اشترك بالحزمة الذهبية واحصل على وصول غير محدود شمرا أكاديميا
تسجيل مستخدم جديدReference antenna techniques for canceling radio frequency interference due to moving sources
142
0
0.0
(
0
)
اسأل ChatGPT حول البحث
ﻻ يوجد ملخص باللغة العربية
We investigate characteristics of radio frequency interference (RFI) signals that can affect the excision potential of some interference mitigation algorithms. The techniques considered are those that modify signals from auxiliary reference antennas to model and cancel interference from an astronomical observation. These techniques can be applied in the time domain, where the RFI voltage is modeled and subtracted from the astronomy signal path (adaptive noise canceling), or they can be applied to the autocorrelated and cross-correlated voltage spectra in the frequency domain (postcorrelation canceling). For ideal receivers and a single, statistically stationary interfering signal, both precorrelation and postcorrelation filters can result in complete cancellation of the interference from the observation. The postcorrelation method has the advantage of being applied on tens or hundreds of millisecond timescales rather than tens or hundreds of nanosecond timescales. However, this can be a disadvantage if the RFI transmitter location is changing, since the cross-correlated power measurements which link the interference power in the astronomy and reference signal paths can decorrelate. If the decorrelation is not too severe, it can be allowed for, at the expense of a noise increase. The time domain adaptive cancelers are allowed to slightly vary their internal coefficients and adapt to changing phases during the integrations, which means that they avoid the decorrelation problem. However, the freedom to adapt also results in a noise increase. In this paper the ability of both types of cancelers to excise interference originating from a moving source is compared. The cancelers perform well on both observed and simulated data, giving complete cancellation.
قيم البحث
اقرأ أيضاً
Radio frequency interference (RFI) detection and excision are key steps in the data-processing pipeline of the Five-hundred-meter Aperture Spherical radio Telescope (FAST). Because of its high sensitivity and large data rate, FAST requires more accur
ate and efficient RFI flagging methods than its counterparts. In the last decades, approaches based upon artificial intelligence (AI), such as codes using convolutional neural networks (CNNs), have been proposed to identify RFI more reliably and efficiently. However, RFI flagging of FAST data with such methods has often proved to be erroneous, with further manual inspections required. In addition, network construction as well as preparation of training data sets for effective RFI flagging has imposed significant additional workloads. Therefore, rapid deployment and adjustment of AI approaches for different observations is impractical to implement with existing algorithms. To overcome such problems, we propose a model called RFI-Net. With the input of raw data without any processing, RFI-Net can detect RFI automatically, producing corresponding masks without any alteration of the original data. Experiments with RFI-Net using simulated astronomical data show that our model has outperformed existing methods in terms of both precision and recall. Besides, compared with other models, our method can obtain the same relative accuracy with fewer training data, thus reducing the effort and time required to prepare the training data set. Further, the training process of RFI-Net can be accelerated, with overfittings being minimized, compared with other CNN codes. The performance of RFI-Net has also been evaluated with observing data obtained by FAST and the Bleien Observatory. Our results demonstrate the ability of RFI-Net to accurately identify RFI with fine-grained, high-precision masks that required no further modification.
In radio astronomy, reference signals from auxiliary antennas that receive only the radio frequency interference (RFI) can be modified to model the RFI environment at the astronomy receivers. The RFI can then be canceled from the astronomy signal pat
hs. However, astronomers typically only require signal statistics. If the RFI statistics are changing slowly, the cancellation can be applied to the signal correlations at a much lower rate than is required for standard adaptive filters. In this paper we describe five canceler setups; precorrelation and postcorrelation cancelers that use one or two reference signals in different ways. The theoretical residual RFI and added noise levels are examined and are demonstrated using microwave television RFI at the Australia Telescope Compact Array. The RFI is attenuated to below the system noise, a reduction of at least 20 dB. While dual-reference cancelers add more reference noise than single-reference cancelers, this noise is zero-mean and only adds to the system noise, decreasing the sensitivity. The residual RFI that remains in the output of single-reference cancelers (but not dual-reference cancelers) sets a nonzero noise floor that does not act like random system noise and may limit the achievable sensitivity. Thus, dual-reference cancelers often result in superior cancellation. Dual-reference precorrelation cancelers require a double-canceler setup to be useful and to give equivalent results to dual-reference postcorrelation cancelers.
