Sparsity and compressive sensing of sense-through-foliage radar signals

Motivated by recent advances on Compressive Sensing (CS), we study the sparsity of sense-through-foliage radar signals. Based on CLEAN method, we obtain the impulse response for sense-through-foliage communication channels for three different radars, 200MHz, 400MHz, and UWB radars. Channel impulse responses for the above three different kinds of channels demonstrate that the sense-through-foliage signals are very sparse, which means CS is possible to be applied to sense-through-foliage radar signals to tremendously reduce the sampling rate. We apply CS and linear programming to sparse signal compression and recovery, and it turns out that we could achieve compression ratio of 32:1 with perfect recovery for the UWB radar signals.