规划检测前跟踪算法(DP-TBD)对新的值函数进行多帧积累,从而实现对弱小目标的检测前跟踪。蒙特卡洛仿真实验结果表明,在信噪比低于4dB的情况下,该算法的检测概率较传统DP-TBD算法和DBT算法相比提高了约10%。同时,在背景复杂的真实红外弱小目标序列图像中,该算法可以在恒定虚警率条件下有效地进行弱小目标的检测前跟踪,提高了目标的检测概率。

Aiming at the low detection probability of traditional DP-TBD algorithm in the infrared weak and small targets images with high background complexity and low SNR,a dynamic programming track-before-detect algorithm based on local gradient and intensity map is proposed.Firstly,the algorithm uses the local gradient and intensity algorithm(LIG)to preprocess the frame sequence images to obtain a new measurement model.Then,a new value function is constructed according to the correlation of the value function of adjacent frames.Finally,the DP-TBD is used to accumulate the new value function in multiple frames,so as to realize the track-before-detect of small and weak targets.Monte Carlo simulation experiment results show that when the signal-to-noise ratio is lower than 4dB,the detection probability of this algorithm is about 10%higher than that of the traditional DP-TBD algorithm and DBT algorithm.At the same time,in the real infrared weak and small target sequence image with complex background,the algorithm can also effectively track the target before detection under the condition of a constant false alarm rate,which improves the detection probability of the target.