Survey
* Your assessment is very important for improving the workof artificial intelligence, which forms the content of this project
* Your assessment is very important for improving the workof artificial intelligence, which forms the content of this project
CCIR 322-2 Atmospheric Noise 1 Why do this? • Understand the evolution atmospheric noise measurements • Determine what are appropriate values to use from the CCIR documentation • Compare CCIR data alternative noise data • Define the noise environment so mitigation techniques may be explored 2 What is CCIR 322-2? • Reported background atmospheric noise levels • Evolved into ITU P372-7 – Included man-made and galactic noise – Removed technical background • Used the ARN-2 Radio Noise Recorder – 16 Stations around the globe – Average noise power at each of eight frequencies for fifteen minutes each hour – 13 kHz, 11kHz, 250kHz, 500kHz, 2.5MHz, 5MHz, 10MHz, and 20MHz – 1957-1961 (4 years) → 8640 15-minute measurements → 99.98% – Tracked filtered noise envelope not instantaneous noise – Took high speed data to obtain APDs 3 What is CCIR 322-2? (cont) • Sectioned the year into seasons and time blocks – Four 90-day seasons – Six 4-hour time blocks • Tracked external antenna noise factor, Fa – Power received through a loss-free antenna Fa = 10*log10(Pn/KToB) – Lists the median value hourly value for each time block, Fam, at 1 MHz – Lists the upper decile (90%) level Du – Calculate noise E-field from Fa, BW, frequency • Use normal or log-normal statistics and graphs to adjust values 4 CCIR Stations 5 Fam for Summer 20-24h 6 Three Step Process for CCIR Data Look up Expected Median statistics (Fam) Adjust from Median to appropriate Time Availability Level (Fa from Du, %T) Adjust from Expected Value (mean) to Service Probability or Confidence (E from Fa, SNR, B, %S) 7 Computing E-field from CCIR Loran Receiver Specifications Frequency BW of system 0.1 MHz 30000 Hz From CCIR Fam 1 MHz 93 dB Fam 100 kHz 135 dB Vdm 200 Hz 7.9 dB Vd 30 kHz 12.8 dB Du 11.2 dB Delta=A-Arms -7 dB Variances of values sigmaDelta 4.2 dB sigmaVdm 1.5 dB sigmaDu 2.5 dB sigmaFam 3.9 dB sigmaPowerError 2 dB Assumed sigmaSNRError 2 dB Assumed 8 Computing E-field from CCIR (cont) Specify Level % Time D and Fa Exceeded % Time D and Fa Not Exceeded kappa (normal deviate) 95% 5% 1.64 Adjust Fam to Fa D [dB] sigmaD [dB] Fa [dB] Enoise (mean) for % Time [dBuV/m] 14 dB 3 dB 149 dB 64 dB uV/m Adjust mean value to service prob Service Probability 99% kappaServiceProb 2.33 sigmaTotal 6.9 dB uV/m kappaServiceProb*SigmaTotal 16 dB uV/m Enoise will be below 95% Time and with 99% Service Prob 80 dB uV/m 9 Computing CCIR Data Look up MEDIAN statistics (Fam) +14 dB <Emedian> = 50 dB uV/m Adjust for appropriate Time Availability Level (Fam, Du, 95%T) <E95%> = 64 dB uV/m +16 dB Adjust for uncertainty in statistics or Service Availability or Confidence (Fa, 99%S) E95% |99%= 80 dB uV/m 10 Adjustment to Enoise at 95% Time Availability for Service Probability Service Probability 90% 95% 99% 99.9% 99.99999% KServiceProb 1.28 1.64 2.33 3.09 5.20 sT for 95% Time Availability [DB] 6.9 6.9 6.9 6.9 6.9 9 11 16 21 36 KServiceProb* sT 11 RMS Envelope vs Inst. Envelope • Failure mode of receiver sometimes dictates using Inst. Envelope values over RMS Envelope values (eg FSK). • Needed a way to measure the “impulsiveness” of the noise. • Came up with using Vd – Vd = 20 * log10( Arms / Aavg) – Vd for Rayleigh (Gaussian > 0) is 1.05 – Larger Vd mean the more impulsive or less Gaussian the noise 12 CCIR APD Experimental Setup • Thanks to Bob Matherson and CCIR Instantaneous Noise, Vn IF Inst. Noise Voltage, VIF Atm Noise Instantaneous Noise Envelope, A RMS Noise Envelope, Arms Average Noise Envelope, Aavg 13 VIF and Envelope Voltages VIF Voltage and Noise Envelope Voltages 0.015 0.01 Voltage [V] 0.005 0 -0.005 VIF A