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Direction of Arrival Estimation by Moving Antenna for Multipath GNSS Channel Characterization Mohammad Hatef Keshvadi Position, Location And Navigation.

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Presentation on theme: "Direction of Arrival Estimation by Moving Antenna for Multipath GNSS Channel Characterization Mohammad Hatef Keshvadi Position, Location And Navigation."— Presentation transcript:

1 Direction of Arrival Estimation by Moving Antenna for Multipath GNSS Channel Characterization Mohammad Hatef Keshvadi Position, Location And Navigation (PLAN) Group Department of Geomatics Engineering University of Calgary ENGO699.27 - March 16 th, 2010 Mohammad Hatef Keshvadi Position, Location And Navigation (PLAN) Group Department of Geomatics Engineering University of Calgary ENGO699.27 - March 16 th, 2010

2 Direction of Arrival Estimation by Moving Antenna for Multipath GNSS Channel Characterization2/13ContentsContents ReviewReview Beamscan error analysisBeamscan error analysis Implementation of MUSIC DoA method for outdoor dataImplementation of MUSIC DoA method for outdoor data Indoor data collection, Upper floor, Mild multipath environmentIndoor data collection, Upper floor, Mild multipath environment Indoor data collection, Lower floor, Mild to harsh multipath environmentIndoor data collection, Lower floor, Mild to harsh multipath environment ConclusionConclusion ReviewReview Beamscan error analysisBeamscan error analysis Implementation of MUSIC DoA method for outdoor dataImplementation of MUSIC DoA method for outdoor data Indoor data collection, Upper floor, Mild multipath environmentIndoor data collection, Upper floor, Mild multipath environment Indoor data collection, Lower floor, Mild to harsh multipath environmentIndoor data collection, Lower floor, Mild to harsh multipath environment ConclusionConclusion

3 ENGO 699.27- GNSS indoor channel characterization in dense multipath environments by moving antenna 3/13Review Previous Tasks: Collecting data on the roofCollecting data on the roof Implementation of BeamscanImplementation of Beamscan Elevation estimation error (deg)Elevation estimation error (deg) (for the first revolution): PRN 29PRN 24 El 79.767.9 PRN 29PRN 24 El4.32.6

4 ENGO 699.27- GNSS indoor channel characterization in dense multipath environments by moving antenna 4/13 Beamscan error Analysis Analyzing the error in estimation of elevation angle for various revolutions of the antenna (Ref. of measurement: Navigation data from Novatel’s DTU software) PRN 29PRN 24 Mean 3.62.4 Variance 0.060.08 Probably due to time offset between the data collection time and capturing the satellite’s position time. Search Space Steps: 0.01 rad = 0.57 deg

5 ENGO 699.27- GNSS indoor channel characterization in dense multipath environments by moving antenna 5/13 Implementation of MUSIC: outdoor data PRN 29PRN 24 El 79.767.9 MUSIC: Scanning the field of view to find spots where noise subspace is orthogonal to the signal subspace. Higher resolution comparing to Beamscan The same error pattern as Beamscan method Data collection environment: CCIT rooftop (No Multipath)

6 ENGO 699.27- GNSS indoor channel characterization in dense multipath environments by moving antenna 6/13 Indoor data collection (Upper floor) Data collected in a typical North American, wooden frame residential structure. This location is prone to mild to harsh multipath and fading Data collection specifications: Date: 5 Feb. 2010, 11:00am until 12:00pm Revolution Speed:4 revs/min System Architecture: Outdoor Ref. Ant. And Indoor Rotating Ant. Coherent Int. Time: 200msec Radius of Rotation: 51cm

7 ENGO 699.27- GNSS indoor channel characterization in dense multipath environments by moving antenna 7/13 Indoor data collection (Upper floor) El (deg) PRN-1856.07 PRN-2461.99 PRN-2930.42 More than 1 peak is observed in indoor environment The height of the secondary peaks is always less than 1 The peak’s location is not constant with time (unlike outdoor conditions)

8 ENGO 699.27- GNSS indoor channel characterization in dense multipath environments by moving antenna 8/13 Indoor data collection (Upper floor) Satellite’s actual Elevation: 62 o Variations of Signal’s source with time:

9 ENGO 699.27- GNSS indoor channel characterization in dense multipath environments by moving antenna 9/13 Indoor data collection (Upper floor) Error Analysis PRN - 29 BeamscanMUSIC mean2.271.03 Variance0.3710.96 Max3.383.95 Min1.09-6.93 Time interval between each revolution: 15s

10 ENGO 699.27- GNSS indoor channel characterization in dense multipath environments by moving antenna 10/13 Indoor data collection (Lower floor) The same building as previous scenario. The test apparatus moved from main floor to lower floor to investigate the effects of higher levels of Multipath and Fading Data collection specifications: Date: 5 Feb. 2010, 13:00pm until 14:30pm Revolution Speed:4 revs/min System Architecture: Outdoor Ref. Ant. And Indoor Rotating Ant. Coherent Int. Time: 200msec Radius of Rotation: 36cm

11 ENGO 699.27- GNSS indoor channel characterization in dense multipath environments by moving antenna 11/13 Indoor data collection (Lower floor) ElAz PRN-1877.0168.82 PRN-2420.98119.45 The number of observed peaks increase Peaks vary more significantly in power by time The peak’s location has temporal variations

12 ENGO 699.27- GNSS indoor channel characterization in dense multipath environments by moving antenna 12/13 Indoor data collection (Lower floor) Error Analysis Beamscan PRN18PRN24 Mean-13.565.95 Variance0.0849.81 MUSIC PRN18PRN24 Mean-13.425.66 Variance0.22015.04

13 ENGO 699.27- GNSS indoor channel characterization in dense multipath environments by moving antenna 13/13Conclusions For mild multipath environments, the error in estimation of DoA reaches to several (6~8) degrees. By increasing the level of multipath, this error increases while introducing more and relatively stronger sources of signal. Future works 1- Implementing FFT based DoA methods 2- Implementing Beamforming methods 3- Applying the above derived algorithms on a set of data collected in a harsh multipath environmentFor mild multipath environments, the error in estimation of DoA reaches to several (6~8) degrees. By increasing the level of multipath, this error increases while introducing more and relatively stronger sources of signal. Future works 1- Implementing FFT based DoA methods 2- Implementing Beamforming methods 3- Applying the above derived algorithms on a set of data collected in a harsh multipath environment

14 ENGO 699.27- GNSS indoor channel characterization in dense multipath environments by moving antenna 14/13 Indoor data collection (Lower floor) Variations of Signal’s source with time: PRN 18 – High elevation Satellite’s actual Elevation: 77 o APPENDIX

15 ENGO 699.27- GNSS indoor channel characterization in dense multipath environments by moving antenna 15/13 Indoor data collection (Lower floor) Variations of Signal’s source with time: PRN 24 – Low elevation  Low C/N0 and antenna pattern effects Satellite’s actual Elevation: 21 o APPENDIX


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