Comparison of time of arrival vs. multiple parameter based radar pulse train deinterleavers

摘要

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. Multi-parametric 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 [1989] and Milojevic and Popovich [1992] shows some of the early work in TOA-based deinterleaving. Ray [1997] demonstrates some of the more recent work in this area. Multi-parametric techniques are exemplified by Granger, et al [1998] and Thompson and Sciortino [2004]. 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.