Landsat TM has a number of advantages that makes it unique for de

Landsat TM has a number of advantages that makes it unique for deriving burnt area estimates. This sensor is currently the only high spatial resolution sensor (30 m in the reflective channels and Sorafenib B-Raf 120 m in one thermal channel that it has) providing, at no cost, global image data at high spectral resolution (7 bands from visible to thermal infrared), compared to other high spatial resolution radiometers of high acquisition Inhibitors,Modulators,Libraries cost (e.g., ASTER, ALOS, SPOT), or to freely distributed coarser spatial resolution imagery (e.g., MODIS, MERIS, AVHRR).Landsat TM data have been used in the past in a large number of burnt area mapping s
In order to supply precise attitude for control systems, almost all spacecrafts need to obtain the attitudes. There are several sensors to determine the attitude relative to reference objects.

Star sensors are the most effective among them, acquiring the attitude information by star map processing methods and attitude-determining algorithms.An autonomous star recognition method is one of the core technologies of spacecraft attitude measurements with a star sensor. According to the original star map data obtained by the star sensor, the identification method transforms, Inhibitors,Modulators,Libraries transfers or combines Inhibitors,Modulators,Libraries the star points, which are included in a star map, and comes up with the characteristic information that reflects this star map as far as possible. Then, the information is compared with the Guidance-star database to complete the identification of the star map. The identification method must be able to achieve the rapid acquisition of spacecraft attitude, as well as rapid attitude reconstruction.

Therefore, the speed and success Inhibitors,Modulators,Libraries rate of identification are the key factors for judging the performance of identification algorithms.There are many popular star map recognition methods, which can be divided into three groups: the graph theory-based, the primary star-based and the intelligence-based. For example, the triangular [1,2], the quadrilateral [3] and the Delaunay triangulation [4] fall into the first group. The planar triangles [5], the grid [6], the identification method based on constellation [7], the statistical characteristics [8], the hausdorff distance [9] and the pyramid algorithm [10] fall into the second group. Finally, the star pattern recognition method based on neural network [11] and the genetic algorithm [12] fall into the third group.

These algorithms have their respective merits Dacomitinib in recognition speed, recognition success rate, the sky coverage rate, the database size, antinoise performance and stability. But in the condition of large Field Of View (FOV), which is no less than 20�� �� 20�� and high-sensitivity, next the recognition speed and success rate are the two outstanding problems for star recognition methods.The ant algorithm (AA) was first proposed by Italian scholar M. Dorigo in 1991.

Leave a Reply

Your email address will not be published. Required fields are marked *

*

You may use these HTML tags and attributes: <a href="" title=""> <abbr title=""> <acronym title=""> <b> <blockquote cite=""> <cite> <code> <del datetime=""> <em> <i> <q cite=""> <strike> <strong>