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In FMCW automotive radar applications, it is often a challenge to design achirp sequence that satisfies the requirements set by practical drivingscenarios and simultaneously enables high range resolution, large maximumrange, and unambiguous velocity estimation. To support long-range scenarios thechirps should have a sufficiently long duration compared to their bandwidth. Atthe same time, the long chirps result in ambiguous velocity estimation fortargets with high velocity. The problem of velocity ambiguity is often solvedby using multiple chirp sequences with co-prime delay shifts between them.However, coherent processing of multiple chirp sequences is not possible usingclassical spectral estimation techniques based on Fast Fourier Transform (FFT).This results in statistically not efficient velocity estimation and loss ofprocessing gain. In this work, we propose an algorithm that can jointly processmultiple chirp sequences and resolve possible ambiguities present in thevelocities estimates. The resulting algorithm is statistically efficient andgridless. Furthermore, it increases the resolution of velocity estimationbeyond the natural resolution due to its super-resolution properties. Theseresults are confirmed by both numerical simulations and experiments withautomotive radar IC.

Joint Multiple FMCW Chirp Sequence Processing for Velocity Estimation and Ambiguity Resolving