PL EN


Preferencje help
Widoczny [Schowaj] Abstrakt
Liczba wyników
Tytuł artykułu

Real Time Processing of Networked Passive Coherent Location Radar System

Autorzy
Treść / Zawartość
Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
A Passive Coherent Location (PCL) Radar system, consisting of spatially distributed transmitters and receivers is currently being integrated at the University of Cape Town (UCT). The paper investigates the feasibility of real-time processing of PCL system signals using Graphic Processing Units (GPUs), specifically a study of two distinct clutter cancellation algorithms: ECA (Extensive Cancellation Algorithm) and NLMS (Normalised Least Mean Square). Clutter cancellation is the most computationally demanding part of PCL signal processing. This investigation compares the processing speed-up achieved by GPU over CPU implementations, with very encouraging results.
Słowa kluczowe
EN
passive   PCL   real-time   GPU  
Twórcy
autor
autor
autor
  • Radar Remote Sensing Group, Department of Electrical Engineering, University of Cape Town, Rondebosch 7701, South Africa, mathewjohnth@gmail.com
Bibliografia
  • [1] E. Mollick, „Establishing Moore's Law”, in Annals of the History of Computing, IEEE, vol. 28, no. 3, September 2009, pp. 62 - 75.
  • [2] F. S. Heunis, „Passive Coherent Location Radar using Software-Defined Radio Techniques”, Master's thesis, University of Cape Town, Private Bag, Rondebosch, 7701, South Africa, May 2010.
  • [3] C. Tong, M. R. Inggs, and G. E. Lange, „Processing design of a networked passive coherent location system”, in Proceedings of the 2011 IEEE Radar Conference, May 2011.
  • [4] M. Ettus, USRP User's and Developer's Guide, Ettus Research LLC, Matt Ettus, Ettus Research LLC.
  • [5] Scott.C.Douglas, „A Family of Normalized LMS algorithms”, in IEEE Signal Processing Letters, vol. SPL-1, no. 3, 1994, pp. 49 - 51.
  • [6] F. Colone, „A multistage processing algorithm for disturbance removal and target detection in Passive Bistatic Radar”, in IEEE Trans. On Aerospace and Electronic Systems, vol. 45, no. 2, 2009, pp. 698 - 721.
  • [7] Tuning CUDA Applications for Fermi ver. 1.2, NVIDIA, Santa Clara, CA, July 2010.
  • [8] NVIDIA CUDA Reference Manual ver. 3.0, NVIDIA, Santa Clara, CA, February 2010.
  • [9] M. R. Inggs, Y. Paichard, and G. E. Lange, „Networked PCL System”, in Proceedings of the 2010 Cognitive Systems with Interactive Sensors (COGIS 2010). IET United Kingdom, 2010.
  • [10] NVIDIA CUDA Programming Guide, 3rd ed., NVIDIA, February 2010.
  • [11] N. Morrison, R. T. Lord, and M. R. Inggs, „The Gauss-Newton Algorithm in Passive Aircraft Tracking using Doppler and Bearings”, in Proceedings of the IET International Conference on Radar Systems (RADAR 2007). Institution of Engineering and Technology, October 2007.
  • [12] S. Haykin, Adaptive Filter Theory, 4th ed., T. Kailath, Ed. Prentice Hall, 2002.
  • [13] N. Willis, 'Bistatic radar' chapter 25 in Radar Handbook1, 2nd ed., M. Skolnik, Ed. McGrawHill, 1990.
  • [14] C. Sanderson, An Open Source C++ Linear Algebra Library for Fast Prototyping and Computationally Intensive Experiments, NICTA, St Lucia, Australia, September 2010.
  • [15] CUDA CUBLAS Library, NVIDIA, Santa Clara, CA, March 2008.
  • [16] CUDA CUFFT Library ver. 1.1, NVIDIA, Santa Clara, CA, October 2007.
  • [17] K.Szumski, „Real-Time Software Implementation of Passive Radar”, in Proceedings of the 6th European Radar Conference, September 2009, pp. 33 - 36.
  • [18] M. J. Brooker, „The design and implementation of a simulator for multistatic radar systems”, Doctoral Thesis, University of Cape Town - RRSG, Jun. 2008.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-article-BWAK-0026-0018
JavaScript jest wyłączony w Twojej przeglądarce internetowej. Włącz go, a następnie odśwież stronę, aby móc w pełni z niej korzystać.