Improving BEM channel estimation for airborne passive radar reference signal reconstruction

In this article, we consider an airborne passive radar using ODFM signals of opportunity in a Single Frequency Network (SFN) environment. The long and sparse multipath fading channel and the mobility of the receiver can deeply alterate the signal and therefore degrade the decoding processing. Classic methods experience difficulties in dealing with such channel impacts. Consequently we present a Basis Expansion Model (BEM) based channel estimation method. We also propose to combine it with the Minimum Description Length (MDL) and ESPRIT algorithms to get a prior information. Simulation results emphasize the benefits of using the BEM and confirm the necessity to have an a priori knowledge of the channel.