Aerospace and Electronic Systems Magazine October 2017 - 28

Knowledge-Aided Processing for MER

Figure 4.

Comparison of LIDAR data to the optical image (from the U.S. Geological Survey) of the MER Phase I measurement site. (a) LIDAR image. (b) Optical
image.

MER PROCESSING ARCHITECTURE
During the MER Phase II effort, three significantly different approaches for MER tracking were investigated. A simple, top-level
view of the best performing approach is provided in Figure 5. This
flow diagram was constructed to illustrate MER-specific issues.
Numerous algorithms associated with standard GMTI processing, such as pulse compression, calibration, Doppler processing,
space-time adaptive processing (STAP), detection, clustering, and
angle estimation, reside in the single block of Figure 5 labeled ra-

dar signal processing. This block also contains several nonstandard
algorithms required to mitigate radar-specific artifacts, as well as
enhancements to STAP to improve its performance in an urban environment. The output of this block consists of a set of detections
for each coherent processing interval (CPI) that is characterized by
measurement-space quantities such as range, Doppler, and angle.
In general, measurement-space tracks are not sufficient for the goal
of persistent surveillance. To convert these quantities into the desired Cartesian space, a ray tracer is employed to solve the inverse
problem. As shown in Figure 5, a ray tracer is also used to solve

Figure 5.

Top-level view of urban GMTI signal processing architecture developed during MER Phase II.

28

IEEE A&E SYSTEMS MAGAZINE

OCTOBER 2017



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