Prototype Software-based Receiver for Remote Sensing using Reflected GPS Signals. Dinesh Manandhar The University of Tokyo

Transcription

1 Prototype Software-based Receiver for Remote Sensing using Reflected GPS Signals Dinesh Manandhar The University of Tokyo 1

2 Contents Background Remote Sensing Capability System Architecture Data Observation Algorithm (Signal Processing) Results and Discussions 2

3 GPS Signal Characteristic GPS signal is RHCP (Right Hand Circular Polarization) type The polarization of GPS signal may change when reflected from RHCP to LHCP and vice versa Based on reflecting material type and signal incidence angle The amplitude reduces for every reflection, because: The reflection coefficient is less than one Some of the signal is absorbed Reflection may not be perfectly specular The phase of the signal changes that might be neither RHCP nor LHCP (elliptical polarization) The chip delay increases for every reflection Since it needs to travel extra distance Thus, the analysis of relative amplitude between the direct signal and reflected signal provides information about reflecting material type The chip delay corresponds to the path delay length or multipath amount 3

4 Remote Sensing Capability using GPS/GNSS Signal GPS / GNSS signals around 1.5Ghz is good for soil moisture analysis The dielectric value difference is about 10 times between dry soil and wet soil This value is about 30times more for water than dry soil Hence it provides very strong sensitivity to soil moisture at L-band Beside soil moisture, there are many other applications where GPS signals can be used for remote sensing applications Wind velocity over ocean, ocean observation, ice monitoring etc GPS / GNSS signals is available to all, at any time and at free of cost, An active radar can be tracked or detected while it s observing, but not the passive one like GPS because it does not transmit any signal for observation The signals are continuously transmitted only for navigation purpose You can observe the things without being detected Important aspect in military applications 4

5 Reflection Coefficient of materials for Horizontal and Verticle Polarization Linear Reflection Coeff Linear Reflection Coefficient, Horizontal Fresh Water Sea Water Wet Ground Medium Dry Ground Dry Ground Concrete Linear Reflection Coeff. Linear Reflection Coefficient, Verticle 1 Fresh Water Sea Water 0.8 Wet Ground 0.6 Medium Dry Ground 0.4 Dry Ground 0.2 Concrete Propagation Angle This slide shows coefficient of reflection at 1.5Ghz fro different incident angles. Circular polarization can be divided into two components, which are horizontal and verticle components. As we can see in the graphs that, the reflection coefficient values smoothly decreases with respect to incident angle for horizontal component. Where as for verticle component, it decreases fast upto certain angle called Brewster's angle then it raises smoothly after that angle. Hence, the characteristics of horizontal and verticle components are quite different. A circular polarization can be modeled by the vector sum of horizontal land vertical components to estimate the overall effect. 5

6 Change in Phase Angle for Horizontal and Verticle Polarization 200 Phase Angle of Reflection, Horizontal Phase Angle Phase Angle Sea Water Propagation Angle Phase Angle of Reflection, Verticle Concrete Dry Ground Medium Dry Ground Wet Ground Fresh Water Concrete Dry Ground Medium Dry Ground Wet Ground Fresh Water Sea Water Propagation Angle This slide shows the effect of reflection on phase for horizontal and vertical components. When a circularly polarized signal is reflected, it s horizontal component will always have 180 degree phase reversal. Where as the verticle component will have phase reversal only if the propagation angle is below Brewster s angle. If the phase changes for both horizontal and vertical components, then we will have left hand circular polarization since GPS signal is right hand circular polarization. However, if the propagation angle is greater than the Brewster s angle, then we will have elliptical polarization which is neither perfectly left hand nor right hand. This is the case in most of the cases for reflected signals. 6

