For some applications, data burden can become a problem if the system needs to resolve targets accurately. Passive coherent location using digital video broadcast signals is not an exception: large amounts of data need to be acquired, transferred, and stored for processing. Redundancy in signals can be exploited thanks to compressive sensing by means of sparsity in a given domain, random down-sampling the received signal and discarding unnecessary data. However, not all applications are suitable and may not be robust enough. This paper will present preliminary results of passive coherent location and compressive sensing based on signal modelling and Monte-Carlo simulations.