A method with high detection rate, low false-alarm rate, and low computational cost is presented for removing stars and noise and detecting space debris with signal-to-noise ratio (SNR>3) in consecutive raw frames. The top-hat transformation is implemented firstly to remove background, then a masking technique is proposed to remove stars, and finally, a weighted algorithm is used to detect the pieces of space debris. The simulation samples are images taken by 600 mm ground-based telescope. And a series of simulation targets are added to the image in order to test the detection rate and false-alarm rate of different SNRs. The telescope in this paper is worked in “staring target mode.” The experimental results show that the proposed method can detect space debris effectively with low false-alarm by only three frames. When the SNR is higher than 3, the detection probability can reach 94%, and the false-alarm rate is below 2%. The running time of this algorithm is within 1 second. Additionally, algorithm performance tests in different regions are also carried out. A large set of image sequences are tested, which proves the stableness and effectiveness of the proposed method.

The star identification (star-ID) algorithm can match the stars captured by an optical system with a star catalog according to certain features. Star-ID has been an important research issue in many astronomical studies and a strong robust star-ID algorithm can effectively identify a certain number of stars as a standard source to correct uncalibrated telescopes. Generally, before star-ID, the celestial coordinates should be translated into the image coordinates with knowledge of optical center coordinates, image rotation angle, focal length of optical system, image sensor's pixel size and so on. For an uncalibrated telescope, the star-ID performance usually suffers from the errors or even the lack of these parameters. In this paper, a novel star-ID algorithm is devised which is based on image normalization technique and the Zernike moment such that the invariant features of asterisms are extracted instead of traditional ways. And three real images which captured via an uncalibrated ground-based telescope are used to validate our method, and the results show that it can effectively identify stars with a success rate of 99.27%, which demonstrate the robustness and accuracy of the proposed method.

In order to solve the problem that ground-based optical telescope cannot detect space targets in the daytime, an infrared detection method is proposed in this paper. Firstly, from the perspective of spectral characteristics of space targets and skylight, the short-wave infrared band(SWIR) of 0.9~1.7μm is optimized, which reduces the brightness of the skylight, and avoids the cooling of the optical system. Secondly, the signal-to-noise ratio(SNR) of the target is improved by the time-domain multi-frame accumulation algorithm and the goal of daytime 'extended range' detection of optical telescope is achieved. Experiments on a 0.3-meter telescope show that the space targets, which SNR less than 1 are detected by adopting this method in the daytime, when the zenith angle of sun is 40°, exposure time is 40ms, and the number of the cumulative frames is 360, the limit detection ability is 10.8mV. The results of the experiments well verify the theoretical analysis, which provides a reference for the system design of the next generation of ground-based optical telescope.Ground based optical telescope; Space targets; Day time; SWIR; Multi-frame accumulation.

The blind pixels and the flash pixels of infrared detector, which are easily to be detected as the target, increase the false alarm rate. An algorithm about the detection of blind pixel and flash pixel is proposed in this paper. This method is based on the characteristics that the gray values of the blind pixels in the sequence images are basically unchanged, there is a jump in the gray values of the flash pixels, and there are obvious differences between blind pixels and neighboring pixels in spatial domain, the method of joint processing in space-time domain is used to detect blind pixels. Compared with the traditional algorithm, this method effectively avoids the problem of target signal suppression in blind flash pixel detection. The experiment of a 0.3m telescope shows that this algorithm can effectively eliminate blind flash pixels in infrared images. In the experiment of dim target detection, combined with multi-frame energy accumulation algorithm, this algorithm has the ability to detect targets with signal to noise ratio (SNR) ≤ 1 and the brightness of 10.8mV is detected, which lays a technical foundation for the follow-up ground-based optical telescope to carry out full-time detection.The blind and flash pixels; Image sequence; SNR; Multi-frame accumulation