Arms Aavg -0.01 -0.015 22.5 23 23.5 Time [msec] 24 24.5 14 25 Envelope RMS Voltage (Arms) & Instantaneous Envelope Voltage (A) • Arms is 3dB above rms instantaneous noise voltage VIFrms • APD – Amplitude Probability Distribution or A Posteriori Distribution – Exceedance probability P[A > Arms + D=A0] 0 • Parameterized by Vd Voltage deviation • Plotted on Rayleigh Probability Paper 15 CCIR FSK Example Results Time availability as a function of service probability Geneva, Switzerland Summer season: 2000-2400 h Frequency: 50 kHz Bandwidth: 100 Hz Binary errors: 0.05% Montgomery [1954] Model 16 CCIR Limitation (1983 §1) • "The estimates for atmospheric noise levels given in the Report are for the average background noise level due to lightning in the absence of other signals, whether intentionally or unintentionally radiated. In addition, the noise due to local thunderstorms has not been included. In some areas of the world, the noise from local thunderstorms can be important for a significant percentage of the time." 17 CCIR Limitations (cont) • “Atmospheric radio noise is characterized by large, rapid fluctuations, but if the noise power is averaged over a period of several minutes, the average values are found to be nearly constant during a given hour variations rarely exceeding ±2dB except near sunrise or sunset, or when there are local thunderstorms.” 18 CCIR Questions • What should we specify as a service probability 95%? • What is an appropriate level of availability? • How do the values change when we are near lightning? 19 dB(V/m/Hz) Electric/Magnetic Field Data (cont) 20 Preta 1984 Obtaining E-field from Lightning Return Stroke Data Lightning E-field noise density at 100kHz and 50km (Preta) Add conversion for 30kHz BW Add conversion from dB V/m to dB uV/m Lightning E-field at 100kHz, 30kHz BW, 50km -100 45 120 65 dB V/m/Hz dB Hz dB dB uV/m 21 Comparing E-fields and Distance Lightning E-field at 100kHz, 30kHz BW, 50km 65 dB uV/m Enoise for 95% Time and 99% Service Prob 80 dB uV/m • Lightning E-field data varies with 1/D • E2-E1 = 20*log10(D1/D2) = 20*log10(50km/D2) • For 100 kHz, an Enoise of 80 dB uV/m is equivalent to being 8.7 km from continuous repetitive lightning return strokes! • Can do this for all levels of % Time availability for any Service Probability 22 Conclusion from CCIR Data • Calculate Noise Level • Specify % Time and Confidence • Alternatively, as a distance to a lightning return stroke. I.e. define this as a ATC constraint 23 Summary • Reviewed CCIR-322 and current lightning research and found good correlation between both data sets. • Need to set both a not-to-exceed level and a confidence to make a reasonable estimate of noise level or can define a distance to a lightning return stroke. e.g. define this as a ATC constraint. • Need to use nonlinear processing to increase SNR. • Have pieces for a time-domain model. 24 Backup Slides 25 Processing Gain 26 Mitigation Techniques • Clipping or Blanking based on Vd – Spaulding/Middleton – Modestino/Enge • Using the Loran antenna as a lightning detector/locator • Low frequency signals propagate faster than higher frequency signals • Magnetic antenna / magnetometer 27 Spaulding/Middleton (Parametric) • Divide all noise into three canonical forms – Class A (3 parameters) • (duration of noise)(receiver bandwidth) >> 1 • Negligible transients are produced in linear front-end of receiver. • Steady state series of waves produced. – Class B (3 or 6 parameters) • (duration of noise)(receiver bandwidth) << 1 • All transients are produced in linear front-end of receiver. • Overlapping impulse response. – Class C (8 parameters) • (duration of noise)(receiver bandwidth) << 1 • Additive mixture of Class A and B • Use optimal adaptive non-linear filtering for improvement • Use suboptimal non-linear filtering (e.g. hole punch, hard limiter, etc) 