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Characterization of Atmospheric Noise in the Loran-C Band

This presentation discusses the data processing and flight test results for the characterization of atmospheric noise in the Loran-C band. The study includes measurements from normal conditions and thunderstorms in Ohio and Florida.

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Characterization of Atmospheric Noise in the Loran-C Band

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  1. Characterization of Atmospheric Noise in the Loran-C BandPresented to the International Loran Association (ILA-32) November 6, 2003 Boulder, CO Manish Lad Frank van Graas, Ph.D. David Diggle, Ph.D. Curtis Cutright

  2. Outline • Data Processing Overview • Flight Test Results • “Quiet (normal conditions)” data collected in Ohio • “Thunderstorm” data collected in Florida • Conclusions

  3. Flight Data Collection Equipment • King Air C-90 B Aircraft • LORADD-DS DataGrabber • Novatel OEM4 GPS receiver • WX-500 StormScope • Apollo 618 (Loran receiver) • Data collection PC King Air C-90B

  4. Wire vs. Loop Antenna Gain • Theoretically, the dual-loop antenna has a 3-dB gain advantage over the wire antenna • Exact gain difference depends on the antenna installation Gain = 0 dB Gain = 3 dB Note: SNR results are determined at the output of the antenna.

  5. Processing Collected Data • Read Loran-C data • Identify and remove CW interference • Remove Thunderstorm bursts • Read GPS data • Identify and remove Loran-C chains • Calculate signal-to-noise ratio • Characterize atmospheric noise

  6. Loran-C Data Processing Overview GPS Time, Position Collected data Find filter coefficients Loran Processor Remove pulses that are above noise floor Bandstop filters Track transmitters Noise power Signal power Calculate SNR Noise Sequence Noise Characterization Noise distribution

  7. Removal of CW and Thunderstorm Bursts Bank of band-pass filters Sampled data at 400 kSamples/sec Detect CW 1-500 Hz Calculate bandstop filter coefficients 501-1000 Hz 2-sec data block 1001-1500 Hz Filter the CW from 2 second data block 199.5-200KHz Integrate PCI’s for identifying different chains Remove bins with Energy above a set threshold Calculate Energy in bins

  8. Loran processor Chain information Integrate signal as per PCI of chain Identify Master and secondaries Antenna position Compute signal power for each station Remove Loran-C pulses that are above noise floor Compute average noise power obtained after removal of pulses Calculate the noise distribution Calculate SNR for master and secondaries Signal after removal of CWs and Thunderstorm Bursts (if present)

  9. Flight Test Data • Results obtained for different data sets under diverse atmospheric conditions (clear and Thunderstorm) • Data collected in Ohio: NEUS chain • Data collected in Florida: SEUS chain

  10. Flight Test Results Normal conditions Athens, Ohio Collected on August 13, 2003

  11. Ground Path (Athens, Ohio) Flight test trajectory near Athens, Ohio

  12. E–field Data Example: Time Domain Note: Signal Amplitude is in A/D levels

  13. E–field Data Example (Cont’d) Before and after processing the 2-second data chunk

  14. E-field Noise Statistics (Athens, Ohio) Noise Distribution Number of samples

  15. E-field Noise Statistics (Cont’d) Calculated and Gaussian cdf cdf (1-cdf) Cumulative probability

  16. H–field Data Example (Athens, Ohio)

  17. H–field Data Example (Cont’d) Before and After Processing the 2-second data chunk

  18. H-field Noise Statistics (Athens, Ohio) Noise Distribution Number of samples

  19. H-field Noise Statistics (Cont’d) Calculated and Gaussian cdf cdf (1-cdf) Cumulative probability

  20. Results (Athens, Ohio) SNR measurements (average of 326 seconds) at the output of the antenna for NEUS chain

  21. Flight Test Results Daytona Beach, Florida Collected in the Vicinity of Thunderstorms on August 14, 2003

  22. Ground Path (Daytona Beach, FL) Flight test trajectory near Daytona Beach, FL

  23. E-field Data Example (Daytona Beach, FL) Signal Amplitude Number of samples (2 seconds of data) Note: Dynamic range of data collection equipment is 96 dB (16 bits)

  24. E-field Data Example (Cont’d) Before and After Processing the 2-second data chunk

  25. E-field Data Example (Cont’d) Signal Amplitude Number of samples (2 seconds of data)

  26. E-field Data Example (Cont’d) Before and After Processing the 2-second data chunk

  27. E-field Data Example (Cont’d)

  28. E–field Noise Statistics (Daytona Beach, FL) Noise Distribution Number of samples

  29. E–field Noise Statistics (Cont’d) Calculated and Gaussian cdf cdf (1-cdf) Cumulative probability

  30. H–field Noise Statistics (Daytona Beach, FL) Noise Distribution Number of samples

  31. H–field Noise Statistics (Cont’d) Calculated and Gaussian cdf cdf (1-cdf) Cumulative probability

  32. Results (Daytona Beach, FL) SNR (average of 326 seconds) measurements at the output of the antenna for SEUS chain

  33. Flight Test Results Palm Coast, Florida Collected in the Vicinity of Thunderstorms on August 14, 2003

  34. Ground Path (Palm Coast, FL) Flight test trajectory near Palm coast, FL

  35. E–field Noise Statistics (Palm Coast, FL) Noise Distribution Number of samples

  36. E–field Noise Statistics (Palm Coast, FL) Calculated and Gaussian cdf cdf (1-cdf) Cumulative probability

  37. H–field Noise Statistics (Palm Coast, FL) Noise Distribution Number of samples

  38. H–field Noise Statistics (Palm Coast, FL) Calculated and Gaussian cdf cdf (1-cdf) Cumulative probability

  39. Results (Palm Coast, FL) SNR (average of 326 seconds)measurements at the output of the antenna for SEUS chain

  40. Conclusions • SNR at the output of Loop (H-field) antenna is generally greater than the SNR at the output of Wire (E-field) antenna by 2-3 dB • Noise distribution • Core of distribution looks Gaussian • Tail probabilities are much larger than Gaussian with an equivalent rms value (looks like 3-sigma) • Data collected from both the antennas closely match in the calculated cdf of the noise

  41. Acknowledgements • Federal Aviation Administration (FAA) • Mitch Narins (Loran Program Manager) • Reelektronika B.V. • Dr. Durk van Willigen, Wouter Pelgrum • King Air Crew • Bryan Branham, Jay Clark

  42. Questions ?

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