Bottomside Ionospheric Inversion using Passive High Frequency Transmissions
Abstract
Funds are provided to develop algorithms and simulations to estimate the vertical ionospheric electron density profile given passively collected HF skywave propagation data from Coastal Ocean Dynamics and Applications Radars (CODARs), which form a suitable single frequency oblique ionospheric sounding. The proposed effort will include a Clemson graduate student and undergraduate students. The proposed effort is divided into two major tasks. Task 1 is to continue ongoing data collection of skywave CODAR transmissions at theClemson Atmospheric Research Laboratory (CARL) from CODAR transmitters located along the East Coast of the U.S. For this task, we will improve the data processing and analysis so we can extract the time series of the skywave propagation link. We will separate multiple cochannel CODAR transmissions by range, polarization state, and number of ionospheric hops. We will further develop algorithms to extract Doppler using standard range-Doppler radar signal processing. Task 2 will focus on developing an inversion algorithmto estimate ionospheric parameters from passively received HF skywave CODAR transmissions. Forthis task, we will couple a parameterized ionospheric model using Chapman layers with an ionospheric ray tracing software package. We will perform the ionospheric parameter estimation as a non-linear least squares problem. We will develop a simulation to generate synthetic CODAR data so we can test the estimation of ionospheric parameters and associated uncertainties for a given set of ionospheric parameters. Using an analytic quasi-parabolic ionospheric model, we will develop suitable initial guesses and investigate using this ionospheric model as a more direct inversion. With assurance that our parameter estimation algorithm functions appropriately, we will apply our methodology to two case studies corresponding to a quiet ionosphere and more disturbed ionospheric conditions.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Aug 05, 2021
- Source ID
- N000142112546
Entities
People
- Stephen Kaeppler
Organizations
- Clemson University
- Office of Naval Research
- United States Navy