AAE6102_Assignments

• AAE6102_Assignments
  • Usage
  • Task 1 – Acquisition
    • Urban
    • Opensky
  • Task 2 – Tracking
    • Urban
    • Opensky
    • Discussion
  • Task 3 – Navigation Data Decoding
    • Urban
      • PRN 1
      • PRN 3
      • PRN 11
      • PRN 18
    • Opensky
      • PRN 16
      • PRN 22
      • PRN 26
      • PRN 27
      • PRN 31
  • Task 4 – Position and Velocity Estimation
    • Urban
    • Opensky
  • Task 5 – Kalman Filter-Based Positioning
    • Urban
    • Opensky
    • Discussion

Usage

1. Change dataset path and identify which dataset at initSettings.m.

settings.dataNo             = 0;  % 0 for Urban, 1 for Opensky
% This is a "default" name of the data file (signal record) to be used in
% the post-processing mode

if (settings.dataNo == 0)
    settings.fileName           = 'C:\Users\mint\Documents\dataset\GNSS\Urban.dat';
    settings.IF                 = 0;
    settings.samplingFreq       = 26e6;
else
    settings.fileName           = 'C:\Users\mint\Documents\dataset\GNSS\Opensky.bin';
    settings.IF                 = 4.58e6;
    settings.samplingFreq       = 58e6;
end

2. Run tasks one by one

Task_1_Acquistion

Task_2_Tracking

Task_3_DataDecoding

Task_4_PositionandVelocityEstimation

Task_5_KalmanFilterBasedPositioning

Task 1 – Acquisition

Process the IF data using a GNSS SDR and generate the initial acquisition results.

Urban

Opensky

Task 2 – Tracking

Adapt the tracking loop (DLL) to generate correlation plots and analyze the tracking performance. Discuss the impact of urban interference on the correlation peaks. (Multiple correlators must be implemented for plotting the correlation function.)

Urban

Opensky

Discussion

• Multipath:

Multipath interference causes the correlation peak to broaden, shift, or develop secondary peaks. This distorts the true peak position, leading to errors in pseudorange measurements. The constructive and destructive interference of multipath signals can reduce the amplitude of the correlation peak, making it harder to detect. The correlation peak may become asymmetric, with a steeper leading edge and a trailing edge due to delayed multipath signals.

• NLOS:

NLOS signals can create false correlation peaks that are stronger than the true peak, leading to incorrect pseudorange measurements. The correlation peak may shift away from its true position due to the additional path delay introduced by reflections. NLOS signals are typically weaker and noisier, reducing the overall quality of the correlation peak.

Task 3 – Navigation Data Decoding

Decode the navigation message and extract key parameters, such as ephemeris data, for at least one satellite.

Urban

PRN 1

Field Name	Field Value
C_ic	-7.45058059692383e-08
omega_0	-3.10603580061844
C_is	1.60187482833862e-07
i_0	0.976127704025531
C_rc	287.46875
omega	0.711497598513721
omegaDot	-8.16962601200124e-09
IODE_sf3	72
iDot	-1.81078971237415e-10
idValid	2 0 3
weekNumber	1032
accuracy	0
health	0
T_GD	5.58793544769287e-09
IODC	12
t_oc	453600
a_f2	0
a_f1	-9.43600753089413e-12
a_f0	-0.0000348975881934166
IODE_sf2	72
C_rs	-120.71875
deltan	4.19088885305686e-09
M_0	0.517930887728972
C_uc	-0.00000633485615253448
e	0.00892308494076133
C_us	0.0000053010880947113
sqrtA	5153.65564346313
t_oe	453600
TOW	449352

