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Rapid Prototyping for Radio-Frequency Geolocation Applications
Scott Briles, PhD
Los Alamos National Laboratory
Los Alamos, NM, 87545, USA
(505) 667-4298
briles(alanl.gov
Dakx Turcotte
Lyrtech Inc.
Quebec City, Canada
(418) 877-4644
dakx.turcotte(cIyrtech.comJoseph Arrowood, PhD
Los Alamos National Laboratory
Los Alamos, NM, 87545, USA
(505) 667-4818
arrowood(dlanI.gov
Etienne Fiset
Lyrtech Inc.
Quebec City, Canada
(418) 877-4644
etienne.fiset'lIyrtech.comThomas Braun
Los Alamos National Laboratory
Los Alamos, NM, 87545, USA
(505) 665-2830
tbraun(@Ianl.govAbstract: Previous space-to-ground, single-platform
geolocation experiments exploiting time-difference-of arrival (TDOA)
via interferometry were successful at separating and quantitatively
characterizing interfering radio frequency (RF) signals from expected
RF transmissions. Much of the success of these experiments rested
on the use of embedded processors to perform the required signal
processing. The experiments handled data in a "snapshot" fashion:
digitized data was collected, the data was processed via a digital
signal processing (DSP) microprocessor to yield differential phase
measurements, and these measurements were transmitted to the
Earth for geolocation processing.
With the utilization of FPGAs (field programmable gate arrays) for
the intensive number-crunching algorithms, the processing of
streaming real-time data is feasible for bandwidths on the order of 20
MHz. By partitioning the signal processing algorithm so there is a
significant reduction in the data rate as data flows through the FPGA,
a DSP microprocessor can now be employed to perform further
decision-oriented processing on the FPGA output. This hybrid
architecture, employing both FPGAs and DSPs, typically requires an
expensive and lengthy development cycle. However, the use of
graphical development environments with auto-code generation and
hardware-in-the-loop testing can result in rapid prototyping for
geolocation experiments, which enables adaptation to emerging
signals of interest in a cost and time effective manner.
Introduction: Los Alamos National Laboratory is
charged with certain aspects of treaty monitoring
with respect to nuclear nonproliferation activities.
In particular, Los Alamos is interested in detecting
any nuclear testing that may occur and uses
several sensing methodologies to perform this
detection. One of these methods is to look for the
radio frequency (RF) emissions that accompany
any nuclear device detonation. Not only is it
important to detect these detonations, it is
imperative to geolocate where they took place.
When multiple sensors across multiple platforms
pre available, cross-ambiguity function (CAF)
processing may be implemented to use any time-
difference of arrival (TDOA) or frequency
gfference of arrival (FDOA) measurements to
Efectively triangulate where the signal originated.When only one platform is available - due to cost
or other factors - one would like to have multiple
sensors on board to determine the TDOA via the
phase information for the varying input signals. In
essence, differential phase (A0) is measured
between adjacent sensors and this information,
combined with measurements of the incoming
frequency and knowledge of the sensor baseline
distances allows one to determine a set of
potential location points for the signal of interest.
This process is called interferometry or short
baseline TDOA processing.
The purpose of this paper is to demonstrate rapid
prototyping techniques for this application. In
particular, the Mathworks' Simulink and Matlab
commercial software packages will provide an
interface to graphically implement a short baseline
interferometer for simulation, fixed point testing,
hardware-in-the-loop testing and eventual
deployment. For cost saving, both deployment
and prototyping are to be performed with the
same hardware platform from Lyrtech. Lyrtech
has developed a heterogeneous system with
FPGAs and DSPs and created the necessary
software hooks to integrate their product into the
Simulink environment.
Interferometry: The cost of putting multiple
satellites in orbit precludes using the CAF
processing from a long baseline TDOA/FDOA
perspective. Therefore, geolocation from a single
platform using _ iple sensors is desired. The
math behind [Diic interferometry is simple.
Figure 1 details Lme configuration for a two sensor
array with a separation of D between the sensors
and assuming far field for the emitter. The goal isS a
'I c
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Synchrotron-based high-pressure research in materials science, article, Date Unknown; [Los Alamos, New Mexico]. (https://digital.library.unt.edu/ark:/67531/metadc934902/m1/1/: accessed March 28, 2024), University of North Texas Libraries, UNT Digital Library, https://digital.library.unt.edu; crediting UNT Libraries Government Documents Department.