Study On Automatic Target Recognition Of The TV-guided Missile

Since it appeared for the first time in World War II, the precision-guided weapons have sprung up like mushroom. Looking back over every large and small local war in the world during the past more than half a century, guided weapons were used in the ground rising rapidly. From the first appearance in World War II to be used in the Vietnam War, and then occupied a dominant position in the recent Libyan war, there seems to be a substitute for conventional trends. Although the two arms have their own characteristics and advantages, but using guidance technology in the conventional weapons will be an inevitable trend for the world's military development. Based on this background, in this article we will make a detailed analysis of the precision-guided weapons on the current world, and then do more detailed research in short-range TV-guided missiles whose representative are "Javelin" missile made by US."Javelin" is a shoulder-fired weapon for close range combats. After the missile-man aims at the goal and fired missiles, they can complete the task of target identification, tracking and attacking independently, it has achieved the true automatic target recognition. There is no relevant information on this type of TV-guided missile domestic; its difficulty mainly has three aspects:first, there will be a large view changes between images made templates stored before the missile fired and images used for template matching. It is difficult for traditional image matching algorithm to resolve this problem. Second, the missile has an ignition process before attacking down, a violent of shaking will occur in this short period, and background will have a serious interference on the target. So the image tracking algorithm must have high accuracy and speed. Third, the target will become larger and larger when the missile gets close to it, this requires the image tracking algorithm in this phase to have very strong robustness to scale changes. Moreover, in hardware designing, the size of circuit board is limited by the missile's size and weight. So we should arrange the location of the high-speed digital signal processing chip appropriately and make sure it's effectiveness. This article studied mainly based on these technical requirements and difficulty, and made the following arrangements:1. In the second chapter we will conduct a comprehensive classification and summary to precision-guided weapons in the world based on a large number of literature data domestic and abroad. Analysis of the characteristics and application environment to the various types of guided weapons will be presented in this chapter too. The last of this chapter has made an introduction to the current imaging precision guidance technology.2. The third chapter of this article is mainly to solve the problem of having large view changes in template matching for TV-guided missiles. After comparing many images matching algorithms of anti-affine transforming based on features, we propose to use an improved anti-entire affine SIFT matching algorithm to solve the view changing problem.3. We will presents a target tracking algorithm combined the statistical characteristics of Harris corners and PSO algorithm. This algorithm sets the accuracy and speed in one to meet the images'violent shaking during TV-guided missiles early tracking. At the end of this chapter, we use a set of actual combat video doing experiment to verification the timeliness and effectiveness of the proposed algorithm.5. Chapter5focused on the target's size changes during the TV-guided missile's last tracking, proposed scale adaptive tracking algorithm based on Mean-shift. The new algorithm solved the problem of mean-shift's lack to the target's criterion size changes. Experiments show that the improved algorithm is robust to scale changes and a real-time one.6. In the6th chapter of this paper, we mainly introduced the image processor based on DSP+FPGA. This chapter made a detailed introduction to the processor's principle, chips'selection and their function respectively. The biggest problem in desing this circuit board is we should not only arrange many larger electric chip in a small area but also solve the complex electromagnetic compatibility. So that it can meet the application requirements in engineering practice. At the end of this chapter we gave out the physical images of the image processor's circle board and its mounting platform flowed by many practical images in practical applications.The algorithms of target tracking based on statistical properties of harris corner and pso and mean-shift that is affine to scale changes are both simulated on a PC with VC++6.0. Both of them are meet the real time requirements and have been used in practice. Regrettably, the image matching algorithm based on SIFT should make more effort to real-time work due to its computational complexity and large amount of calculation.