Millimeter-wave Passive Imaging Weak Moving Target Detection Algorithm

Passive millimeter wave imaging(PMMW) forms images by detecting the difference radiation from the scene and targets. Compared with infrared, optical, microwave imaging, this imaging technology has unique advantages. It also has important applications in battlefield reconnaissance and scene monitoring.However, the objects radiation in millimeter band is very weak, and the space resolution is low in distance. Therefore, how to achieve dim target detection in low SNR in PMMW images is difficult. The article is meant to solve this problem.1) Measurement has been down to collect the objects and the scene's brightness temperature. Analyze the statistical characteristics of the back ground noise. Several pretreatment has been study to improve the input SNR and inhibit the background clutter.2) Contrary to traditional Dynamic Programming (DP) Algorithm performs bad in low SNR images. We research an improved DPA with adoptive threshold. This algorithm has better performance with different PMMW images.3) In order to solve the reunite effect in traditional DPA, we research a reversed detecting way to eliminate the reunite effect. Detection performance has been improved. And lead into Extreme Value Theory (EVT) to analyze the performance of DPA. The detection probability has been computed.4) As the requirements for real-time, we lead into a state stabilization dynamic programming algorithm. This algorithm can reduce the input SNR significantly. It also eliminates the reunite effect. And its compute amount is less than traditional DPA.The above algorithm has been simulated, the result shows that the improved DPA has better detection performance in low SNR PMMW images.