吡虫啉的射程错误 [英] Wrong Range Rate with Pyephem

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本文介绍了吡虫啉的射程错误的处理方法,对大家解决问题具有一定的参考价值,需要的朋友们下面随着小编来一起学习吧!

问题描述

我正在尝试使用Python和pyephem计算卫星测距率.不幸的是,pyephems结果似乎是错误的.

I am trying to calculate a satellites Range Rate using Python and pyephem. Unfortunately pyephems result seems to be wrong.

将该值与其他卫星跟踪程序(如GPredict或Ham Radio Deluxe)进行的计算进行比较后,差异达到2 km/sec.Azemuth和Elevation脚踝的计算值几乎相同. TLE是新的,系统时钟是相同的.

After comparing the value with calculations made by other satellite tracking programs like GPredict or Ham Radio Deluxe the the difference goes up to 2km/sec.The calculated values for the Azemuth and Elevation ankle are almost the same thought. TLE's are new and the system clock is the same.

您是否看到我在代码中犯的任何错误,或者您知道还有什么可能导致该错误?

Do you see any mistake I made in my code or do you have an idea what else could cause the error?

非常感谢!

这是我的代码:

import ephem
import time
#TLE Kepler elements
line1 = "ESTCUBE 1"       
line2 = "1 39161U 13021C   13255.21187718  .00000558  00000-0  10331-3 0  3586"
line3 = "2 39161  98.1264 332.9982 0009258 190.0328 170.0700 14.69100578 18774"
satellite = ephem.readtle(line1, line2, line3) # create ephem object from tle information
while True:
    city = ephem.Observer() # recreate Oberserver with current time
    city.lon, city.lat, city.elevation = '52.5186' , '13.4080' , 100

    satellite.compute(city)
    RangeRate = satellite.range_velocity/1000 # get RangeRate in km/sec
    print ("RangeRate: " + str(RangeRate))
    time.sleep(1)

我从脚本和GPRedict记录了一些Range Rate值,以可再现地产生该错误:

I recorded some Range Rate values from the script and from GPRedict to make the error reproducibly:

ESTCUBE 1               
1 39161U 13021C   13255.96108453  .00000546  00000-0  10138-3 0  3602
2 39161  98.1264 333.7428 0009246 187.4393 172.6674 14.69101320 18883

date: 2013-09-13  
time       pyephem-Script  Gpredict          
14:07:02   -1.636          -3.204  
14:12:59   -2.154          -4.355  
14:15:15   -2.277          -4.747  
14:18:48   -2.368          -5.291  

然后我添加了一些行来计算卫星的仰角和坐标:

And I added some lines to calculate the satellites elevation and coordinates:

elevation = satellite.elevation
sat_latitude = satellite.sublat
sat_longitude = satellite.sublong

带时间戳的结果是:

2013-09-13 14:58:13  
RangeRate: 2.15717797852 km/s  
Range: 9199834.0  
Sat Elevation: 660743.6875  
Sat_Latitude: -2:22:27.3  
Sat_Longitude: -33:15:15.4    

2013-09-13 14:58:14  
RangeRate: 2.15695092773 km/s  
Range: 9202106.0  
Sat Elevation: 660750.9375  
Sat_Latitude: -2:26:05.8  
Sat_Longitude: -33:16:01.7  

另一个重要的信息可能是我正在尝试计算卫星通行证的多普勒频率.因此,我需要Range Rate:

Another important information might be that I am trying to calculate the Doppler Frequency for a satellite pass. And therefore I need the Range Rate:

f_Doppler_corrected = (c0/(c0 + RangeRate))*f0

范围率描述了移动对象在视轴上到观察者的速度.也许range_velocity有所不同?

Range Rate describes the velocity of a moving object on the visual axis to the observer. Maybe the range_velocity is something different?

推荐答案

似乎pyephem(后端为libastro)和gpredict(预测)为后端使用不同的方式来计算卫星速度.我附上比较的详细输出,以便进行实际的参考观察.可以看出,两者都输出正确的位置,而只有gpredict输出合理的range_rate值.该误差似乎发生在卫星速度矢量中.我会说gpredict的原因更合理(而且类似的代码在libastro中带有问号..)因此我将在libastro中提出一个修复程序来像gpredict中一样处理它,但是也许了解它背后的数学原理的人可以添加到此.

It seems pyephem (libastro as a backend) and gpredict (predict) as a backend use different ways to calculate the satellite velocity. I am attaching detailed output of comparison for an actual reference observation. It can be seen that both output the correct position, while only gpredict outputs reasonable range_rate values. The error seems to occur in the satellite velocity vector. I would say that the reasons from gpredict are more reasonable (and the similar code is with question marks in libastro ..) therefore I will propose a fix in libastro to handle it as in gpredict, however maybe someone who understands the math behind it can add to this.

我添加了另一个工具PyPredict(也基于预测),可以在此处进行一些计算.但是这些值是关闭的,因此必须是其他值.

I added another tool, PyPredict (also predict based), to get some calculations here. However these values are off, so must be something else.

