Space Environment and Satellite Systems: Removing Clutter from Ground-to-Satellite Signals. Sigrid Close

Transcription

1 Space Environment and Satellite Systems: Removing Clutter from Ground-to-Satellite Signals Sigrid Close

2 Background Overview RF propagation through ionosphere can be problematic Goals Traditionally too simplistic Bending and higher order effects typically ignored Review prior simplistic ionospheric-removal methods Present improved methods

3 Outline Introduction What is the ionosphere? Signal generator (LAPP) and receiver (FORTE) Ionospheric Removal Techniques Results Summary

4 Brief History of the Ionosphere On December 12, 1901, Marconi received a signal in Newfoundland sent from England (500 khz) Awarded Nobel Prize in 1909 (EM for communication) Problem: EM radiation travels in straight lines Solution: Heaviside and Kennely propose conducting layer 1924, Appleton developed ionosonde and provide existence of ionosphere Awarded Nobel Prize in 1947

5 The Ionosphere What is the ionosphere? Partially ionized gas (i.e. a plasma) that envelops the earth and forms the interface between the atmosphere and space How do we detect the ionosphere? Sounders (i.e. ionosondes) Ground-based Space-based Radar Coherent Incoherent Scatter Radar (ISR) Rockets Satellites (GPS, etc.)

6 Ionospheric Variability - Time Vertical TEC (10 16 el/m 2 ) Solar Cycle Calendar Year Diurnal Variation Each radio frequency travels through ionosphere at different group velocity TEC = s 0 n e ds Seasonal Cycle Time Of Day (hours) Calendar Year

7 Ionospheric Variability - Location Auroral Auroral Oval South Auroral Oval North Field lines coupled to magnetosphere B z field to Earth Equatorial B x field II to Earth

8 Dispersion Relation Appleton-Hartree Dispersion Equation Quasi-longitudinal approximation n f p f 2 Only if Angle between k and B Meaning, Radio frequency >> Plasma frequency and propagation cannot be approximately within 0.5 o to magnetic field

9 Cost of Using Approximation Time Delay Error Due to Residual Ionosphere (sec)

10 Ground-based Signal Generator: LAPP Los Alamos Portable Pulser: Electromagnetic Pulses (EMPs) Capabilities Broadband high-power (750 MW at source) EMP signal source 12 o beamwidth High accuracy timing Satellite receiver calibration source: MHz Microsecond update Dr. Kalpak Dighe

11 Satellite-based Sensor: FORTE Sensors Broadband VHF receivers (20 80, MHz) Broadband Optical Photodiode 0.4 to 1.1 µm 15 µs resolution CCD Imager 10 km location accuracy Platform Altitude: ~ 825 km Inclination: 70 degrees Data Optical & VHF waveforms Event times Event location - precise with CCD data; to within field-ofview otherwise

12 Outline Introduction Ionospheric Removal Techniques Matched filter NIRA: Nonlinear Ionospheric Removal Algorithm Results Summary

13 Time Domain Signal Time-domain signal buried in noise at full bandwidth Frequency domain signal shows signal still buried Can we use time-domain signal to extract ionosphere?

14 Matched Filter Coherent method of time-frequency analysis Reverse the frequency-dependent phase shift from ionosphere Entire Electric field signal (E vs. t) Multiply FFT of the data with the conjugate of transfer function Benefits Simplified transfer function: where f is frequency, k is constant and TEC is total electron content Examines entire spectrum H trans = e 2πikTEC f Use entire signal-to-noise ratio (SNR) of signal

15 Frequency Domain Signal Short-time Fourier Transform (STFT) FFT on small portion of data Use sliding time window Can we fully model this signal?

16 Nonlinear Ionospheric Removal Algorithm (NIRA) Fit broadband data to Appleton-Hartree index of refraction Use nonlinear fitting algorithm Levenberg Marquardt Trust region Use output from quasi-longitudinal (1/f 2 ) fit to provide upper and lower bounds Input cyclotron frequency (ω c ) Output: Infinite frequency time of arrival (t o ) Angle between k and B (θ) Plasma density (n e ) Path length (ds)

17 Outline Introduction Ionospheric Removal Techniques Results Matched filter NIRA Stressed cases Summary

18 Matched Filter and NIRA

19 TEC Comparison Elevation = 33.6 o Matched Filter /f NIRA 58.5

20 Errors in Estimation Lay et al., 2010

21 Stressed Cases UHF L-BAND S-BAND

22 Stressed Cases Broadband Lightning Equatorial Plumes Matched Filter 27 1/f 2 50 NIRA 35 GPS 28 Matched Filter 105 1/f NIRA 103 Radar 113

23 Outline Introduction Ionospheric Removal Techniques Results Summary

24 Summary Broadband, satellite-based RF sensors need more sophisticated ionospheric-removal algorithms Two new approaches developed for ionospheric removal Matched filter NIRA Future work Modeling of non-impulsive event Scintillation and stressed cases Irregular structures in lower (i.e. weaker) ionosphere