This paper provides a comparison of the two main techniques currently in use to solve the problem of radar pulse train
deinterleaving. Pulse train deinterleaving separates radar pulse trains into the tracks or bins associated with the detected
emitters. The two techniques are simple time of arrival (TOA) histogramming and multi-parametric analysis. TOA
analysis uses only the time of arrival (TOA) parameter of each pulse to deinterleave radar pulse trains. Such algorithms
include Cumulative difference (CDIF) histogramming and Sequential difference (SDIF) histogramming. Multiparametric
analysis utilizes any combination of the following parameters: TOA, radio frequency (RF), pulse width (PW),
and angle of arrival (AOA). These techniques use a variety of algorithms, such as Fuzzy Adaptive Resonance Theory
(Fuzzy-ART), Fuzzy Min-Max Clustering (FMMC), Integrated Adaptive Fuzzy Clustering (IAFC) and Fuzzy Adaptive
Resonance Theory Map (Fuzzy-ARTMAP) to compare the pulses to determine if they are from the same emitter. Good
deinterleaving is critical since inaccurate deinterleaving can lead to misidentification of emitters.
The deinterleaving techniques evaluated in this paper are a sizeable and representative sample of both US and
international efforts developed in the UK, Canada, Australia and Yugoslavia. Mardia  and Milojevic and Popovich
 shows some of the early work in TOA-based deinterleaving. Ray  demonstrates some of the more recent
work in this area. Multi-parametric techniques are exemplified by Granger, et al  and Thompson and Sciortino
. This paper will provide an analysis of the algorithms and discuss the results obtained from the referenced
articles. The algorithms will be evaluated for usefulness in deinterleaving pulse trains from agile radars.