CFAR Detection applied to MIMO Radar in a Simulated Maritime Surveillance Scenario

In this paper, a multiple-input multiple-output (MIMO) radar with separated antennas is simulated in a maritime surveillance scenario to detect extended naval targets. The simulator first extracts the main scattering elements of the targets, then it generates the signals transmitted/received by each bistatic radar node and it evaluates the MIMO cross-ambiguity function in the Cartesian search space. Moreover, a modified version of the cell-averaging constant false alarm rate (CA- CFAR) detection algorithm is applied, in which the noise level is evaluated from the bistatic range cells around the cell-under-test. Preliminary results demonstrate the improvement granted by this training method with respect to the rectangular window in terms of reduced number of false alarms. Far from being exhaustive, this paper addresses some of the signal processing issues that rise from a real maritime surveillance scenario, in which a MIMO radar with widely separated antennas and based on photonic technology will be operated.