A Novel MIMO Radar Approach Based on Sparse Sensing and Matrix Completion

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In both civilian and military applications, there is increasing interest in networked radars which are inexpensive and easily deployable, while at the same time enabling reliable surveillance of an area. Examples include radar systems consisting of transmit and receive antennas placed on the nodes of a wireless sensor network, on backpacks, or on cars. The transmit antennas transmit probing waveforms. By jointly processing the signals from all receive antennas the desired target parameters can be extracted. This processing can be done at a fusion center, which collects the measurements of all receive antennas. Reliable surveillance requires collection, communication and fusion of vast amounts of data from various antennas, a task that is expensive and power consuming. This project proposes a novel approach for substantially reducing the amount of data that need to be communicated to a fusion center, while ensuring high target detection and estimation performance.Multiple-input multiple-output (MIMO) radars have received considerable recent attention as they can achieve superior resolution. The proposed project will investigate a novel networked MIMO radar system that relies on advanced signal processing techniques, in particular, sparse sensing and matrix completion, in order to achieve a tradeoff between the competing requirements of reliability and cost. In particular, the goal is to achieve high resolution in the angle, Doppler and range space, while limiting the amount of data measured and forwarded by each receive antenna through the network. Unlike previously developed compressive sensing based MIMO radars, the proposed approach will not require grid discretization and thus will be more robust. The project will: (i) develop theoretical results on target recoverability and performance guarantees for matrix completion applied to MIMO radars. Insight from the analysis will be used to design new radar configurations that have improved performance; (ii) develop decentralized algorithms for implementing matrix completion, so that the proposed radar system can be implemented in a distributed fashion without the need for a fusion center; (iii) investigate the potential of the proposed scheme for spectrum sharing between radars and communication systems; (iv) investigate the possibility of further performance improvement by exploiting node mobility and optimal node placement though motion control.