www.gusucode.com > Smart Nanosatellite Attitude Propagator (SNAP) 程序工具箱matlab源码 > Smart Nanosatellite Attitude Propagator (SNAP)/libastro/load_keps.m
% [R V Epoch JD Name] = load_keps(file) % % Translates TLEs to orbit initial conditions (position, velocity and % epoch). If the file contains multiple TLEs, the first one is used. % % ----------------------------------------------------------------------------- % Copyright (c) 2010-2018 Samir A. Rawashdeh % Electrical and Computer Engineering % University of Michigan - Dearborn % % All rights reserved. % % Redistribution and use in source and binary forms, with or without % modification, are permitted provided that the following conditions are % met: % % * Redistributions of source code must retain the above copyright % notice, this list of conditions and the following disclaimer. % * Redistributions in binary form must reproduce the above copyright % notice, this list of conditions and the following disclaimer in % the documentation and/or other materials provided with the distribution % % THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" % AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE % IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE % ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE % LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR % CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF % SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS % INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN % CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) % ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE % POSSIBILITY OF SUCH DAMAGE. % % ---------------------------------------------------------------------------- function [R V Epoch Name] = load_keps(file) sat = read_tloes(file); i=1; % for i = 1:length(sat) %% calculating semi major axis n = sat(i).mean_motion*2*pi/(24*60*60); mu = 5.9736e24 * 6.6742e-11; a = (mu/n^2)^(1/3); %% calculating true anomaly nu = nuFromM(sat(i).mean_anomaly*pi/180,sat(i).eccentricity); %% calculate R and V in km/sec [R,V] = randv(a/1000, ... sat(i).eccentricity, ... sat(i).inclination*pi/180, ... sat(i).RAAN*pi/180, ... sat(i).argp*pi/180, ... nu); % in m/s R = R*1000; V = V*1000; Epoch = sat(i).epoch.year + sat(1).epoch.day/365.2425; Name = sat(i).name; % disp([sat(i).name ', alt:' num2str((a-6357000)/1000) ', inc:' num2str(sat(i).inclination)]) % alt = (sqrt(R(1)^2+R(2)^2+R(3)^2)-6357000)/1000 % vel = (sqrt(V(1)^2+V(2)^2+V(3)^2))/1000 % % end