Passive MIMO radar detection exploiting known format of the communication signal observed in colored noise with unknown covariance matrix

Abstract In passive multiple input multiple output (MIMO) radar, the transmit signals of the noncooperative illuminators of opportunity are usually not completely known. However, they are often standard communication signals with some specific signal structure. Exploiting such information, the detection performance of passive MIMO radar can be improved. In this paper we derive a generalized likelihood ratio test (GLRT) for passive MIMO radar detection when the covariance matrix of the colored Gaussian noise is unknown and the structure of the transmit signal is known but it contains some unknown information bits. Moreover, a model which employs a reasonable approximation for some practical scenarios while requiring only a limited number of training samples is also considered, and a GLRT for this model is also derived. Our tests are shown to be constant false alarm rate (CFAR), and their performance approaches the optimum performance with known signal structure and known covariance matrix when the number of training samples is increased. Finally, several numerical examples are presented to demonstrate the effectiveness of the proposed method.