Application of Adaptive Pulse Compression in Cluttered Radar Cross Section Measurements

Abstract

This article discusses a post-processing method to achieve highly accurate radar cross section (RCS) measurements in challenging test environments. In the ideal RCS measurement setup, the only received signal is the reflection from the object under test (OUT). However, this scenario is often not realizable in practice as outside measurements suffer from a multitude of scattering objects beyond the OUT, and even anechoic chambers have nonnegligible multipath clutter. Time-gating has been shown to be a powerful post-processing clutter suppression tool by temporally filtering any undesired return signals. However, this technique is only sufficient when there is ample spacing between the OUT and undesired return signals or when the sidelobes of one scatterer do not mask the return of a smaller nearby scatterer in the time domain. In the latter scenario, traditional time-gating techniques cannot separate the sidelobes from a nearby dominant scatterer overlapping with the main lobe of the OUT, and the RCS of the OUT cannot be extracted accurately. By applying the proposed stepped frequency continuous wave (SFCW) adaptive pulse compression (APC) algorithm, a range-dependent filter is created to iteratively estimate the range profile and suppress sidelobes allowing for temporal separation of the scatterers and accurate RCS estimation. To validate the concept, the RCS of a 15.2 cm sphere is extracted in two measurement configurations (with and without a large nearby dominating scatterer). The traditional matched filter data processing accuracy is compared to the proposed APC technique. Implementation of APC in post-processing yields a 71.2% improvement in average RCS error compared to traditional processing in the sphere-only measurement and an 88.2% improvement in the presence of a metal plate.