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Robust Transmission Waveform Design for Distributed Multiple-Radar Systems Based on Low Probability of Intercept

  • Shi, Chenguang (Key Laboratory of Radar Imaging and Microwave Photonics, Ministry of Education, Nanjing University of Aeronautics and Astronautics) ;
  • Wang, Fei (Key Laboratory of Radar Imaging and Microwave Photonics, Ministry of Education, Nanjing University of Aeronautics and Astronautics) ;
  • Sellathurai, Mathini (School of Engineering & Physical Sciences, Heriot-Watt University) ;
  • Zhou, Jianjiang (Key Laboratory of Radar Imaging and Microwave Photonics, Ministry of Education, Nanjing University of Aeronautics and Astronautics) ;
  • Zhang, Huan (Key Laboratory of Radar Imaging and Microwave Photonics, Ministry of Education, Nanjing University of Aeronautics and Astronautics)
  • Received : 2014.10.20
  • Accepted : 2015.10.14
  • Published : 2016.02.01

Abstract

This paper addresses the problem of robust waveform design for distributed multiple-radar systems (DMRSs) based on low probability of intercept (LPI), where signal-to-interference-plus-noise ratio (SINR) and mutual information (MI) are utilized as the metrics for target detection and information extraction, respectively. Recognizing that a precise characterization of a target spectrum is impossible to capture in practice, we consider that a target spectrum lies in an uncertainty class bounded by known upper and lower bounds. Based on this model, robust waveform design approaches for the DMRS are developed based on LPI-SINR and LPI-MI criteria, where the total transmitting energy is minimized for a given system performance. Numerical results show the effectiveness of the proposed approaches.

Acknowledgement

Supported by : National Natural Science Foundation of China

References

  1. E.P. Phillip, "Detecting and Classifying Low Probability of Intercept Radar," Boston, USA: Artech House, 2009, pp. 342-352.
  2. E. Fishler et al., "Spatial Diversity in Radars-Models and Detection Performance," IEEE Trans. Signal Process., vol. 54, no. 3, Mar. 2006, pp. 823-838. https://doi.org/10.1109/TSP.2005.862813
  3. C.G. Shi et al., "LPI Optimization Framework for Target Tracking in Radar Network Architectures Using Information-Theoretic Criteria," Int. J. Antennas Propag., vol. 2014, July 2014, pp. 1-10.
  4. B. Friedlander, "Waveform Design for MIMO Radars," IEEE Trans. Aerosp. Electron. Syst., vol. 43, no. 3, July 2007, pp. 1227-1238. https://doi.org/10.1109/TAES.2007.4383615
  5. P. Stoica, J. Li, and Y. Xie, "On Probing Signal Design for MIMO Radar," IEEE Trans. Signal Process., vol. 55, no. 8, Aug. 2007, pp. 4151-4161. https://doi.org/10.1109/TSP.2007.894398
  6. M.R. Bell, "Information Theory and Radar Waveform Design," IEEE Trans. Inf. Theory, vol. 39, no. 5, Sept. 1993, pp. 1578-1597. https://doi.org/10.1109/18.259642
  7. Y. Yang and R.S. Blum, "MIMO Radar Waveform Design Based on Mutual Information and Minimum Mean-Square Error Estimation," IEEE Trans. Aerosp. Electron. Syst., vol. 43, no. 1, Jan. 2007, pp. 330-343. https://doi.org/10.1109/TAES.2007.357137
  8. M.M. Naghsh et al., "Unified Optimization Framework for Multi-static Radar Code Design Using Information-Theoretic Criteria," IEEE Trans. Signal Process., vol. 61, no. 21, Nov. 2013, pp. 5401-5416. https://doi.org/10.1109/TSP.2013.2278154
  9. Y.F. Chen et al., "Adaptive Distributed MIMO Radar Waveform Optimization Based on Mutual Information," IEEE Trans. Aerosp. Electron. Syst., vol. 49, no. 2, Apr. 2013, pp. 1374-1385. https://doi.org/10.1109/TAES.2013.6494422
  10. L. Xu and Q.L. Liang, "Waveform Design and Optimization in Radar Sensor Network," IEEE Conf. Global Telecommun., Miami, FL, USA, Dec. 6-10, 2010, pp. 1-5.
  11. B. Tang, J. Tang, and Y.N. Peng, "MIMO Radar Waveform Design in Colored Noise Based on Information Theory," IEEE Trans. Signal Process., vol. 58, no. 9, Sept. 2010, pp. 4684-4697. https://doi.org/10.1109/TSP.2010.2050885
  12. R.A. Romero, J. Bae, and N.A. Goodman, "Theory and Application of SNR and Mutual Information Matched Illumination Waveforms," IEEE Trans. Aerosp. Electron. Syst., vol. 47, no. 2, Apr. 2011, pp. 912-927. https://doi.org/10.1109/TAES.2011.5751234
  13. P.M. Woodward, "Theory of Radar Information," Trans. IRE Professional Group Inf. Theory, vol. 1, no. 1, Feb. 1953, pp. 108-113. https://doi.org/10.1109/TIT.1953.1188560
  14. P.M. Woodward, "Information Theory and the Design of Radar Receivers," Proc. IRE, vol. 39, no. 12, Dec. 1951, pp. 1521-1524. https://doi.org/10.1109/JRPROC.1951.273638
  15. S.A. Kassam and H.V. Poor, "Robust Techniques for Signal Processing: A Survey," Proc. IEEE, vol. 73, no. 3, Mar. 1985, pp. 433-481. https://doi.org/10.1109/PROC.1985.13167
  16. Y. Yang and R.S. Blum, "Minimax Robust MIMO Radar Waveform Design," IEEE J. Sel. Topics Signal Process., vol. 1, no. 1, June 2007, pp. 147-155. https://doi.org/10.1109/JSTSP.2007.897056
  17. B. Jiu et al., "Minimax Robust Transmission Waveform and Receiving Filter Design for Extended Target Detection with Imprecise Prior Knowledge," Signal Process., vol. 92, no. 1, Jan. 2012, pp. 210-218. https://doi.org/10.1016/j.sigpro.2011.07.008
  18. Y.Q. Zhao, C.L. Yu, and H.P. Yin, "Research into the Anti-Common-Frequency Interference Technology Based on Code-Agility," Shipboard Electron. Countermeasure, vol. 36, no. 1, Jan. 2013, pp. 14-19.
  19. C.G. Shi, J.J. Zhou, and F. Wang, "Low Probability of Intercept Optimization for Radar Network Based on Mutual Information," IEEE China Summit Int. Conf. Signal Inf. Process., Xi'an, China, July 9-13, 2014, pp. 683-687.
  20. L.L. Wang et al., "Minimax Robust Jamming Techniques Based on Signal-to-Interference-Plus-Noise Ratio and Mutual Information Criteria," IET Commun., vol. 8, no. 10, July 2014, pp. 1859-1867. https://doi.org/10.1049/iet-com.2013.1054