Image matching plays an important role in feature tracking, object recognition, stereo matching, digital photogrammetry, remote sensing, and computer vision. Imperialist competitive algorithm (ICA) is inspired by imperialistic competition mechanism. In this paper, we present a novel template matching method based on chaotic ICA. Based on the introduction of the principle of ICA, the correlation function used in this approach is proposed. The chaos can improve the global convergence of ICA, and the phenomena of falling into local best solution can be prevented. The detailed process for chaotic ICA-based template matching is also presented in detail. The three typical comparative results show that our proposed chaotic ICA image matching approach is more efficient and effective than the basic ICA.

The main goal of flight clearance is to use the structured singular value (μ) analysis of the flight control system when some parameters in the system vary in a certain range. As the μ -analysis can only be done on a linear fractional transformation (LFT) model, the first step of flight clearance is to generate the LFT model of the flight control system. In this paper, based on the introduction of basic theory of LFT and μ -analysis, an X-fighter is chosen as an example to utilize the proposed methods. In order to realize the flight clearance process automatically, a novel software package based on MATLAB programming language is developed. The results of simulation experiments validate the feasibility and effectiveness of the novel methods proposed in this paper.

A novel type of Ant Colony Algorithm (ACA) for the globally optimal trajectory planning of Unmanned Aerial Vehicle (UAV) is proposed in this paper. The parallelism and positive feedback of ACA is feasible in UAV trajectory planning under complex environments, but the basic ACA model has the limitation of stagnation, and easy to fall into local optimum. Hybrid improvement strategies for the basic ACA model are proposed in this paper, and a type of trajectory smoothing scheme is also put forward. Simulation results show that the improved ACA is effective and can be used in the real-time trajectory planning of UAV. It has also been verified that the proposed method has better performance in convergence speed, solution variation, dynamic convergence behavior, and computational efficiency than the UAV trajectory planning method based on the basic ACA model under complex environments.