  In pulsed Doppler radars, the classic Chinese remainder theorem (CCRT) is a
common method to resolve Doppler ambiguities caused by fast-moving targets.
Another issue concerning high-velocity targets is related to the loss in the
signal-to-noise ratio (SNR) after performing range compression. In particular,
this loss can be partially mitigated by the use of subpulse processing (SP).
Modern radars combine these techniques in order to reliably unfold the target
velocity. However, the presence of background noise may compromise the Doppler
estimates. Hence, a rigorous statistical analysis is imperative. In this work,
we provide a comprehensive analysis on Doppler estimation. In particular, we
derive novel closed-form expressions for the probability of detection (PD) and
probability of false alarm (PFA). To this end, we consider the newly introduce
SP along with the CCRT. A comparison analysis between SP and the classic pulse
processing (PP) technique is also carried out. Numerical results and
Monte-Carlo simulations corroborate the validity of our expressions and show
that the SP-plus-CCRT technique helps to greatly reduce the PFA compared to
previous studies, thereby improving radar detection.
