Code optimization with similarity and accuracy constraints

S. De Nicola, Y. Huang, A. De Maio, S. Zhang, A. Farina

Research output: Chapter in Book/Report/Conference proceedingConference contribution

6 Scopus citations

Abstract

This paper deals with the design of coded waveforms which optimize radar performances in the presence of colored Gaussian disturbance. We focus on the class of linearly coded pulse trains and determine the radar code which maximizes the detection performance under a control on the region of achievable Doppler estimation accuracies, and imposing a similarity constraint with a pre-fixed radar code. The resulting optimization problem is non-convex and quadratic. In order to solve it, we propose a technique based on the relaxation of the original problem into a semidefinite program. Indeed the best code is determined through a rank-one decomposition of an optimal solution of the relaxed problem. At the analysis stage we assess the performance of the new encoding technique in terms of detection performance, region of achievable Doppler estimation accuracies, and ambiguity function.

Original languageEnglish (US)
Title of host publication2008 IEEE Radar Conference, RADAR 2008
DOIs
StatePublished - 2008
Event2008 IEEE Radar Conference, RADAR 2008 - Rome, Italy
Duration: May 26 2008May 30 2008

Publication series

Name2008 IEEE Radar Conference, RADAR 2008

Other

Other2008 IEEE Radar Conference, RADAR 2008
Country/TerritoryItaly
CityRome
Period5/26/085/30/08

Keywords

  • Non-Convex Quadratic Optimization
  • Radar Signal Processing
  • Semidefinite Programming Relaxation

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