The frequencies of interest for redshifted 21 cm observations are heavily affected by terrestrial radio-frequency interference (RFI). We identify the McGill Arctic Research Station (MARS) as a new RFI-quiet site and report its RFI occupancy using 122
hours of data taken with a prototype antenna station developed for the Array of Long-Baseline Antennas for Taking Radio Observations from the Sub-Antarctic. Using an RFI flagging process tailored to the MARS data, we find an overall RFI occupancy of 1.8% averaged over 20-125 MHz. In particular, the FM broadcast band (88-108 MHz) is found to have an RFI occupancy of at most 1.6%. The data were taken during the Arctic summer, when degraded ionospheric conditions and an active research base contributed to increased RFI. The results quoted here therefore represent the maximum-level RFI environment at MARS.
Positions and proper motions of Gaia sources are expressed in a reference frame that ideally should be non-rotating relative to distant extragalactic objects, coincident with the International Celestial Reference System (ICRS), and consistent across
all magnitudes. For sources fainter than 16th magnitude this is achieved thanks to Gaias direct observations of quasars. At brighter magnitudes it is difficult to validate the quality of the reference frame due to the scarcity of comparison data. This paper examines the use of VLBI observations of radio stars to determine the spin and orientation of the bright reference frame of Gaia. Simultaneous estimation of the six spin and orientation parameters makes optimal use of VLBI data and makes it possible to include even single-epoch VLBI observations in the solution. The method is applied to Gaia Data Release 2 (DR2) using published VLBI data for 41 radio stars. Results for the 26 best-fitting sources indicate that the bright reference frame of Gaia DR2 is rotating relative to the faint quasars at a rate of about 0.1 mas/yr, significant at 2-sigma level. This supports a similar conclusion based on a comparison with stellar positions in the Hipparcos frame. The accuracy is currently limited by the small number of radio sources used, by uncertainties in the Gaia DR2 proper motions, and by the astrophysical nature of the radio stars. While the origin of the indicated rotation is understood and can be avoided in future data releases, it remains important to validate the bright reference frame of Gaia by independent observations. This can be achieved using VLBI astrometry, which may require re-observing the old sample of radio stars as well as measuring new objects. The unique historical value of positional measurements is stressed and VLBI observers are urged to ensure that relevant positional information is preserved for the future.
The redshifted 21 cm line of neutral hydrogen is a promising probe of the Epoch of Reionization (EoR). However, its detection requires a thorough understanding and control of the systematic errors. We study two systematic biases observed in the LOFAR
EoR residual data after calibration and subtraction of bright discrete foreground sources. The first effect is a suppression in the diffuse foregrounds, which could potentially mean a suppression of the 21 cm signal. The second effect is an excess of noise beyond the thermal noise. The excess noise shows fluctuations on small frequency scales, and hence it can not be easily removed by foreground removal or avoidance methods. Our analysis suggests that sidelobes of residual sources due to the chromatic point spread function and ionospheric scintillation can not be the dominant causes of the excess noise. Rather, both the suppression of diffuse foregrounds and the excess noise can occur due to calibration with an incomplete sky model containing predominantly bright discrete sources. We show that calibrating only on bright sources can cause suppression of other signals and introduce an excess noise in the data. The levels of the suppression and excess noise depend on the relative flux of sources which are not included in the model with respect to the flux of modeled sources. We discuss possible solutions such as using only long baselines to calibrate the interferometric gain solutions as well as simultaneous multi-frequency calibration along with their benefits and shortcomings.
سجل دخول لتتمكن من نشر تعليقات
التعليقات
جاري جلب التعليقات
سجل دخول لتتمكن من متابعة معايير البحث التي قمت باختيارها
