Remote sensing satellites play an increasingly prominent role in environmental monitoring and disaster rescue. Taking advantage of almost the same sunshine condition to same place and global coverage, most of these satellites are operated on the sun-synchronous orbit. However, it brings some problems inevitably, the most significant one is that the temporal resolution of sun-synchronous orbit satellite can’t satisfy the demand of specific region monitoring mission. To overcome the disadvantages, two methods are exploited: the first one is to build satellite constellation which contains multiple sunsynchronous satellites, just like the CHARTER mechanism has done; the second is to design non-predetermined orbit based on the concrete mission demand. An effective method for remote sensing satellite orbit design based on multiobjective evolution algorithm is presented in this paper. Orbit design problem is converted into a multi-objective optimization problem, and a fast and elitist multi-objective genetic algorithm is utilized to solve this problem. Firstly, the demand of the mission is transformed into multiple objective functions, and the six orbit elements of the satellite are taken as genes in design space, then a simulate evolution process is performed. An optimal resolution can be obtained after specified generation via evolution operation (selection, crossover, and mutation). To examine validity of the proposed method, a case study is introduced: Orbit design of an optical satellite for regional disaster monitoring, the mission demand include both minimizing the average revisit time internal of two objectives. The simulation result shows that the solution for this mission obtained by our method meet the demand the users’ demand. We can draw a conclusion that the method presented in this paper is efficient for remote sensing orbit design.
With the development of space technology, a growing number of the earth observing satellites have been used to acquire
data of the earth for various purposes, and the capability of data acquirement from spaceborne sensor makes a rapid
enhancement. Under this circumstance, it is very important to measure the capability of data acquirement quantitatively.
This paper concerns on the measurement of EOS data acquirement. This measurement can identify access area of a
specific EOS. Considering the characteristics of payload, the location of instantaneous imaging area could be calculated
based on sensor geometric model. To calculate the location of a given sensor instantaneous imaging area, the
measurement is divided into 3 stages: firstly, a satellite motion prediction is undertaken for the purpose of getting
position and velocity of the satellite; furthermore, considering the performance of skew maneuver, the imaging area of
the satellite's sensor could be calculated based on strict geometric model, finally, the imaging area of sensor is
calculated. Experimental results show that the proposed measurement is accurate.
An algorithm for satellite tracking and orbit prediction is presented in detail. Firstly, the satellite's position and velocity
are calculated by the Simplified General Perturbations Version 4 and Simplified Deep-space Perturbation Version 4
(SGP4/SDP4) orbit propagation algorithms. And we put forward "Two-Point-Pair" which means two points that the
CCD of satellite's IFOV rays intersecting with the earth. We make use of the "Two-Point-Pair" to calculate the accuracy
bounding box of satellite at the instantaneous time through the satellite's position and velocity above. Besides, we build a
system called GeoGlobe to simulate the algorithm. The system can be used to simulate all kinds of satellites that the
Two-Line Element (TLE) Sets files can provide.