An efficient implementation of the low-complexity multi-coset sub-Nyquist wideband radar electronic surveillance

The problem of efficient sampling of wideband radar signals for Electronic Surveillance (ES) using a parallel sampling structure will be investigated in this paper. Wideband radio frequency sampling, which is a necessary component of the modern digital radar surveillance systems, needs a sampling rate at least twice the maximum frequency of signals, i.e. Nyquist rate, which is generally very high. Designing an analog to digital converter which works with such a high sampling rate is difficult and expensive. The standard wideband ES receivers use the rapidly swept superheterodyne technique, which selects a subband of the spectrum at a time, while iterating through the whole spectrum sequentially. Such a technique does not explore the underlying structure of input RF signals. When the signal is sparsely structured, we can use the fact that signals do not occupy the whole spectrum. There indeed exists a parsimonious structure in the time-frequency domain in radar ES signals. We here use a recently introduced low-complexity sampling system, called LoCoMC [1], which is inspired by the compressive sampling (CS) of sparse signals and it uses the multi-coset sampling structure, while it does not involve a computationally expensive reconstruction step. A new implementation technique is here introduced, which further reduces the computational cost of the reconstruction algorithm by combining two filters, while improving the accuracy by implicitly implementing an infinite length filter. We also describe the rapidly swept superheterodyne receiver and compare it with the LoCoMC algorithm. In a contrast to the former technique, LoCoMC continuously monitors the spectrum, which makes it much more robust in the short pulse detection.