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Design of Pareto-Optimal Radar Receive Filters

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This paper deals with the design of radar receive filters jointly optimized with respect to sidelobe energy and sidelobe peaks via Pareto-optimal theory. We prove that this criterion is tantamount to jointly minimizing two quadratic forms, so that the design can be analytically formulated in terms of a multi-objective optimization problem. In order to solve it, we resort to the scalarization technique, which reduces the vectorial problem into a scalar one using a Pareto weight defining the relative importance of the two objective functions. At the analysis stage, we assess the performance of the receive filters in correspondence of different values of the Pareto weight highlighting the performance compromises between the Integrated Sidelobe Level (ISL) and the Peak Sidelobe Level (PSL).
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  • Universita di Napoli "Federico II", Via Claudio 21, 80125, Naples, Italy, ademaio@unina.it
Bibliografia
  • [1] M. I. Skolnik, Introduction to radar systems, 3rd ed. Mc Graw Hill, 2001.
  • [2] C. E. Cook and M. Bernfield, Radar signals: nn introduction to theory and application. New York: Academic Press, 1967.
  • [3] D. F. DeLong and E. M. Hofstetter, “On the design of optimum radar waveforms for clutter rejection,” IEEE Transactions on Information Theory, vol. 13, no. 3, pp. 454–463, July 1967.
  • [4] C. Stutt and L. Spafford, “A best mismatched filter response for radar clutter discrimination,” IEEE Transactions on Information Theory, vol. 14, no. 2, pp. 280–287, March 1968.
  • [5] Y. I. Abramovich and M. B. Sverdlik, “Synthesis of a filter which maximizes the signal-to-noise radio under additional quadratic constraints,” Radio Engineering and Electronic Physics, vol. 15, no. 11, pp. 1977–1984, 1970.
  • [6] V. T. Dolgochub and M. B. Sverdlik, “Generalized -filters,” Radio Engineering and Electronic Physics, vol. 15, pp. 147–150, January 1970.
  • [7] P. Stoica, J. Li, and M. Xue, “Transmit codes and receive filters for radar,” IEEE Signal Processing Magazine, vol. 25, no. 6, pp. 94–109, November 2008.
  • [8] Y. I. Abramovich and M. B. Sverdlik, “Synthesis of filters maximizing the signalto- noise ratio in the case of a minimax constraint on the sidelobes of the crossambiguity function,” Radio Engineering and Electronic Physics, vol. 16, pp. 253–258, February 1971.
  • [9] S. Zoraster, “Minimum peak range sidelobe filters for binary phasecoded waveforms,” IEEE Transactions on Aerospace and Electronic Systems, vol. 16, no. 1, pp. 112–115, January 1980.
  • [10] A. Nemirovski, Lectures on modern convex optimization. Class Notes, Georgia Institute of Technology, Fall 2005.
  • [11] S. A. Vorobyov, A. B. Gershman, and Z.-Q. Luo, “Robust adaptive beamforming using worst-case performance optimization: a solution to the signal mismatch problem,” IEEE Transactions on Signal Processing, vol. 51, no. 2, pp. 313–324, February 2003.
  • [12] K. Yang, G. Wang, and Z.-Q. Luo, “Efficient convex relaxation methods for robust target localization by a sensor network using time differences of arrivals,” IEEE Transactions on Signal Processing, vol. 57, no. 7, pp. 2775–2784, July 2009.
  • [13] S. Boyd and L. Vandenberghe, Convex Optimization. Cambridge University Press, 2003.
  • [14] K. Griep, J. A. Ritcey, and J. J. Burlingame, “Poly-phase codes and optimal filters for multiple user ranging,” IEEE Transactions on Aerospace and Electronic Systems, vol. 31, no. 2, pp. 752–767, April 1995.
  • [15] P. Stoica, J. Li, and M. Xue, “On binary probing signals and instrumental variables receivers for radar,” IEEE Transactions on Information Theory, vol. 54, no. 8, pp. 3820–3825, August 2008.
  • [16] J. E. Cilliers and J. C. Smit, “Pulse compression sidelobe reduction by minimization of Lp-norms,” IEEE Transactions on Aerospace and Electronic Systems, vol. 43, no. 3, pp. 1238–1247, July 2007.
  • [17] K. Deb, Multi-objective optimization using evolutionary algorithms, 1st ed. John Wiley & Sons, June 2001.
  • [18] J. F. Sturm, “Using SeDuMi 1.02, a MATLAB toolbox for optimization over symmetric cones,” Optimization Methods and Software, vol. 11–12, pp. 625–653, August 1999.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-article-BWA0-0051-0009
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