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Applying the recently emerged technique‎, ‎MIMO (Multiple Input Multiple Output) to PCL (Passive Coherent‎ ‎Location) is expected to improve performance of localization schemes‎. ‎In this paper‎, ‎we explore the‎ ‎application of MIMO technology to PCL schemes and see how it improves the spatial diversity of such systems‎. ‎Specifically‎, ‎we use the DVB-T stations as the‎ ‎illuminators of opportunity in the simulations‎, ‎mainly because of their unique features which‎ ‎make them quite suitable for both MIMO and PCL application as will be demonstrated in this‎ ‎paper‎. ‎In addition‎, ‎we address the key problem of finding optimum locations for placement of receive antennas‎.

The authors deal with the robust design of multiple-input–multiple-output (MIMO) space–time transmit code (STTC) and space–time receive filter (STRF) for a point-like target embedded in signal-dependent interference. Specifically, they assume that the radar exploits knowledge provided by dynamic environmental database, to roughly predict the actual scattering scenario. Then, they devise an iterative method to optimise the (constrained) STTC and the (constrained) STRF which sequentially improves the worst-case (over interfering scatterers statistics) signal-to-interference-plus-noise ratio (SINR). Each iteration of the algorithm is handled via solving two (hidden) convex optimisation problems. The resulting computational complexity is linear with the number of iterations and polynomial with the sizes of the STTC and the STRF. At the analysis stage, they assess the performance of the proposed algorithm in terms of the achieved SINR. They show that properly exploiting the spatial degrees of freedom offered by the MIMO system, it is possible to obtain considerable SINR gains with respect to the conventional single-input–single-output system. Moreover, their results highlight the capability of the proposed method to robustify the performance of the designed system against possible knowledge inaccuracies.