7 System Architecture RH Master Antenna (RHCP) RF Front-End GPS signal Processing pc Hard Disk 1 LH Slave Antennas (LHCP) Antenna Orientation RHCP : Zenith (Sky) LHCP : Nadir (Ground) The system consists of two antennas, a front-end device, a PC and an external high speed hard disk. The front-end down-converts the analog signal from the antenna at 1.5Ghz to 16Mhz with a centre frequency of 4Mhz at 4bit resolution. It is necessary to do so since we need a sampled digital data of the original analog data at a level data a standard PC can process. We use RHCP (right hand circular polarization) antenna for GPS since GPS signal transmitted from the satellite is RHCP. However, in our case we also use reversed polarized antenna, which is LHCP (left hand circular polarization). The reason for using LHCP antenna is that the reflected signal in most of the cases is no more RHCP unless it reflected twice where the signal changes polarization from RHCP to LHCP and then back to RHCP again. But, multiple reflection signals are very weak compared to single reflection. As, we have seen in the previous slides, normally reflected signals are either LHCP or elliptical. Hence the use of LHCP antenna provides us better SNR (signal to noise ratio). The RHCP antenna is oriented towards the sky to receive direct signal, without multipath as far as possible. The LHCP antenna is oriented downwards to receive reflected signal. The orientation angle of the LHCP antenna has big impact on received signal based on satellite geometry in view. As we discussed in the previous slide, the reflected signal coefficient and phase change with respect to incident or propagation angle. Hence, it is very important to understand the impact of orientation angle with respect to satellite geometry if the application is intended for remote sensing purpose. 7

8 Data Observation, Rooftop of University Bldg Data observation height : about 20m Antenna Used : LPA Passive Data logged on different days 8

9 Data Obs. Ht: 87m Antenna Used: LPA Passive Data logged for a single day only Data Observation, Tower Location of Antenna 9

10 Power Spectrum and Histogram of Raw Data This slide shows the PSD (Power Spectrum Density) of raw GPS (IF Data) signals (TOP) and histograms of the data (bottom). TOP: Blue color shows data from Reflected Signal or LHCP antenna Red Color shows data from Direct Signal or RHCP antenna BOTTOM Right: Histogram for Direct or RHCP antenna data Bottom Left : Histogram for Reflect or LHCP data 10

11 Algorithm, Signal Processing RHCP Data PRN & Carrier Acquisition Tracking Navigation Position X, Y, Z Vx, Vy, Vz 2 2 ( I Q ) + Corresponds to Reflecting Material Character PRN only LHCP Data PRN for LHCP I-Channel chip Code and Carrier Phase from RHCP tracking Q-Channel chip I-Channel n th chip Q-Channel n th chip RHCP Power 2 2 ( I + Q ) 2 2 ( I Q ) + LHCP Power 2 2 ( I + Q ) Corresponds to Path Delay The basic algorithm concept: Perform acquisition on RHCP data and compute code phase and doppler frequency Assume that the doppler frequency is the same since both the antennas are at the same platform and they move together. Use the code phase and doppler frequency computed from RHCP antenna to compute the relative delay in LHCP data with respect to RHCP data. Doppler frequency computed from RHCP is used for acquisition in LHCP data. Only code phase is computed at various chip delays beginning from the chip delay computed for RHCP data. This is also called Master-Slave processing. In our case, Master is RHCP and slave is LHCP. 11

12 Basic Concept Difference in Amplitude Provides Information about Reflecting Material Chip Delay corresponds to Extra Path (Multipath?) Basically, we can observe two parameters: (1) Relative difference in Chip Delays (2) Relative difference in Amplitude If there is a delay in incoming signal in LHCP antenna, there will be chip delay difference between the RHCP and LHCP peaks. By observing the relative chip delay between the two antennas, we can estimate the amount of path delay. Another point of observation is the relative difference between the amplitude of the two signals. The difference in amplitude is due to the difference in electrical property of the reflecting material. Hence, by observing the relative amplitude difference, it might be possible to model the reflecting object type. This is a sort of remote sensing using GNSS signal. 12

