Finite Truncation Based On Adaptive Genetic Algorithm And Its Application In Autonomous Navigation

As the most similar astronomical with the Earth in the solar system, Mars exploration has been an important goal of deep space exploration. Image captured by Mars detector is an important way to obtain information of the planet’s surface. Information that extracted from the image is directly related to the stability of the detector and accuracy of navigation. Due to limitations of spaceborne computer performance, the speed of image processing is one of the major bottlenecks that affect real-time navigation. It often takes the landing detector a long time in extraction and matching of feature points, estimation of fundamental matrix and motion estimation of detector parameters, which brings significant time delay to the navigation system. The amount of data information received in navigation is not only huge, but also requires a high level of timeliness in data processing. Big data analysis and processing technology makes major challenges to statistical discipline. For large data, we can purposeful design and analysis by modern computer technology and innovative statistical methods, and then get the value of data. For meeting autonomy and real-time requirements in navigation, this dissertation finds a more rapid and effective truncation algorithm to improve computational efficiency by studying large linear equations, with the support of 973 sub-project(Feature Extraction and Tracking and Fast Motion Estimation Method of the planet’s surface). The main contents are as follows:(1)This thesis introduces an improved genetic algorithm against premature convergence and slow convergence in the traditional genetic algorithm-adaptive genetic algorithm. And this paper applies the adaptive genetic algorithm to function optimization problems, The numerical experiment represents that the adaptive genetic algorithm is superior than the traditional genetic algorithm in convergence speed and accuracy.(2) Combined with fast convergence of adaptive genetic algorithm, this thesis proposes a finite truncation based on adaptive genetic algorithm. Experiments show that the finite truncation based on adaptive genetic algorithm has superiority in time.(3) This thesis applies the finite truncation based on adaptive genetic algorithm into horizontal velocity estimation of detector, on one hand, the new algorithm can reduce the extent of ill coefficient matrix, which makes the solution more stable, on the other hand it can improve computing efficiency by shortening the estimated time of relative attitude of the detector and then provides plenty of time to the avoidance of Mars and selecting the landing site in follow-up process.