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Cognitive radar sequence design under the spectral compatibility requirements

Ge, P ; Sharif University of Technology

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  1. Type of Document: Article
  2. DOI: 10.1049/iet-rsn.2016.0239
  3. Abstract:
  4. As the increasing demands of military detection, wireless communication and remote sensing make the spectrum even more crowded, radar sequence design meeting spectral compatibility requirement is a challenging and urgent problem. This study is devoted to designing optimised phase-coded sequences which keep spectral-compatible with the overlaid electromagnetic radiators and at the same time optimise the signal-to-interference-plus-noise ratio (SINR). First, an intelligent dynamic spectrum information around the radar system is achieved by a radio environmental map. The information is introduced to form a constrained optimisation process aimed at improving the spectral compatibility and the radar detection performance. Second, the unimodularity requirement is necessary to make full use of transmit power and a similarity constraint is enforced to keep desired ambiguity function feature. Third, to resolve the resulting non-convex optimisation quadratically constrained quadratic problem, a relaxation and a randomisation procedure are applied. Therefore, the technique behaves a polynomial computational complexity. Finally, the performance analysis is given to show its effectiveness in terms of the SINR, the spectral shape, and the resulting auto-correlation function. © 2016, The Institution of Engineering and Technology
  5. Keywords:
  6. Constrained optimization ; Convex optimization ; Radar ; Radar systems ; Remote sensing ; Signal interference ; Signal to noise ratio ; Spurious signal noise ; Wireless telecommunication systems ; Ambiguity function ; Autocorrelation functions ; Performance analysis ; Phase-coded sequences ; Quadratically constrained quadratic problems ; Signal to interference plus noise ratio ; Wireless communications ; Tracking radar
  7. Source: IET Radar, Sonar and Navigation ; Volume 11, Issue 5 , 2017 , Pages 759-767 ; 17518784 (ISSN)
  8. URL: https://ieeexplore.ieee.org/document/7914095