Pyephem: 3.7.5.3
Gpredict: 1.3
PyPredict 1.1 (Git: 10/02/2015)


OS: Ubuntu x64
Python 2.7.6

Time:
Epoch timestamp: 1420086600
Timestamp in milliseconds: 1420086600000
Human time (GMT): Thu, 01 Jan 2015 04:30:00 GMT

ISS (ZARYA)             
1 25544U 98067A   15096.52834639  .00016216  00000-0  24016-3 0  9993
2 25544  51.6469  82.0200 0006014 185.1879 274.8446 15.55408008936880

observation point: N0 E0 alt=0

Test 1:

Gpredict: (Time, Az, El, Slant Range, Range Velocity)

2015 01 01 04:30:00 202.31 -21.46 5638 -5.646
2015 01 01 04:40:00 157.31 -2.35 2618 -3.107
2015 01 01 04:50:00 72.68 -10.26 3731 5.262

Pyephem 3.7.5.3 (default atmospheric refraction)

(2015/1/1 04:30:00, 202:18:45.3, -21:27:43.0, 5638.0685, -5.3014228515625)
(2015/1/1 04:40:00, 157:19:08.3, -1:21:28.6, 2617.9915, -2.934402099609375)
(2015/1/1 04:50:00, 72:40:59.9, -10:15:15.1, 3730.78375, 4.92381201171875)
No atmospheric refraction
(2015/1/1 04:30:00, 202:18:45.3, -21:27:43.0, 5638.0685, -5.3014228515625)
(2015/1/1 04:40:00, 157:19:08.3, -1:21:28.6, 2617.9915, -2.934402099609375)
(2015/1/1 04:50:00, 72:40:59.9, -10:15:15.1, 3730.78375, 4.92381201171875)

Pypredict

1420086600.0
{'decayed': 0, 'elevation': -19.608647085869123, 'name': 'ISS (ZARYA)', 'norad_id': 25544, 'altitude': 426.45804846615556, 'orbit': 92208, 'longitude': 335.2203454719759, 'sunlit': 1, 'geostationary': 0, 'footprint': 4540.173580837984, 'epoch': 1420086600.0, 'doppler': 1635.3621339278857, 'visibility': 'D', 'azimuth': 194.02436209048014, 'latitude': -45.784314563471646, 'orbital_model': 'SGP4', 'orbital_phase': 73.46488929141783, 'eclipse_depth': -8.890253049060693, 'slant_range': 5311.3721164183535, 'has_aos': 1, 'orbital_velocity': 27556.552465256085}
1420087200.0
{'decayed': 0, 'elevation': -6.757496200551716, 'name': 'ISS (ZARYA)', 'norad_id': 25544, 'altitude': 419.11153234752874, 'orbit': 92208, 'longitude': 9.137628905963876, 'sunlit': 1, 'geostationary': 0, 'footprint': 4502.939901708917, 'epoch': 1420087200.0, 'doppler': 270.6901377419433, 'visibility': 'D', 'azimuth': 139.21315598291235, 'latitude': -20.925997669236732, 'orbital_model': 'SGP4', 'orbital_phase': 101.06301876416072, 'eclipse_depth': -18.410968838249545, 'slant_range': 3209.8444916123644, 'has_aos': 1, 'orbital_velocity': 27568.150821416708}
1420087800.0
{'decayed': 0, 'elevation': -16.546383900323555, 'name': 'ISS (ZARYA)', 'norad_id': 25544, 'altitude': 414.1342802649042, 'orbit': 92208, 'longitude': 31.52356804788407, 'sunlit': 1, 'geostationary': 0, 'footprint': 4477.499436144489, 'epoch': 1420087800.0000002, 'doppler': -1597.032808834609, 'visibility': 'D', 'azimuth': 76.1840387294104, 'latitude': 9.316828913183791, 'orbital_model': 'SGP4', 'orbital_phase': 128.66115193399546, 'eclipse_depth': -28.67721196244149, 'slant_range': 4773.838774518728, 'has_aos': 1, 'orbital_velocity': 27583.591664378775}


Test 2 (short time):
Gpredict: (Slant Range, Range Velocity)
2015 01 01 04:30:00 5638 -5.646
2015 01 01 04:30:10 5581 -5.648
->5.7 km/s avg

(2015/1/1 04:30:00, 5638.0685, -5.3014228515625)
(2015/1/1 04:30:10, 5581.596, -5.30395361328125)
->5.7 km/s avg

