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Abstract. UAV is increasingly popular in the field of military, civil and scientific research, since its low loss, strong adaptability and high mobility. This paper introduces the design and implement of the visual tracking system based on the rotor UAV, and gives the UAV a function of continuous and stable tracking of the ground target. Based on the standard Mean Shift algorithm, we introduce the improved object tracking algorithm with the spatial histogram and scale estimation. The robustness to scale adaptive and background related interference is improved with the enhanced tracking algorithm. It is finally implemented in our image processing board with TMS320C6657 and ZYNQ 7020. The whole system is optimized and accelerated by both of the two core of DSP. We finally achieve the real-time tracking and monitoring of the ground target in the range of 100m ~ 1km.

Star sensor is a device that uses astronomical information for navigation and attitude measurement. It is widely used in satellites, intercontinental missiles, strategic bombers and other scenarios. Since star sensors are mainly used in the military field, we need a fast, robust and high accuracy star identification algorithm. In order to improve the performance of the star sensor, this paper will use the Haar wavelet transform to obtain the multi-resolution radial features of the star image, which is matched according to the resolution from low to high. The algorithm is implemented in a pipelined manner on the FPGA platform. Experiments show that the star identification rate of the scheme reaches 98% or more when the star position error is within 3 pixels, and the worst case time consuming is only 1.4 millisecond when the FPGA runs at 100 MHZ. Compared with the traditional algorithm, this is a more robust and real-time star identification algorithm.