Warship Formation Recognition Algorithm Based on Hough Transform and Clustering

doi:10.3969/j.issn.1000-1093.2016.04.011

Abstract

Abstract: Formation recognition is an important research task in the area of target recognition for anti-ship missile weapon systems. Perfect formation recognition capability can improve the target selection of anti-ship missiles for compact warship formation, thus enhancing the hit probability and operational effectiveness of anti-ship missiles. The formation recognition algorithm is researched base on Hough transform, which has higher recognition rate without the influence of detection noise. If the target information is polluted badly, the improved K-means clustering algorithm is used to cluster the local peaks in an accumulation matrix. The shape parameters of formation to be recognized can be extracted from the clustering results so that the adverse influence due to detection noise is restrained effectively. Even though the target information is polluted badly, the algorithm has better recognition accuracy and robustness. The complexity of the algorithm and the effect of target designation error on the accuracy of the algorithm are analyzed. The simulation results show that the proposed algorithm has the perfect capability of formation recognition.

Key words: control and navigation technology of aerocraft, formation recognition, Hough transform, improved K-means clustering, peak clustering

CLC Number:

TP391

ZHANG Yi-fei， DONG Shou-quan， BI Kai-bo. Warship Formation Recognition Algorithm Based on Hough Transform and Clustering[J]. Acta Armamentarii, 2016, 37(4): 648-655.

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