Direction Of Arrival Estimation in the Presence of Imperfect Waveforms for Multiple Targets in MIMO Radar

Abstract

Direction Of Arrival (DOA) estimation of multiple targets is a renowned challenging problem that has extensive applications in Multiple Input Multiple Output (MIMO) radar system. The introduction of sub-space based techniques escalates the accurate estimation of DOA but at the cost of increased computational complexity as they require multiple snapshots. The current work deals with the presentation of a novel approach based on Wild Horse Optimization (WHO) for the DOA estimation of multiple targets with Co-located MIMO radar in the presence of imperfect waveforms. The theory of extended array manifold vectors is incorporated in Mean Square Error (MSE) sense to develop an objective function that requires a single snapshot to gain the desired results. The deviation in MSE from the desired value is controlled through a penalty function which is the difference between the desired and actual responses of the system. A rigorous statistical analysis based on Monte Carlo simulations is carried out to validate the effectiveness of the proposed algorithm through histogram plots, box plots, Cumulative Distribution Function (CDF) plots, RMSE, robustness against noise, and estimation accuracy. Result comparison with state-of-the-art algorithms further endorses the legitimacy of the proposed WHO scheme for DOA estimation.

Keywords

• Antenna arrays
• direction of arrival estimation
• evolutionary computing techniques
• monostatic MIMO radar
• wild horse optimization