(IVAR) - Final Report - Strategic Environmental Research and ...

6.1.2 Qualitative Performance Criteria
6.1.2.1 Automates Real-Time Tracking of Radar Echoes [PA1.2]
Objective
We designed Performance Criterion PA1.2, Automates Real-Time Tracking of Radar Echoes was
to demonstrate that the digital avian radars being evaluated by the IVAR project can automatically
discriminate the echoes of moving targets from the analog waveform data returned by the marine
radars used by most avian radar systems. Our objective was to demonstrate that these systems
can detect and track in real time the same targets that a human operator would detect when
observing the same radar display.
We set the success criterion for the qualitative PA1.2 criterion that the detection and tracking of
these targets would be “Achievable”.
Methods
We chose to demonstrate criterion PA1.2 using the eBirdRad avian radar system because it uses
the same transceiver (Furuno 2155BB) and 4° dish antenna as its analog BirdRad predecessor, but
with the addition of the Accipiter® DRP that performs the automatic detection and tracking
functions. We divided the task of demonstrating that the eBirdRad can automatically track radar
echoes in real time into two segments. For the first segment, Validation by Simulation, we used
an in-house software simulation tool to validate that the automatic tracking algorithms used in
the eBirdRad DRP track sequences of detections are consistent with avian target dynamics. This
simulation tool produces a plot file of the same format as does the DRP when operating in real
time and can be replayed for off-line re-processing (i.e., re-tracking). Thus, our testing
methodology for PA1.2 made use of the actual radar systems under test to validate the capabilities
of the automatic tracking algorithms.
The plots file we simulated for the purpose of this validation includes the following targets and
dynamics:
• A total of twenty (20) simulated targets are “flying” simultaneously, with speeds around
15 m/s – emulating typical bird speeds.
• The targets are organized into four groups with 4 to 6 targets in each group.
• For certain times during the simulation, the targets are far enough apart to simulate a
separated target tracking scenario.
• For certain times during the simulation, targets are crossing to simulate a target-crossing
tracking scenario.
• For certain times during the simulation, targets are converging to simulate a converging
target tracking scenario.
• For certain times during the simulation, targets maneuver to simulate a maneuvering
target tracking scenario.
• For certain times during the simulation, targets are diverging to simulate a diverging
target tracking scenario.
These motion dynamics are consistent with single birds and flocking birds. We designed them to
demonstrate the inherent automatic tracking capabilities of the Multiple Hypothesis Testing
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