ESPRIT for DOA estimation

Abstract: Radar is a tool that has had a tremendous impact since its discovery. This thesis evaluates an algorithm called ESPRIT. ESPRIT is used in radar to estimate the angles to detected objects. The angle of an object is referred to as its DOA (Direction of arrival). ESPRIT separates from similar algorithms by having lower computational complexity, storage needs, and robustness. The thesis compares ESPRIT with another DOA-estimation algorithm used by a company called Raytelligence. The other algorithm can not be named due to confidentiality. The comparison is based on gathered data from an FMCW (Frequency Modulated Continuous Wave) radar. The comparison aims to validate ESPRIT functionality and its competitiveness versus the other algorithm. The comparison is based on two criteria: Accuracy and complexity. The thesis also presents potential optimizations which can improve ESPRIT’s ability to estimate DOA. These are an increase in the number of antennas used in the DOA estimation, and using the preprocessing scheme Spatial smoothing. The result for DOA estimation shows that ESPRITs' strength lies in detecting several objects at the same distance. The difference between ESPRIT and the other DOA estimation algorithm was insignificant when estimating one object. No conclusion could be drawn about the estimation accuracy for one object detection. The result also showed that ESPRIT's performance increases with the number of antennas and which preprocessing scheme is used. The result for complexity showed that ESPRIT has higher complexity than the other DOA estimation algorithm. For ESPRIT to use its strength, which is to detect several objects at the same distance, the implementation of complex pre-processing schemes is required. This will further increase the difference in complexity between the two compared algorithms.