Nested sparse sampling and co-prime sampling in sense-through-foliage target detection

This paper firstly introduces nested sampling and co-prime sampling, which were proposed recently, but have never been applied to real world target detection. We apply nested sampling and co-prime sampling to target detection in UWB radar sensor networks (RSN), based on a differential approach. The non-stationary UWB signal needs to be decomposed into several approximate wide sense stationary (WSS) signals so that nested sampling could be used in this situation. We also compare the performance of nested sampling and co-prime sampling against uniform under-sampling. The results show that in terms of good quality data and poor quality data, both nested sampling and co-prime sampling work better.