New Trends in Coded Waveform Design for Radar Applications

In this lecture, we provide an overview of some recent algorithms for radar waveform design. We first illustrate the concept of matched illumination for optimized target detection and identification. This theory derives the optimized transmission signal and the corresponding receiver response which maximizes the Signal to Noise Ratio (SNR). The second part of the lecture is focused on waveform optimization in the presence of colored disturbance with known covariance matrix. Focusing on the class of coded pulse trains, we present a code selection algorithm which maximizes the detection performance but, at the same time, is capable of controlling both the region of achievable values for the Doppler estimation accuracy and the degree of similarity with a pre-fixed radar code. Finally, the last part of the talk is devoted to the challenging issue of Multiple-Input Multiple-Output (MIMO) radar waveform design. In this context, we discuss the benefits of waveform diversity enabling the MIMO radar superiority over its phased array counterpart.