  This paper introduces a Compressed Sensing (CS) estimation scheme for
Orthogonal Time Frequency Space (OTFS) channels with sparse multipath. The OTFS
waveform represents signals in a two dimensional Delay-Doppler (DD) orthonormal
basis. The proposed model does not require the assumption that the delays are
integer multiples of the sampling period. The analysis shows that non-integer
delay and Doppler shifts in the channel cannot be accurately modelled by
integer approximations. An Orthogonal Matching Pursuit with Binary-division
Refinement (OMPBR) estimation algorithm is proposed. The proposed estimator
finds the best channel approximation over a continuous DD dictionary without
integer approximations. This results in a significant reduction of the
estimation normalized mean squared error with reasonable computational
complexity.