PRN 3

Field Name	Field Value
C_ic	1.11758708953857e-08
omega_0	-2.06417843827738
C_is	5.21540641784668e-08
i_0	0.96285874592588
C_rc	160.3125
omega	0.594974558438532
omegaDot	-7.83246911092014e-09
IODE_sf3	72
iDot	4.81091467962126e-10
idValid	2 0 3
weekNumber	1032
accuracy	0
health	0
T_GD	1.86264514923096e-09
IODC	4
t_oc	453600
a_f2	0
a_f1	-1.13686837721616e-12
a_f0	0.000186326447874308
IODE_sf2	72
C_rs	-62.09375
deltan	4.44768526394384e-09
M_0	-0.430397463873375
C_uc	-0.00000309012830257416
e	0.00222623045556247
C_us	0.0000115595757961273
sqrtA	5153.77780151367
t_oe	453600
TOW	449352

PRN 11

Field Name	Field Value
C_ic	-3.16649675369263e-07
omega_0	2.72577037566571
C_is	-1.32247805595398e-07
i_0	0.909806735685279
C_rc	324.40625
omega	1.89149296226273
omegaDot	-9.3043161335422e-09
IODE_sf3	83
iDot	1.2857678431059e-11
idValid	2 0 3
weekNumber	1032
accuracy	0
health	0
T_GD	-1.2572854757309e-08
IODC	229
t_oc	453600
a_f2	0
a_f1	8.5265128291212e-12
a_f0	-0.000590092502534389
IODE_sf2	83
C_rs	-67.125
deltan	5.89095966783022e-09
M_0	-0.198905418191913
C_uc	-0.0000036042183637619
e	0.0166431387187913
C_us	0.00000151246786117554
sqrtA	5153.70659637451
t_oe	453600
TOW	449352

PRN 18

Field Name	Field Value
C_ic	-2.5331974029541e-07
omega_0	3.12182125430595
C_is	3.53902578353882e-08
i_0	0.954642600078998
C_rc	280.15625
omega	1.39301587576552
omegaDot	-8.61071581373341e-09
IODE_sf3	56
iDot	-1.61792453590826e-10
idValid	2 0 3
weekNumber	1032
accuracy	0
health	0
T_GD	-5.58793544769287e-09
IODC	244
t_oc	453600
a_f2	0
a_f1	3.18323145620525e-12
a_f0	5.98649494349957e-05
IODE_sf2	56
C_rs	-113.875
deltan	4.72019661513546e-09
M_0	0.259840988631583
C_uc	-0.00000610947608947754
e	0.0154198176460341
C_us	0.00000511482357978821
sqrtA	5153.69931793213
t_oe	453600
TOW	449352

Opensky

PRN 16

Field Name	Field Value
C_ic	-1.00582838058472e-07
omega_0	-1.6742614288517
C_is	1.3597309589386e-07
i_0	0.971603403113095
C_rc	237.6875
omega	0.679609496852005
omegaDot	-8.01283376668916e-09
IODE_sf3	9
iDot	-4.89306095848636e-10
idValid	2 0 3
weekNumber	1155
accuracy	0
health	0
T_GD	-1.02445483207703e-08
IODC	234
t_oc	396000
a_f2	0
a_f1	-6.3664629124105e-12
a_f0	-0.000406925100833178
IODE_sf2	9
C_rs	23.34375
deltan	4.24660545959145e-09
M_0	0.718116855169473
C_uc	0.00000138953328132629
e	0.0122962790774181
C_us	0.00000768713653087616
sqrtA	5153.77132225037
t_oe	396000
TOW	390102

PRN 22

Field Name	Field Value
C_ic	-1.00582838058472e-07
omega_0	1.27273532182623
C_is	-9.31322574615479e-08
i_0	0.936454582863647
C_rc	266.34375
omega	-0.887886685712927
omegaDot	-8.66857536667317e-09
IODE_sf3	22
iDot	-3.03584074066672e-11
idValid	2 0 3
weekNumber	1155
accuracy	0
health	0
T_GD	-1.76951289176941e-08
IODC	218
t_oc	396000
a_f2	0
a_f1	9.2086338554509e-12
a_f0	-0.000489472411572933
IODE_sf2	22
C_rs	-99.8125
deltan	5.28307720422849e-09
M_0	-1.26096558850673
C_uc	-0.00000515580177307129
e	0.00671353843063116
C_us	0.00000516511499881744
sqrtA	5153.71227264404
t_oe	396000
TOW	390102

