Compressive sensing-based 3D signal extraction for MIMO passive radar using OFDM waveforms

Abstract

In this paper three-dimensional channel estimation for passive radar using Orthogonal Frequency Division Multi-plexing(OFDM) waveforms is proposed. The passive radar has gained plenty of interests for the covert operations while the detection of the target signal is one of its issues. In modern communication systems, Single Frequency Network (SFN) has been used. This leads to the difficulty to determine the sources of the incoming signals providing that one frequency is transmitted. Instead of employing the MIMO radar with widely separated antennas, this paper uses the MIMO receiver with co-located antennas to extend two-dimensional OFDM signal in the angular domain. The channel estimates consisting of time delay, Doppler frequency and angle of arrivals are derived. Compressive sensing is applied to reduce the number of measurements of the observation matrix. The li-SVD, which is the method employing multiple time samples, has been used to reconstruct the sparse signal in comparison with a single time sample basis pursuit. The simulations show that the proposed method performs well in terms of detecting and extracting the target parameters.