A method has been designed for using multiple independent stations to discriminate fast transient radio sources from local anomalies, such as antenna noise or radio frequency interference (RFI). This can improve the sensitivity of incoherent detection for geographically separated stations such as the very long baseline array (VLBA), the future square kilometer array (SKA), or any other coincident observations by multiple separated receivers.
The transients are short, broadband pulses of radio energy, often just a few milliseconds long, emitted by a variety of exotic astronomical phenomena. They generally represent rare, high-energy events making them of great scientific value. For RFI-robust adaptive detection of transients, using multiple stations, a family of algorithms has been developed. The technique exploits the fact that the separated stations constitute statistically independent samples of the target. This can be used to adaptively ignore RFI events for superior sensitivity. If the antenna signals are independent and identically distributed (IID), then RFI events are simply outlier data points that can be removed through robust estimation such as a trimmed or Winsorized estimator.
The alternative “trimmed” estimator is considered, which excises the strongest n signals from the list of short-beamed intensities. Because local RFI is independent at each antenna, this interference is unlikely to occur at many antennas on the same step. Trimming the strongest signals provides robustness to RFI that can theoretically outperform even the detection performance of the same number of antennas at a single site. This algorithm requires sorting the signals at each time step and dispersion measure, an operation that is computationally tractable for existing array sizes.
An alternative uses the various stations to form an ensemble estimate of the conditional density function (CDF) evaluated at each time step. Both methods outperform standard detection strategies on a test sequence of VLBA data, and both are efficient enough for deployment in real-time, online transient detection applications.
This work was done by David R. Thompson, Kiri L. Wagstaff, and Walid A. Majid of Caltech for NASA’s Jet Propulsion Laboratory. NPO-47678
This Brief includes a Technical Support Package (TSP).
Multiple-Beam Detection of Fast Transient Radio Sources
(reference NPO-47678) is currently available for download from the TSP library.
Don't have an account?
Overview
The document is a Technical Support Package from NASA's Jet Propulsion Laboratory (JPL) detailing advancements in the detection of fast transient radio sources using multiple-beam techniques. Fast transients are short bursts of radio energy, often lasting just a few milliseconds, and are associated with rare astronomical phenomena. Detecting these signals is crucial for understanding high-energy events in the universe.
The work addresses the challenges of identifying these transient signals in radio array data, which often requires real-time data processing. Traditional methods of transient detection involve summing signals from multiple antennas, but this approach can be limited by the presence of radio frequency interference (RFI) and the need for accurate de-dispersion of signals affected by the interstellar medium. The document emphasizes the importance of storing raw antenna data for thorough analysis, as transient events can be fleeting and may be discarded shortly after collection.
A significant focus of the research is on incoherent de-dispersion, which compensates for the frequency-dependent delays caused by the interstellar medium. The dispersion measure (DM) is a key factor in this process, as it quantifies the density of ionized plasma between the source and the receiver. The document outlines the necessity of performing trial de-disperisons across a wide range of DMs to effectively detect transient signals.
The findings presented in the document highlight new approaches that outperform traditional methods by improving the detection of synthetic pulses in multi-station Very Long Baseline Array (VLBA) data. These advancements are particularly relevant for next-generation instruments like the Square Kilometre Array (SKA), which are expected to generate vast amounts of raw data, making efficient transient detection and archiving essential.
The document also acknowledges the contributions of various researchers and institutions, including the National Radio Astronomy Observatory (NRAO) and Curtin University, in supporting the development of the detection techniques and software used in this research.
Overall, this Technical Support Package outlines a significant step forward in the field of radio astronomy, providing insights into the detection of transient signals and the methodologies that enhance the sensitivity and accuracy of these observations.
