Research On The Qunantum Genetic Algorithm Based On The Ladar Image Searching

Imaging laser radar can get the 3D range image which reflects the spatial location of targets and the intensity image which reflects the material of targets. These images are named 4D image of target. Compared with other 2D sensors, for example, the passive infrared sensor and CCD, imaging laser radar can get more abundant information and has high spatial resolution, so it is suitable to be used to detect and recognite targets. The target searching algorithm is an important part of detrctor and identity module of imaging ladar. Because the core approach of the algorithm always works sequencely, the complexity is ptoportional with the image resolution. Especially, with the emergence of the wide field and high frame rate laser ladar, it is difficult for the traditional algorithm to meet the demand of the high accuracy and the real-time.Quantum genetic algorithm is a kind of fast optimization algorithm, which is the combination of the intelligent algorithm and the quantum thought. Becase the basic quantum concepts, for example, the superposition states, unitary quantum gates, are introduced into the process of biological evolution, the algorithm gets the highly quantum parallelism. It is one of the key to the target searching technology of he laser radarFirstly, considering the characteristics of the 4D images of imaging laser radar, this article will research and improve the quantum genetic algorithm to make it be suitable for target searching of imaging laser radar. To state the images, the article uses the wave function to state the images by random the coordinates. To find the global optimal solution fast, the article presents the proposal of unequal-probality initialization for the solution space, and improves the quantum gate which can be adjusted adaptively with the change of the evolitional generations and the fitness respectively. In addition, a series of test functions with distinctive features are designed to test the convergence of the algorithm. The feasibility of the algorithm is proved.Secondly, in this paper, the algorithm is applied into the target searching of the standard images, the simulated images of imaging ladar and the real images of imaging ladar. The success rate, convergence and the stability of the algorithm are discussed. The results show that the quantum genetic search algorithm has the feasibility of practical application. Finally, in this paper, the preliminary proposals for realizing the established quantum genetic searching algorithm are present. They are the full quantum proposal, the FPGA proposal and the CPU proposal. Contrapose to the characteristics of these proposals, the technical requirements and the reflected real-time are analyzed and discussed.