Inside GNSS Media & Research

NOV-DEC 2018

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54 InsideGNSS N O V E M B E R / D E C E M B E R 2 0 1 8 www.insidegnss.com ΔPRC standard deviation error. is difference shows the right trend, however, is not significant. But as both signals are strong, no large difference can be expected and the error budget is expected to be dominated by multipath. e standard deviation of the ΔPRP with a C/N 0 ≈ 52 dB-Hz is 0.52 cm and with a C/N 0 ≈ 58 dB-Hz it is 0.66 cm. As mentioned above, the degradation of the phase tracking in the higher power signal also causes a bigger standard deviation in the ΔPRP. Summary and Outlook An innovative concept for code and phase performance analy- UAV Transmitted Composite-BOC (CBOC) Signal Until now, only the SIS was pro- cessed a nd a na ly zed to verif y that the ground system works as desired. From now on a self-cre- ated single CBOC pilot signal is used, with the same parameters as for the Galileo OS E1B CBOC. e transmission sampling rate was 40 MS/s (complex valued). Only the D-FE results will be shown from now on. In the f light test, the drone is hovering between the two Rx antennas at a height of 30 meters, pictured in Figure 1. In Figure 10, the tracking results for the D-FE1 and D-FE2 recording are shown. In the 500-second-long segment the transmitting power was increased by +6 dB at approxi- mately 250 seconds. An increase in code tracking (DLL) and frequency tracking (FLL) performance, by increased power, can easily be seen in Figure 10 (middle row). On the contrary, a slight degradation of the phase tracking (PLL) is visible for the increased power (most likely but still to be verified due to tran- sient errors or oscillator jitter). e CMC variation is in a reasonable range, but the small CMC dri in both signals is an issue for further investigation. As the ground sys- tem was tested and this dri only occurs in the UAVlite signal, it is assumed that either temperature or hardware effects are causing this dri in the USRP. A represen- tative multi correlator (MC) plot of the recorded UAVlite signals is presented in Figure 11. e MC plot shows 201 correlation values of the CBOC signal for a chip offset of –0.51 till +0.51 chips. For the ΔPR analysis of the UAVlite signal we analyzed 180 seconds from the lower (50-54 dB-Hz) C/N 0 power level and 180 seconds from the higher (57-60 dB-Hz) C/N 0 power level. e results for ΔPRC (top) and ΔPRP (bottom) are presented in Figure 12 (lower power) and Figure 13 (higher power). e standard deviation of the ΔPRC with a C/N 0 ≈ 52 dB-Hz is 0.369 meters and with a C/N 0 ≈ 58 dB-Hz it is 0.337 meters. Both values are better than for the SIS analysis. is is reasonable as the UAVlite signal was 6 dB stronger. Furthermore it shows that the signal, with 6 dB higher power, has a slightly better WORKING PAPERS FIGURE 8 ∆PR of Code (a) and Phase (b) of Galileo OS PRN3 SIS comparing D-FE1 and D-FE2 (same clock; no external clock sync.). The top plots show ∆PR(t) and ∆GR(t) (satellite movement approximated by a quadratic polynomial fit). The bottom plots show the difference of ∆PR – ∆GR = ε 1 - ε 2 Time [s] 0 a. b. 50 100 150 200 250 5 0 –5 ∆ Range [m] Time [s] 0 50 100 150 200 250 5 0 –5 δ ∆ Range [m] Time [s] 0 50 100 150 200 250 1 0 –1 ∆ Phase [m] Time [s] 0 50 100 150 200 250 0.02 0 –0.02 δ ∆ Phase [m] FIGURE 9 ∆PR of Code (a) and Phase (b) of Galileo OS PRN3 SIS comparing S-FE and D-FE2 (diff. clocks; WR clock sync.). The top plots show ∆PR(t) and ∆GR(t) (satellite movement approximated by a quadratic polynomial fit). The bottom plots show the difference of ∆PR – ∆GR = ε 1 - ε 2 Time [s] 0 50 100 150 200 250 5 0 –5 ∆ Range [m] Time [s] 0 50 100 150 200 250 5 0 –5 δ ∆ Range [m] Time [s] 0 50 100 150 200 250 1 0 –1 ∆ Phase [m] Time [s] 0 50 100 150 200 250 0.02 0 –0.02 δ ∆ Phase [m] a. b.

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