skip to main content


Title: Bistatic Observations With SuperDARN HF Radars: First Results
Abstract

Super Dual Auroral Radar Network (SuperDARN) radars operate in a coordinated but monostatic configuration whereby high‐frequency (HF) signals scattered from ionospheric density irregularities or from the surface of the Earth return to the transmitting radar where Doppler parameters are then acquired. A bistatic arrangement has been developed for SuperDARN radars in which HF signals transmitted from one radar are received and analyzed by another radar that is separated by a large distance (>1,000 km). This new capability was developed and tested on radars located in Oregon and Kansas. Numerous 3‐day bistatic campaigns have been conducted over a period extending from September 2019 through March 2020. During these campaigns three distinct bistatic propagation modes have been identified including a direct mode in which signals are transmitted and received through the radar side lobes. Direct mode signals propagate along the great‐circle arc connecting the two bistatic radar sites, reflecting from the ionosphere at bothEregion andFregion altitudes. Two additional modes are observed in which HF signals transmitted from one radar scatter from either ionospheric density irregularities or from the surface of the Earth before propagating to the bistatic receiving radar. Ray tracing simulations performed for examples of each mode show good agreement with observations and confirm our understanding of these three bistatic propagation modes. Bistatic campaigns continue to be scheduled in order to improve technical aspects of this new capability, to further explore the physical processes involved in the propagation and scattering of HF bistatic signals and to expand the coverage of ionospheric effects that is possible with SuperDARN.

 
more » « less
Award ID(s):
1934997 1935110
NSF-PAR ID:
10377804
Author(s) / Creator(s):
 ;  ;  ;  ;  ;  ;  ;  
Publisher / Repository:
DOI PREFIX: 10.1029
Date Published:
Journal Name:
Radio Science
Volume:
55
Issue:
8
ISSN:
0048-6604
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
More Like this
  1. Abstract

    Propagation of high‐frequency (HF) radio signals is strongly dependent on the ionospheric electron density structure along a communications link. The ground‐based, HF space weather radars of the Super Dual Auroral Radar Network (SuperDARN) utilize the ionospheric refraction of transmitted signals to monitor the global circulation ofE‐ andF‐region plasma irregularities. Previous studies have assessed the propagation characteristics of backscatter echoes from ionospheric irregularities in the auroral and polar regions of the Earth's ionosphere. By default, the geographic location of these echoes are found using empirical models which estimate the virtual backscattering height from the measured range along the radar signal path. However, the performance of these virtual height models has not yet been evaluated for mid‐latitude SuperDARN radar observations or for ground scatter (GS) propagation modes. In this study, we derive a virtual height model suitable for mid‐latitude SuperDARN observations using 5 years of data from the Christmas Valley East and West radars. This empirical model can be applied to both ionospheric and GS observations and provides an improved estimate of the ground range to the backscatter location compared to existing high‐latitude virtual height models. We also identify a region of overlapping half‐hopF‐region ionospheric scatter and one‐hopE‐region GS where the measured radar parameters (e.g., velocity, spectral width, elevation angle) are insufficient to discriminate between the two scatter types. Further studies are required to determine whether these backscatter echoes of ambiguous origin are observed by other mid‐latitude SuperDARN radars and their potential impact on scatter classification schemes.

     
    more » « less
  2. Abstract

    The Super Dual Auroral Radar Network (SuperDARN) is a network of High Frequency (HF) radars that are typically used for monitoring plasma convection in the Earth's ionosphere. A majority of SuperDARN backscatter can broadly be divided into three categories: (a) ionospheric scatter due to reflections from plasma irregularities in the E and F regions of the ionosphere, (b) ground scatter caused by reflections from the ground/sea surface following reflection in the ionosphere, and (c) backscatter from meteor trails left by meteoroids as they enter the Earth's atmosphere. Due to the complex nature of HF propagation and mid‐latitude electrodynamics, it is often not straightforward to distinguish between different modes of backscatter observed by SuperDARN. In this study, we present a new two‐stage machine learning algorithm for identifying different backscatter modes in SuperDARN data. In the first stage, a neural network that “mimics” ray‐tracing is used to predict the probability of ionospheric and ground scatter occurring at a given location along with parameters like the elevation angles, reflection heights etc. The inputs to the network include parameters that control HF propagation, such as signal frequency, season, UT time, and geomagnetic activity levels. In the second stage, the output probabilities from the neural network and actual SuperDARN data are clustered together to determine the category of the backscatter. Our model can distinguish between meteor scatter, 1/2 hop E‐/F‐region ionospheric as well as ground/sea scatter. We validate our model by comparing predicted elevation angles with those measured at a SuperDARN radar.

     
    more » « less
  3. The Super Dual Auroral Radar Network (SuperDARN) is an international network of ground-based, space weather radars which have operated continuously in the Arctic and Antarctic regions for more than 30 years. These high-frequency (HF) radars use over-the-horizon (OTH) radio wave propagation to detect ionospheric plasma structures across ranges of several thousand kilometers (km). As a byproduct of this technique, the transmitted radar signals frequently reflect from the Earth's surface and can be observed as ground backscatter echoes. The monthly files in this dataset contain maps of daily ground backscatter observations from the Clyde River (CLY) SuperDARN HF radar binned onto an equal-area 24 km grid. The CLY radar is located in Clyde River, Nunavut (70.49°N, 68.50°W) and is operated by the University of Saskatchewan (Principal Investigator: Kathryn A. McWilliams, kathryn.mcwilliams@usask.ca) with funding support from the Canada Foundation for Innovation, the Province of Saskatchewan, and the Canadian Space Agency. 
    more » « less
  4. The Super Dual Auroral Radar Network (SuperDARN) is an international network of ground-based, space weather radars which have operated continuously in the Arctic and Antarctic regions for more than 30 years. These high-frequency (HF) radars use over-the-horizon (OTH) radio wave propagation to detect ionospheric plasma structures across ranges of several thousand kilometers (km). As a byproduct of this technique, the transmitted radar signals frequently reflect from the Earth's surface and can be observed as ground backscatter echoes. The monthly files in this dataset contain maps of daily ground backscatter observations from the Goose Bay (GBR) SuperDARN HF radar binned onto an equal-area 24 km grid. The GBR radar is located in Labrador, Canada (53.32°N, 60.46°W) and is operated by Virginia Tech (Principal Investigator: J. Michael Ruohoniemi, mikeruo@vt.edu) with funding support from the National Science Foundation. 
    more » « less
  5. The Super Dual Auroral Radar Network (SuperDARN) is an international network of ground-based, space weather radars which have operated continuously in the Arctic and Antarctic regions for more than 30 years. These high-frequency (HF) radars use over-the-horizon (OTH) radio wave propagation to detect ionospheric plasma structures across ranges of several thousand kilometers (km). As a byproduct of this technique, the transmitted radar signals frequently reflect from the Earth's surface and can be observed as ground backscatter echoes. The monthly files in this dataset contain maps of daily ground backscatter observations from the Iceland West (ICW) SuperDARN HF radar binned onto an equal-area 24 km grid. The ICW radar is located in Þykkvibær, Iceland (63.77°N, 20.54°W) and is operated by Dartmouth College (Principal Investigator: Simon G. Shepherd, simon.g.shepherd@dartmouth.edu) with funding support from the National Science Foundation. 
    more » « less