Vision based terrain relative navigation sensor

Arindam Mal, J. Laha, Tanisha Bhatia, Subhalakshmi K, Shwetha Kanawalli
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Abstract

Space field has witnessed vigorous change due to evolution of image processing. For precise spacecraft navigation and landing, high end image processing algorithm has to be executed in real time. In this paper, vision based in plane relative positioning and velocity sensor is discussed for precise landing. Image acquisition of the planet from the camera at the altitude of 6km–200m at successive time interval is planned. These images are used for the estimation of velocity and relative position using phase correlation based method. Image FFT are performed to compute correlation using radiation hardened FPGA. Sub pixel-shift of 1/20th pixel between two images is calculated from correlation peak using interpolation technique. Terrain relative horizontal velocity is estimated from the images pixel-shift per unit time with the help of altimeter data. This measurement technique is robust against image illumination variation, rotation tolerance of 0.3 degree between two successive images and Jitter of the space craft. The computation time is assessed from the simulation and optimized to get a faster update rate. A proto model of the sensor is tested successfully in laboratory environment using a scene simulation of lunar terrain in front of the sensor.
由于图像处理技术的发展,空间领域发生了巨大的变化。为了实现航天器的精确导航和着陆,需要实时执行高端图像处理算法。本文讨论了基于平面相对定位和速度传感器的视觉精确着陆方法。计划在6公里至200米的连续时间间隔上从相机获取行星图像。这些图像被用于使用基于相位相关的方法估计速度和相对位置。利用增强辐射的FPGA对图像进行FFT计算。利用插值技术从相关峰计算出两幅图像间1/20像素的亚像素位移。利用高度计数据,利用图像单位时间的像元位移估计地形相对水平速度。该测量技术对图像光照变化、连续两幅图像之间0.3度的旋转公差和航天器抖动具有较强的鲁棒性。通过仿真评估计算时间,并对其进行优化以获得更快的更新速率。通过对传感器前方月球地形的场景模拟,在实验室环境下对传感器的原型模型进行了成功的测试。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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