A signal adaptive time of arrival estimation algorithm based on polynomial rooting

In this paper an algorithm for time of arrival estimation is proposed, which allows processing of spectrally sparse channel observations in order to provide highly accurate range estimations with a maximized resolution capability. The use of sparse waveforms in combination with the presented algorithm provides increased spectral efficiency with lower computational complexity due to reduced size of the observation matrices. Additionally, the ability of the algorithm to efficiently process spectral fragmentary data also gives the capability to efficiently cope with missing data caused by frequency selective fading or interferences.