Shape models and physical properties of asteroids

Despite the large amount of high quality data generated in recent space encounters with asteroids, the majority of our knowledge about these objects comes from ground based observations. Asteroids travelling in orbits that are potentially hazardous for the Earth form an especially interesting group to be studied. In order to predict their orbital evolution, it is necessary to investigate their physical properties. This paper briefly describes the data requirements and different techniques used to solve the lightcurve inversion problem. Although photometry is the most abundant type of observational data, models of asteroids can be obtained using various data types and techniques. We describe the potential of radar imaging and stellar occultation timings to be combined with disk-integrated photometry in order to reveal information about physical properties of asteroids.Comment: From Assessment and Mitigation of Asteroid Impact Hazards boo

Sensory processing and world modeling for an active ranging device

In this project, we studied world modeling and sensory processing for laser range data. World Model data representation and operation were defined. Sensory processing algorithms for point processing and linear feature detection were designed and implemented. The interface between world modeling and sensory processing in the Servo and Primitive levels was investigated and implemented. In the primitive level, linear features detectors for edges were also implemented, analyzed and compared. The existing world model representations is surveyed. Also presented is the design and implementation of the Y-frame model, a hierarchical world model. The interfaces between the world model module and the sensory processing module are discussed as well as the linear feature detectors that were designed and implemented

ADAM: a general method for using various data types in asteroid reconstruction

We introduce ADAM, the All-Data Asteroid Modelling algorithm. ADAM is simple and universal since it handles all disk-resolved data types (adaptive optics or other images, interferometry, and range-Doppler radar data) in a uniform manner via the 2D Fourier transform, enabling fast convergence in model optimization. The resolved data can be combined with disk-integrated data (photometry). In the reconstruction process, the difference between each data type is only a few code lines defining the particular generalized projection from 3D onto a 2D image plane. Occultation timings can be included as sparse silhouettes, and thermal infrared data are efficiently handled with an approximate algorithm that is sufficient in practice due to the dominance of the high-contrast (boundary) pixels over the low-contrast (interior) ones. This is of particular importance to the raw ALMA data that can be directly handled by ADAM without having to construct the standard image. We study the reliability of the inversion by using the independent shape supports of function series and control-point surfaces. When other data are lacking, one can carry out fast nonconvex lightcurve-only inversion, but any shape models resulting from it should only be taken as illustrative global-scale ones.Comment: 11 pages, submitted to A&

Planet–sun sensor revisited

Since the seminal work of Daniele Mortari (“Moon-Sun Attitude Sensor,” Journal of Spacecraft and Rockets, Vol. 34, No. 3, 1997, pp. 360–364), the concept of an attitude sensor using images of illuminated celestial bodies has been pushed forward through the years. The basic idea consists of extracting two independent directions from the image of a celestial body, namely, the camera-to-planet and the planet-to-sun directions. The former is estimated from the center of an ellipse fitted to the imaged limb points and the latter from the symmetry axis of the illuminated region. These assumptions, however, only hold for far-distant spherical targets. In this work, the problem is reformulated in the framework of projective camera transformations of quadrics and conics, and an algorithm estimating the line of sight to the planet and the illumination direction from the limb and terminator ellipses, respectively, is presented. The method is applicable to any ellipsoidlike celestial body having known orientation. The algorithm is first validated on synthetically generated images and then tested using real pictures of Dione and Enceladus satellites gathered from Cassini spacecraft. Results show that the sensor concept returns rms errors in the order of the angular width of a pixel in computing the nadir direction, and subdegree accuracy in computing the sun direction