The researches on calibration of star sensor rarely involve the exterior parameters and image distortion of the optical
system. In order to get more accurate interior-exterior parameters of the optical system, this paper proposes exact
calibration model and algorithm based on interior-exterior parameters. Basing on analyzing the imaging model of star
sensor, the principle of the star sensor calibration is as follow: firstly, the two-step method is used to get the initial
interior-exterior parameters; then Levenberg-Marquardt optimization algorithm is utilized to get the global optimal
solution. Experiments show that the angular distance of stars can be reduced from 57" to 5.2" after calibration. In
addition, the calibration method can effectively eliminate the coupling of the interior-exterior parameters, achieve higher
measurement accuracy, and significantly improve the recognition rate of the star map.
Star image blurred by aircraft vibration decreases location accuracy and probability of the star extraction. In this paper,
first, the influence of aircraft vibration on the star image captured by star sensors is analyzed, and the mathematical
model is deduced and established. Then, in order to overcome the adverse effects of star extraction and stabilize the
accuracy of star sensor in high dynamic environment, a restoration method for blurred star image using Richardson-Lucy
(RL) method is introduced. The experimental results indicate that the proposed method can effectively improve the star
image signal-to-noise ratio and the extraction accuracy.
A novel adaptive aircraft detection method based on level set processing and circle-frequency filter is proposed in this paper. First, the SBGFRLS (Selective Binary and Gaussian Filtering Regularized Level Set) method is used twice to find airport region of interest (ROI) and candidate aircraft areas by local segmentation and global segmentation, respectively, so that sizes of those possible target areas can be computed. Then, the circle-frequency (CF) filter method is utilized adaptively to detect target aircrafts in the airport ROI via the mean radius estimated by sizes of those candidate areas obtained before. Experimental results on real remote sensing airport images demonstrate the efficiency and accuracy of the proposed method.
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