The Army Research Laboratory (ARL) has, in the past, demonstrated the effectiveness of low frequency,
ultrawideband radar for detection of slow-moving targets located behind walls. While these initial results
were promising, they also indicated that sidelobe artifacts produced by moving target indication (MTI)
processing could pose serious problems. Such artifacts induced false alarms and necessitated the
introduction of a tracker stage to eliminate them. Of course, the tracker algorithm was also imperfect, and
it tended to pass any persistent, nearly collocated false alarms.
In this work we describe the incorporation of a sidelobe-reduction technique-the randomized linear
receiver array (RA)-into our MTI processing chain. To perform this investigation, we leverage data
collected by ARL's synchronous impulse reconstruction (SIRE) radar. We begin by calculating MTI
imagery using both the non-random and randomized array methods. We then compare the sidelobe levels
in each image and quantify the differences. Finally, we apply a local-contrast target detection algorithm
based on constant false alarm rate (CFAR) principles, and we analyze probabilities of detection and false
alarm for each MTI image.