Multiple radar environment emission deinterleaving and PRI prediction
Master Thesis
2017
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University of Cape Town
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Abstract
The aim of this study was to research TOA based tracking and deinterleaving algorithms suited to radar emitters in an EW environment for application on the CSIR 5th generation DRFM platform. The research problem statement stipulated that the only defining characteristic of the different emitters be the time of arrival (TOA) of their pulses. The pulse repetition interval (PRI) schemes considered in the study was constant, jittered, staggered and dwell and switch. The different TOA based deinterleaving algorithms investigated were sequence search (SS), TOA difference histogram, CDIF, SDIF, CDIF with SS (CDIF SS), SDIF with SS (SDIF SS) and interleaved pulse train spectrum estimation. The interleaved pulse train spectrum estimation algorithm results could not be replicated and were not included in simulations. The TOA based tracking algorithms that were also investigated were Delta-t histogram, Kalman filter, alpha-beta filter and alpha-beta-gamma filter. The alpha-beta-gamma filter became unstable during simulations and hence their results have also been excluded. The algorithms were simulated in MATLAB against EW environments with varied TOA measurement noise, number of emitters, PRI schemes and interference pulses (missing and spurious). General conclusions drawn from the deinterleaving simulations were the success of the algorithms decrease with the increase of emitters in the EW environment, interference pulses increased the success of some algorithms and the success of algorithms increased with TMNR (time measurement to noise ratio). General conclusions drawn from the tracking simulations were track loss of the algorithms decrease with increase in TMNR, tracking error decreases with increase in TMNR and interference pulses affected the initial estimates used to initialise the filters. The performance of the deinterleaving (CDIF & CDIF SS) and tracking ( Delta-t histogram & alpha-beta filter) algorithms were compared on the DRFM platform. On the DRFM platform, the CDIF algorithm deinterleaved in fewer pulses but had more false detections as compared to the CDIF SS algorithm. The alpha-beta filter performed better with lower TMNR than the Delta-t histogram, on the DRFM platform. The CDIF SS algorithm and alpha-beta filter were chosen, based on their performance on the DRFM, to be implemented on a DRFM based system that would deinterleave and then track emitters in an EW environment. The system was successfully implemented and met all requirements that were placed on it. Possible improvements to the system and the future improvements to the research are also discussed.
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Manickchand, K. 2017. Multiple radar environment emission deinterleaving and PRI prediction. University of Cape Town.