Journal
IEEE TRANSACTIONS ON MICROWAVE THEORY AND TECHNIQUES
Volume 64, Issue 9, Pages 2986-2993Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TMTT.2016.2586476
Keywords
Automotive radar; bounding box estimation; dimension extraction; Doppler radar; MIMO radar; orientation estimation; radar imaging; radar signal processing; reliability
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With new generations of high-resolution imaging radars, the orientation of vehicles can be estimated without temporal filtering. This enables time-critical systems to respond even faster. Based on a large data set, this paper compares three generic algorithms for the orientation estimation of a vehicle. An experimental MIMO imaging radar is used to highlight the requirements of a robust algorithm. The well-known orientated bounding box and the so-called L-fit are adapted for radar measurements and compared with a brute-force approach. A quality function selects the best fitted model and is a key factor to minimize alignment errors. Moreover, the reliability of the estimation is evaluated with respect to the aspect angle, the distance to the target, and the number of sensors. An approach to estimate the reliability of the current orientation estimation is introduced. It is shown that the root mean square error of the orientation estimation is 9.77 degrees and 38% smaller compared with the common algorithm. In 50% of the evaluated measurements the orientation estimation error is smaller than 3.73 degrees.
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