Waveform Design for Cognitive Radar with Application to S-Band Naval Phased Array Radar

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Authors
  1. Najafabadi, H.E.
  2. Leung, H.
Corporate Authors
Defence Research and Development Canada, Ottawa Research Centre, Ottawa ON (CAN);Calgary Univ, Calgary ALTA (CAN)
Abstract
In this report, adaptive iterative methods are developed for cognitive radar systems with application to S-band naval radar systems. After an in-depth review of the literature, range maximization with power constraint is investigated without considering any clutter, where power constraint is also considered to achieve plausibility of the problem. The resulted algorithm is suitable for detecting flying objects where the antenna bore-sight does not coincide with sea surface. The same problem in presence of sea clutter is considered afterward, where the range is maximized while clutter return is minimized. The developed model is suitable for low-flying airborne and surface targets, embracing all kinds of sea states. However, The above-mentioned models are restricted in terms of their cognition exploitation. In fact, the only cognition that can be incorporated to these models are target radar cross section (RCS), clutter RCS per unit area, and path loss. In order to incorporate more cognition to waveform design, the waveform design problem is then viewed in some different contexts. First, suppression part of the autocorrelation sidelobes is investigated. This method allows for incorporating a priori cognition of range into waveform design in a no-clutter scenario. Afterward, incorporating range and Doppler a priori knowledge of target and clutter is investigated through waveform design based on ambiguity function. Interestingly, a special case of the formulated problem is reveale

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Keywords
Sea Clutter;Range Maximization Algorithm;Cognitive Radar;Ambiguity function Design;SCNR maximization;Minimum Detectable Range minimization
Report Number
DRDC-RDDC-2019-C113 — Contract Report
Date of publication
01 May 2019
Number of Pages
94
DSTKIM No
CA049516
CANDIS No
810292
Format(s):
Electronic Document(PDF)

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