28 Spaulding 1986 l x ( x j | P( ) ) d log f ( x j | H 0 ) dx j 29 Spaulding 1986 ~30dB Improvement! ~30dB 30 Spaulding 1986 Summary • Reviewed some signal processing with nonGaussian Noise • Much to be learned from the already published work regarding the processing of signals in non-Gaussian noise. • Large gains may be made by utilizing adaptive filters and even sub-optimal ones. • Currently trying to fit CCIR APD to 3Parameter Class B Model to various Vd in order to bound gains 31 Negative Leader CG Lightning 32 National Lightning Detection Network • Privately run • Real-Time data collection • Mostly detection and high level data • Some waveform data • Can use newer analytical field models 33 Sample Data Date Time Lat Lon Amplitude Range Az # Strk 5/9/2001 19:12:08 36.065 -106.483 -14.7 kA 18.9 mi 327.7 deg 1 5/9/2001 19:14:07 36.095 -106.431 -13.0 kA 19.4 mi 338.3 deg 1 5/9/2001 19:19:34 36.088 -106.432 -13.4 kA 19.0 mi 337.6 deg 1 5/9/2001 19:22:13 36.07 -106.471 -14.6 kA 18.9 mi 330.1 deg 1 5/9/2001 19:27:12 36.043 -106.404 -14.2 kA 15.5 mi 338.5 deg 2 5/9/2001 19:28:18 35.983 -106.369 -22.9 kA 11.0 mi 340.2 deg 4 5/9/2001 19:28:22 36.067 -106.491 -16.0 kA 19.2 mi 326.8 deg 4 5/9/2001 19:29:13 35.956 -106.314 -12.3 kA 8.5 mi 355.5 deg 1 5/9/2001 19:29:31 36.05 -106.392 -12.3 kA 15.7 mi 341.5 deg 1 5/9/2001 19:29:57 35.864 -105.964 +11.2 kA 19.0 mi 83.9 deg 1 5/9/2001 19:30:04 36.055 -106.472 -32.5 kA 18.0 mi 328.1 deg 2 5/9/2001 19:31:53 36.037 -106.443 -19.2 kA 16.1 mi 330.8 deg 3 5/9/2001 19:32:14 36.066 -106.337 -11.7 kA 16.1 mi 353.1 deg 1 5/9/2001 19:32:42 36.043 -106.454 -10.0 kA 16.7 mi 329.6 deg 1 5/9/2001 19:33:13 36.065 -106.458 -15.4 kA 18.2 mi 331.4 deg 1 5/9/2001 19:33:24 35.978 -106.291 -16.2 kA 10.0 mi 3.7 deg 2 5/9/2001 19:34:47 36.035 -106.419 -15.5 kA 15.4 mi 334.9 deg 3 5/9/2001 19:35:50 36.053 -106.433 -12.6 kA 16.8 mi 334.3 deg 1 5/9/2001 19:37:14 36.057 -106.421 -10.8 kA 16.8 mi 336.8 deg 1 5/9/2001 19:38:14 36.05 -106.401 -29.6 kA 15.9 mi 339.7 deg 2 5/9/2001 19:38:54 36.06 -106.413 -13.9 kA 16.8 mi 338.5 deg 342 … for another hour and a half ! Lightning Characteristics Type Stepped Leader Return Stroke Intracloud Event Time [usec] Duration [msec] 4 0-550 200 0-1100 2 0-10 35 Electric/Magnetic Field Data Intracloud Stepped Leader Return Pulse Weidman 1981 Intracloud 36 Krider 1975 Lightning Spectrum Return Positive Intracloud Stepped Leader Negative Intracloud 37 Comparing E-fields and Distance Lightning E-field at 100kHz, 30kHz BW, 50km 65 dB uV/m Enoise for 90% Time and 99.99999% Service Prob 96 dB uV/m • Lightning E-field data varies with 1/D • 20*log10(E2/E1) = 20*log10(D1/D2) = 20*log10(50km/D2) • For 100 kHz, an Enoise of 96 dB uV/m is equivalent to Lightning Return Stroke at 1.4 km! • Can do this for all levels of % Time availability for any Service Probability 38 Equivalent Power between % Time Fa Exceed and Lightning at a Given Distance With Given Service Probability Equivalent Distance to Continuous Lightning Strike [m] 100000 10000 1000 100 10 Median Service Prob 99.99999% Service Prob 1 1e-005 0.0001 0.001 0.01 0.1 Percentage of Time Fa Exceeded [%] 1 5 39 10 CCIR Median Data for 99% Level Atmospheric Noise 99% Worst Case of All Time and Seasons [dB V/m] 50 65 45 Latitude [deg] 85 75 40 70 35 80 30 25 50 -120 -110 55 -100 60 65 -90 Longitude [deg] 70 -80 75 -70 80 -60 85 90 40 Time Domain Model • Thunder days for this hemisphere – ~60 in N. Am / ~100-200 Central/South Am • Lightning stroke data from NLDN • Electric/magnetic field models from Uman • CCIR alternative based on APD – Gaussian portion - background – Impulsive portion – strikes 41 Envelope APD 0 42 Plot of APD on CCIR Probability Paper 40 30 3 Parameter Fit Amplitude [dB] 20 10 0 -10 -20 -30 .0001.001 .01 .1 .5 1 5 10 20 30 40 50 60 70 80 85 Percent Time Ordinate Exceeded 90 95 98 43 99