Signal Processing Algorithm of STC Waveforms for the Phased array MIMO Radar: Overview on Target Localization

Abstract: The MIMO phased array radar is a theoretical concept for multi-sensor radar planning that combines elements of traditional phased-array radar with the developing technology of multiple-input multiple output (MIMO) radar. Space-time coding (STC) has been shown to play a key role in the design of Phased Array MIMO radar where MIMO radar can achieve improved localization performance by employing a coherent processing approach with proper antenna positioning. Coherent processing, however, entails the challenge of ensuring phase coherence of the carrier signals from different distributed radar elements. In recent years, studies have shown how the performances of conventional phased-array radar can be improved by using the same approach. We consider the use of STC to mitigate the waveform cross-correlation effects in MIMO radar. In addition, we also extend the model to partial waveform cross-correlation removal based on waveform set division. Numerical results demonstrate the effectiveness of STC in MIMO radar for waveform decorrelation. In this paper, the aim is to shed some light on the optimum transmit policy as the radar is to detect a target at an unknown location: To this end, at first the Cramer–Rao bounds as a function of the STC matrix are computed to providing a systematic treatment of the phase synchronization problem in coherent MIMO radar systems. This paper introduces the signal processing issued for the phased array MIMO radar without and with STC waveforms and also studied phased array MIMO radar with STC waveforms improved target detection and recognition performance.