Quantum genetic search algorithm based on range image of laser radar

Quantum evolutionary learning algorithm is a kind of fast algorithm which search the optimal solution of functions, with the help of Quantum thinking, this kind of algorithm has a high degree of parallelism, and the nature of fast speed. In this paper a frame work of quantum genetic search which is based on laser lidar image, in this frame work, a method of image quantum formulation is proposed, a wave function is used to describe the solution space to be searched, which makes the operand transformed from determined points to the whole solution space. Besides, an unequal probability initialization is shown in this paper, which solves the problem of misconvergence in the general initializations. What is more, an adaptive quantum rotary gate is designed to accelerate the convergence of the algorithm, which is adjusted automatically with the evolutional generation and fitness. The frame work given in this paper was applied in the target searching of streak tube imaging lidar, and shows rapid convergence and high stability with the premise of high-precision.