PRN 26

Field Name	Field Value
C_ic	-2.04890966415405e-08
omega_0	-1.81293070066348
C_is	8.94069671630859e-08
i_0	0.939912327258295
C_rc	234.1875
omega	0.295685419113132
omegaDot	-8.31141763247709e-09
IODE_sf3	113
iDot	-4.17517391275223e-10
idValid	2 0 3
weekNumber	1155
accuracy	0
health	0
T_GD	6.98491930961609e-09
IODC	15
t_oc	396000
a_f2	0
a_f1	3.97903932025656e-12
a_f0	0.000144790392369032
IODE_sf2	113
C_rs	21.25
deltan	5.05128183473523e-09
M_0	1.73557093431869
C_uc	0.00000115297734737396
e	0.00625350861810148
C_us	0.00000704079866409302
sqrtA	5153.63645935059
t_oe	396000
TOW	390102

PRN 27

Field Name	Field Value
C_ic	1.08033418655396e-07
omega_0	-0.7174746604652
C_is	1.15483999252319e-07
i_0	0.974727542206028
C_rc	230.34375
omega	0.630881664719351
omegaDot	-8.02426281418343e-09
IODE_sf3	30
iDot	-7.14315468392169e-13
idValid	2 0 3
weekNumber	1155
accuracy	0
health	0
T_GD	1.86264514923096e-09
IODC	4
t_oc	396000
a_f2	0
a_f1	-5.00222085975111e-12
a_f0	-0.000206120777875185
IODE_sf2	30
C_rs	70.4375
deltan	4.03016787266862e-09
M_0	-0.173022280718202
C_uc	0.00000373087823390961
e	0.0095741068944335
C_us	0.00000824220478534698
sqrtA	5153.65202140808
t_oe	396000
TOW	390102

PRN 31

Field Name	Field Value
C_ic	-1.13621354103088e-07
omega_0	-2.78727290293284
C_is	-5.02914190292358e-08
i_0	0.95588255042505
C_rc	240.15625
omega	0.311626182035606
omegaDot	-7.99497587997936e-09
IODE_sf3	83
iDot	3.21441960776476e-11
idValid	2 0 3
weekNumber	1155
accuracy	0
health	0
T_GD	-1.30385160446167e-08
IODC	228
t_oc	396000
a_f2	0
a_f1	-1.93267624126747e-12
a_f0	-0.000144899822771549
IODE_sf2	83
C_rs	30.71875
deltan	4.8073431022793e-09
M_0	2.82452321963233
C_uc	0.00000146031379699707
e	0.0102715539978817
C_us	0.00000722892582416534
sqrtA	5153.62238883972
t_oe	396000
TOW	390102

Task 4 – Position and Velocity Estimation

Using pseudorange measurements from tracking, implement the Weighted Least Squares (WLS) algorithm to compute the user's position and velocity.

• Plot the user position and velocity.
• Compare the results with the ground truth.
• Discuss the impact of multipath effects on the WLS solution.

Urban

Opensky

Task 5 – Kalman Filter-Based Positioning

Develop an Extended Kalman Filter (EKF) using pseudorange and Doppler measurements to estimate user position and velocity.

Urban

Opensky

Discussion

Aspect	Impact of Multipath
Pseudorange Measurements	Introduces bias and increases noise in pseudorange measurements.
Residuals	Increases residuals, leading to larger errors in the WLS cost function.
Bias in Solution	Introduces systematic errors (bias) in the estimated position.
Weighting Matrix	Degrades the effectiveness of the weighting matrix, leading to over-reliance on corrupted measurements.
Position Accuracy	Causes horizontal and vertical position errors, ranging from meters to tens of meters.
Solution Stability	Reduces solution stability, causing jumps or drifts in the estimated position.