13 Results, Tower Data PRN ID : 30 Antenna Orientation RHCP UP LHCP Down Antenna Height 87mtr. This slide shows results of data taken from tower at a height of about 87m from the ground. The satellite visibility chart shows the visible satellites and their location at the time of survey. In this case, we have taken satellite 30 for analysis. Satellite 30 is visible at an elevation of about 58 degrees and azimuth of about 40degrees. The LHCP antenna was oriented towards the ground at an down looking angle of about 55degrees from nadir. The azimuth direction is similar to satellite 30. The figure on the bottom left shows C/No (carrier to noise) with respect to satellite azimuth and elevation angle for RHCP and LHCP antenna data. As expected, we can see stronger C/No for RHCP data since the signal is coming directly into the antenna. The LHCP signal is weaker compared to RHCP signal but it is not so weak. We can also see the fading patterns in LHCP signal which is due to reflection of the signal. We have data just for a few minutes. The top figure at the right side of the slide shows correlation output power for RHCP (red) and LHCP (blue) signal. We can see very clear difference between the two. Direct signal is stronger and reflected signal is weaker. Also, the reflected signal is offset from the centre (prompt value) by half a chip (one chip is one bit of PRN code which is about 300m long in terms of distance). This is due to extra distance the signal has to travel because of reflection. The middle figure on the right side shows I and Q channel (cosine and sine components) powers. A normal signal will exhibit only power in I channel and noise in Q channel as we see in the figure. The I and Q plot also represents the navigation bits. We can clearly see the sequence of navigation bits with phase reversal at multiples of 20msec, since a navigation bit is 20msec long. However, in the bottom figure, we can see power on both I and Q channels. This is probably due to the fact that the reflected signal is neither LHCP nor RHCP. It is a sort of elliptical polarization and hence the power is divided into both channels. As time lapses, the power level in Q channel will be changing. It may also change in I channel. The key observation here is power level difference between the two antenna data and their relative chip delay. The difference in power level is due to different reflection characteristic of the reflecting material. Dry ground will have very low reflection coefficient and hence the power level will be very low compared to wet ground or water. 13

14 Antenna Height Estimation Extra Path Delay: δr = 2hsin δr h= 2sin ( θ) ( θ) θ θ θ θ P h -h Multipath Model Forward Scattering as shown above The extra path delay is about 0.5 chip delay which is about 150m The antenna elevation angle is about 55degree from the nadir Thus, height of the antenna, h = 150/2*sin(55*pi/180) = 92m This is in very close proximity of actual antenna height from the ground δr P 14

15 Results, Tower Data PRN ID : 1 Antenna Orientation RHCP UP LHCP Down Antenna Height 87mtr 15

16 Results, Tower Data PRN ID : 5 Antenna Orientation RHCP UP LHCP Down Antenna Height 87mtr 16

17 Results, Tower Data PRN ID : 25 Antenna Orientation RHCP UP LHCP Down Antenna Height 87mtr. 17

18 Results, Roof Data PRN ID : 14 Antenna Orientation RHCP UP LHCP Down Antenna Height 20mtr. 18

19 Results, Roof Data PRN ID : 6 Antenna Orientation RHCP UP LHCP Down Antenna Height 20mtr. 19

20 Summary LHCP Antenna Orientation and Gain Pattern The orientation of the antenna with respect to the satellite geometry (azimuth and elevation) has effect on power level Hence, the total power computation shall be done by considering the satellite geometry and antenna orientation considering the gain pattern. The power value shall be normalized for easy comparison A narrow beam antenna will provide good footprint resolution, but this also limits the satellite visibility duration Probably, an array of antennas is needed for wide coverage with better resolution Difficult to automate the selection of satellite that has good reflected signal Both amplitude and delay It seems that similar elevation angle of the satellite and LHCP antenna provides best result For example, if the satellite is at 25degrees above horizon and the LHCP antenna is oriented at 60degrees down, probably there will be no reflected signal It seems that an angle of degree provide good data provided there are visible satellites around that elevation as well This needs further experiments and also depends on the antenna gain pattern 20

21 Summary Correlator Output and spacing Very small chip delays (less that two sampled chips) are not clearly identifiable But, we can see reflected signal with both the direct and reflected peak almost at the same correlator location Probably, we need wider bandwidth front-end in order to detect the peaks at very narrow correlator values, e.g or less in our case Integration of Samples Long integration (averaging of I and Q power) period provides reduced noise However, we may loose the important observation point, especially in dynamic platform We have not modeled the amplitude value with respect to ground condition due to lack of enough samples at different time intervals This needs observation together with validation (reference) data Modeling for remote sensing applications need data from both static and dynamic platforms 21

22 Future Plans Conduct Survey using UAV (remote controlled helicopter) Test Flight Scheduled in Oct Conduct Survey at Experimental Ground of the University where a ground based Microwave Radar is stationed This will provide good reference data, especially for soil moisture 22

23 Thanks a lot! 23