Correlation Between Atmospheric Noise Levels at Different Frequencies

Joglekar, P. J.

doi:10.1109/temc.1970.303064

Cited by 10 publications

(2 citation statements)

References 7 publications

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“…The latter has been subsequently called the noise burst level or the noise level and has been expressed in microvolts per meter. The time constants of the noise meter which were first obtained by trial and error were later explained theoretically [Aiya, 1958] [Aiya, 1962;Satyam, 1962;Lakshminarayan, 1962], (4) recording of the AF output arising from noise bursts on magnetic tapes and level recorders [Aiya and Lakshminarayan, 1965], (5)cathode ray oscillographic and other studies of the structure of noise bursts [Shivaprasad, 1971], (6) effect of receiver bandwidth on the amplitude and time parameters of noise bursts [Gupta, 1969[Gupta, , 1971], (7) measurement, use, and statistical relationship between peak, rms, average, and quasi-peak amplitudes of noise bursts [Aiya and Bhanumurthy, 1969;Bhanumurthy, 1971 ], (8) correlation between atmospheric noise levels at different frequencies [Joglekar, 1970], and (9) study and instrumentation for VHF atmospheric noise bursts [Bhat, 1968]. These studies constitute the scientific basis on which the measurements were carried out and data deduced.…”

Section: Measurementsmentioning

confidence: 99%

Atmospheric noise data for tropical regions

Aiya¹

1979

Radio Science

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The known unsatisfactory nature of atmospheric noise data based on pre-1964 measurements for tropical regions is due to the inadequacy of the dynamic range of the measuring equipment in recording local storm noise. This high-amplitude, highly impulsive noise arises from the electrical discharges inside the cloud at heights varying from about 3 to over 10 km above the mean sea level in the tropics. Direct ray reception of the radiation from such discharges is expected for source distances of the order of 300 km. The number of local storm days is experimentally found to be about three times the recorded number of thunderstorm days and can exceed 50% of the days of a season in the tropics. Electrical discharges corresponding to one lightning flash give rise to one noise burst in the receiver. The structure of such noise bursts and their amplitude and time characteristics have been studied. Highest amplitude noise present for 10% of the time in a short period of time like 5 min is the portion-relevant for interference purposes, and this arises from the noise bursts described. Its short-term characteristics are log normal. The long-term characteristics of the short-term mean values are also log normal. Consequently, noise data are furnished in terms of mean values and standard deviations. Along with such noise data, the required signal-to-noise ratios for different types of service are also given.

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Section: Measurementsmentioning

confidence: 99%

Atmospheric noise data for tropical regions

Aiya¹

1979

Radio Science

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“…This will arise because only one noise grade (at 1 MHz) is given [ CCIR, 1964] for a place and the noise at other frequencies is obtained from the set of frequency curves. The limitations of this procedure have previously been pointed out by Joglekar [1970]. From the studies of correlation between atmospheric noise at different frequencies he concluded that "As the frequency separation increases the correlation decreases.…”

Section: The Physical Explanation In the Previous Section Shows The Ementioning

confidence: 99%

Worldwide variation in atmospheric noise intensities with sunspot number: An in‐depth look at the 20–24 hour seasonal time block

Joglekar¹,

Sathiamurthy²

1975

Radio Science

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Comparisons of the variation of atmospheric radio noise intensities for 20–24 hr to sunspot numbers have been completed. Statistical dependence between the noise intensities and sunspot numbers was found for different seasons at a number of frequencies for many locations in the global network of ARN‐2 noise recorders. The noise intensities generally tended to decrease with sunspot number in the range from 50 kHz to 5 MHz, which is presumed to be due to increases in residual ionospheric absorption during nighttime. At frequencies greater than 5 MHz, noise intensities increased with sunspot number in many cases, which would be expected from our present knowledge of ionospheric behavior in the HF range. By convention, CCIR treats year‐to‐year variation in the noise intensities as random and includes them in the prediction uncertainty σ Fam (for which one value is given at a frequency for a seasonal time block for all locations) in system performance evaluation. An error analysis on a global basis shows that a large portion of the year‐to‐year variability is due to sunspot variation. This suggests the possibility of improved noise estimates.

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Short Term Predictions of Atmospheric Noise Levels

Joglekar

1973

IETE Journal of Research

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Correlation Between Atmospheric Noise Levels at Different Frequencies

Cited by 10 publications

References 7 publications

Atmospheric noise data for tropical regions

Atmospheric noise data for tropical regions

Worldwide variation in atmospheric noise intensities with sunspot number: An in‐depth look at the 20–24 hour seasonal time block

Short Term Predictions of Atmospheric Noise Levels

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