Non-Cooperative Spacecraft Attitude Estimation Based on Feature Extraction on ISAR Images

Aiming at the problem that ISAR images have low resolution and serious noise and non-cooperative spacecraft lack cooperative information, resulting in large attitude estimation errors, a space target attitude estimation method based on contours and linear structures on ISAR images and models is proposed. This method uses an enhanced Frost filter to filter out image noise and preprocess the image to improve image quality. UNet3+ with the CBAM attention mechanism is used to segment the spacecraft contour from the ISAR image, and then the linear structure of the target contour is extracted. The target model is then rotated and projected to establish a target attitude template library, and the template library is clustered using the linear structure of the model. The Softassign ICP algorithm and local direction information are used to optimize shape context matching, and finally the attitude information of the target spacecraft is returned. Experimental results on real ISAR images show that this method can effectively reduce the attitude estimation error, and the errors of the three attitude angles are all within 1 degree.