火星草

import ephem
import time
#TLE Kepler elements

line1 = "ISS (ZARYA)"             
line2 = "1 25544U 98067A   15096.52834639  .00016216  00000-0  24016-3 0  9993"
line3 = "2 25544  51.6469  82.0200 0006014 185.1879 274.8446 15.55408008936880"

satellite = ephem.readtle(line1, line2, line3) # create ephem object from tle information

obs = ephem.Observer() # recreate Oberserver with current time
obs.lon, obs.lat, obs.elevation = '0' , '0' , 0

print('Pyephem Default (atmospheric refraction)')

obs.date = '2015/1/1 04:30:00'
satellite.compute(obs)
print(obs.date, satellite.az, satellite.alt,satellite.range/1000, satellite.range_velocity/1000)

obs.date = '2015/1/1 04:40:00'
satellite.compute(obs)
print(obs.date, satellite.az, satellite.alt,satellite.range/1000, satellite.range_velocity/1000)

obs.date = '2015/1/1 04:50:00'
satellite.compute(obs)
print(obs.date, satellite.az, satellite.alt,satellite.range/1000, satellite.range_velocity/1000)

obs.pressure = 0 # disable atmospheric refraction
print('Pyephem No atmospheric refraction')

obs.date = '2015/1/1 04:30:00'
satellite.compute(obs)
print(obs.date, satellite.az, satellite.alt,satellite.range/1000, satellite.range_velocity/1000)

obs.date = '2015/1/1 04:40:00'
satellite.compute(obs)
print(obs.date, satellite.az, satellite.alt,satellite.range/1000, satellite.range_velocity/1000)

obs.date = '2015/1/1 04:50:00'
satellite.compute(obs)
print(obs.date, satellite.az, satellite.alt,satellite.range/1000, satellite.range_velocity/1000)

print('10 s timing')
obs.date = '2015/1/1 04:30:00'
satellite.compute(obs)
print(obs.date, satellite.range/1000, satellite.range_velocity/1000)
obs.date = '2015/1/1 04:30:10'
satellite.compute(obs)
print(obs.date, satellite.range/1000, satellite.range_velocity/1000)

预测

import predict
import datetime
import time

format = '%Y/%m/%d %H:%M:%S'

tle = """ISS (ZARYA)
1 25544U 98067A   15096.52834639  .00016216  00000-0  24016-3 0  9993
2 25544  51.6469  82.0200 0006014 185.1879 274.8446 15.55408008936880"""
qth = (0, 10, 0)  # lat (N), long (W), alt (meters)

#expect time as epoch time float

time= (datetime.datetime.strptime('2015/1/1 04:30:00', format)  -datetime.datetime(1970,1,1)).total_seconds()
result = predict.observe(tle, qth, time)
print time
print result

time= (datetime.datetime.strptime('2015/1/1 04:40:00', format)  -datetime.datetime(1970,1,1)).total_seconds()
result = predict.observe(tle, qth, time)
print time
print result

time= (datetime.datetime.strptime('2015/1/1 04:50:00', format)  -datetime.datetime(1970,1,1)).total_seconds()
result = predict.observe(tle, qth, time)
print time
print result

调试Gpredict和PyEphem的输出

Debug output of Gpredict and PyEphem

PyPredict

PyPredict

Name = ISS (ZARYA)
current jd = 2457023.68750
current mjd = 42003.7
satellite jd = 2457119.02835
satellite mjd = 42099
SiteLat = 0
SiteLong = 6.28319
SiteAltitude = 0
se_EPOCH  :    115096.52834638999775052071
se_XNO    :         0.06786747737871574870
se_XINCL  :         0.90140843391418457031
se_XNODEO :         1.43151903152465820312
se_EO     :         0.00060139998095110059
se_OMEGAO :         3.23213863372802734375
se_XMO    :         4.79694318771362304688
se_BSTAR  :         0.00024016000679694116
se_XNDT20 :         0.00000000049135865048
se_orbit  :                          93688
dt        :   -137290.81880159676074981689
CrntTime = 42004.2
SatX = -3807.5
SatY = 2844.85
SatZ = -4854.26
Radius = 6793.68
SatVX = -5.72752
SatVY = -3.69533
SatVZ = 2.32194
SiteX = -6239.11
SiteY = 1324.55
SiteZ = 0
SiteVX = -0.0965879
SiteVY = -0.454963
Height = 426.426
SSPLat = -0.795946
SSPLong = 0.432494
Azimuth = 3.53102
Elevation = -0.374582
Range = 5638.07
RangeRate = -5.30142
(2015/1/1 04:30:00, 5638.0685, -5.3014228515625)

Gpredict

time: 2457023,687500
pos obs: -6239,093574, 1324,506494, 0,000000
pos sat: -3807,793748, 2844,641722, -4854,112635
vel obs: -0,096585, -0,454962, 0,000000
vel sat: -6,088242, -3,928388, 2,468585

Gpredict(sgp_math.h)

Gpredict (sgp_math.h)

/ ------------------------------------------- ----------------------- /

/* Converts the satellite's position and velocity  */
/* vectors from normalised values to km and km/sec */ 
void
Convert_Sat_State( vector_t *pos, vector_t *vel )
{
      Scale_Vector( xkmper, pos );
      Scale_Vector( xkmper*xmnpda/secday, vel );

} /* Procedure Convert_Sat_State */

以弗所(Libastro)

Ephem (Libastro)

*SatX = ERAD*posvec.x/1000; /* earth radii to km */
*SatY = ERAD*posvec.y/1000;
*SatZ = ERAD*posvec.z/1000;
*SatVX = 100*velvec.x;      /* ?? */
*SatVY = 100*velvec.y;
*SatVZ = 100*velvec.z;

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