Reference Signal Fractionation for LTE-Based Passive Radar Facing MIMO and OFDMA Challenges

As a potential alternative for low-altitude surveillance, the long term evolution-based passive radar (LTEPR) has received worldwide attention due to the wide availability and large bandwidth of LTE. The multiple input multiple output (MIMO) and orthogonal frequency division multiple access (OFDMA) techniques of LTE mean that the radio resource is randomly allocated and multiple signals are transmitted via multiple antennas. The received reference signal of LTEPR is the mixture of multiple signals and discontinous over time. Target SNR loss easily happens if this reference signal is used in matched filtering. However, open publications rarely consider to fractionate reference signal, that is, separating and refining multiple transmitting signals meanwhile dealing with MIMO and OFDMA. This article proposes a complete procedure of reference signal fractionation for LTEPR, in which a heuristic channel estimator is proposed to solve estimation error caused by virtual subcarriers (VSs), and a supervised strategy is proposed to identify the active radio resource from noise. The MIMO technique is decoded after channel equalization. The numerical simulations prove that the heuristic channel estimator is unbiased and the supervised strategy largely reduces the false alarm and missed alarm caused by OFDMA. The real data tests prove that the proposed procedure is feasible and practical to recover multiple transmitting signals.