Implementation of Generalized Detector in MIMO Radar Systems

In this paper, we consider the problem of multiple-input multiple-output (MIMO) radars employing the generalized detector (GD) based on the generalized approach to signal processing in noise (GASP) and using the space-time coding to achieve a desired diversity. To that end, we derive a suitable GD structure after briefly outlining the model of the received target return signal. GD performance is expressed in closed form as a function of the clutter statistical properties and of the space-time code matrix. We investigate a particular case when GD requires a priori knowledge of the clutter covariance, i.e., the decision statistics under the null hypothesis of “a no” target is an ancillary statistic in the sense that it depends on the actual clutter covariance matrix but its probability density function (pdf) is functionally independent of such a matrix. Therefore, threshold setting is feasible with no a priori knowledge as to the clutter power spectrum. As to the detection performance, a general integral form of the probability of detection is provided, holding independent of the searched object fluctuation model. The formula is not analytically manageable, nor does it appear to admit general approximate expressions, which allow giving an insightful look in the MIMO radar system behaviour. We thus restrict our attention to the case of Rayleigh-distributed target attenuation (Swerling-1 model). To code construction we use an information-theoretic approach and compare conditions for code optimality with ones for classical Chernoff bound. This approach offers a methodological framework for space-time coding in MIMO radar systems constructed based on GASP, as well as simple and intuitive bounds for performance prediction. Key-Words: Generalized detector, multiple-input multiple-output (MIMO), Rayleigh fading, Chernoff bound, generalized approach to signal processing, Swerling-1 model.