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Multichannel radar adaptive signal detection in interference and structure nonhomogeneity

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Abstract

In this paper, we consider the problem of multichannel radar signal detection in interference and structure nonhomogeneity. The interference is often caused by electromagnetic countermeasure (ECM) systems or industrial activity, while the nonhomogeneity usually arises because of rapid variations in terrain or radar antenna structure. We propose three adaptive detectors according to three common criteria of detector design, namely, the generalized likelihood ratio test (GLRT), Rao test, and Wald test. Extensive performance comparisons are conducted under different scenarios. It is shown that when the nonhomogeneity is severe, the detector devised according to the GLRT achieves the best detection performance. In other scenarios, the detector designed according to the Wald test may be the best choice, which has the highest probability of detection.

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References

  1. Kelly E J. An adaptive detection algorithm. IEEE Trans Aerospace Electron Syst, 1986, 22: 115–127

    Article  Google Scholar 

  2. Chen W S, Reed I S. A new CFAR detection test for radar. Digital Signal Process, 1991, 1: 198–214

    Article  Google Scholar 

  3. Robey F C, Fuhrmann D R, Kelly E J, et al. A CFAR adaptive matched filter detector. IEEE Trans Aerospace Electron Syst, 1992, 28: 208–216

    Article  Google Scholar 

  4. de Maio A. A new derivation of the adaptive matched filter. IEEE Signal Process Lett, 2004, 11: 792–793

    Article  Google Scholar 

  5. de Maio A. Rao test for adaptive detection in Gaussian interference with unknown covariance matrix. IEEE Trans Signal Process, 2007, 55: 3577–3584

    Article  MathSciNet  Google Scholar 

  6. Pastina D, Lombardo P, Bucciarelli T. Adaptive polarimetric target detection with coherent radar part I: detection against Gaussian background. IEEE Trans Aerospace Electron Syst, 2001, 37: 1194–1206

    Article  Google Scholar 

  7. Liu J, Zhang Z J, Yang Y. Optimal waveform design for generalized likelihood ratio and adaptive matched filter detectors using a diversely polarized antenna. Signal Process, 2012, 92: 1126–1131

    Article  Google Scholar 

  8. Liu W J, Xie W C, Liu J, et al. Adaptive double subspace signal detection in Gaussian background—part I: homogeneous environments. IEEE Trans Signal Process, 2014, 62: 2345–2357

    Article  MathSciNet  Google Scholar 

  9. Xu J, Yu J, Peng Y N, et al. Radon-fourier transform for radar target detection. I: Generalized Doppler filter bank. IEEE Trans Aerospace Electron Syst, 2011, 47: 1186–1202

    Article  Google Scholar 

  10. Xu J, Xia X G, Peng S B, et al. Radar maneuvering target motion estimation based on generalized Radon-Fourier transform. IEEE Trans Signal Process, 2012, 60: 6190–6201

    Article  MathSciNet  Google Scholar 

  11. Chen X, Guan J, Liu N B, et al. Maneuvering target detection via Radon-fractional Fourier transform-based long-time coherent integration. IEEE Trans Signal Process, 2014, 62: 939–953

    Article  MathSciNet  Google Scholar 

  12. Li X L, Cui G L, Yi W, et al. A fast maneuvering target detection motion parameters estimation algorithm based on ACCF. IEEE Signal Process Lett, 2015, 22: 270–274

    Article  Google Scholar 

  13. Conte E, de Maio A, Ricci G. GLRT-based adaptive detection algorithms for range-spread targets. IEEE Trans Signal Process, 2001, 49: 1336–1348

    Article  Google Scholar 

  14. Kraut S, Scharf L L. The CFAR adaptive subspace detector is a scale-invariant GLRT. IEEE Trans Signal Process, 1999, 47: 2538–2541

    Article  Google Scholar 

  15. de Maio A, Iommelli S. Coincidence of the Rao test, Wald test, and GLRT in partially homogeneous environment. IEEE Signal Process Lett, 2008, 15: 385–388

    Article  Google Scholar 

  16. Kraut S, Scharf L L. Adaptive subspace detectors. IEEE Trans Signal Process, 2001, 49: 1–16

    Article  Google Scholar 

  17. Liu W J, Xie W C, Liu J, et al. Adaptive double subspace signal detection in Gaussian background—part II: partially homogeneous environments. IEEE Trans Signal Process, 2014, 62: 2358–2369

    Article  MathSciNet  Google Scholar 

  18. Rangaswamy M, Weiner D, Oeztuerk A. Non-Gaussian random vector identification using spherically invariant random processes. IEEE Trans Aerospace Electron Syst, 1993, 29: 111–124

    Article  Google Scholar 

  19. Gini F, Farina A. Vector subspace detection in compound-Gaussian clutter part I: survey and new results. IEEE Trans Aerospace Electron Syst, 2002, 38: 1295–1311

    Article  Google Scholar 

  20. Gini F. Sub-optimum coherent radar detection in a mixture of k-distributed and Gaussian clutter. IEEE Process, 1997, 144: 39–48

    Google Scholar 

  21. Gerlach K. Spatially distributed target detection in non-Gaussian clutter. IEEE Trans Aerospace Electron Syst, 1999, 35: 926–934

    Article  Google Scholar 

  22. Cui G L, Kong L J, Yang X B, et al. Distributed target detection with polarimetric MIMO radar in compound-Gaussian clutter. Digital Signal Process, 2012, 22: 430–438

    Article  MathSciNet  Google Scholar 

  23. Sangston K J, Gini F, Greco M S. Coherent radar target detection in heavy-tailed compound-Gaussian clutter. IEEE Trans Aerospace Electron Syst, 2012, 64: 64–76

    Article  Google Scholar 

  24. Zhang T X, Cui G L, Kong L J, et al. Phase-modulated waveform evaluation and selection strategy in compound- Gaussian clutter. IEEE Trans Signal Process, 2013, 61: 1143–1148

    Article  MathSciNet  Google Scholar 

  25. Zhang T X, Cui G L, Kong L J, et al. Adaptive Bayesian detection using MIMO radar in spatially heterogeneous clutter. IEEE Signal Process Lett, 2013, 20: 547–550

    Article  Google Scholar 

  26. Kong L J, Li N, Cui G L, et al. Adaptive Bayesian detection for multiple-input multiple-output radar in compound- Gaussian clutter with random texture. IET Radar Sonar Navigation, 2016, 10: 689–698

    Article  Google Scholar 

  27. Gao Y C, Li H B, Himed B. Knowledge-aided range-spread target detection for distributed MIMO radar in nonhomogeneous environments. IEEE Trans Signal Process, 2017, 65: 617–627

    Article  MathSciNet  Google Scholar 

  28. Besson O, Tourneret J Y, Bidon S. Knowledge-aided Bayesian detection in heterogeneous environments. IEEE Signal Process Lett, 2007, 14: 355–358

    Article  Google Scholar 

  29. Orlando D, Ricci G. A Rao test with enhanced selectivity properties in homogeneous scenarios. IEEE Trans Signal Process, 2010, 58: 5385–5390

    Article  MathSciNet  Google Scholar 

  30. Besson O, Orlando D. Adaptive detection in nonhomogeneous environments using the generalized eigenrelation. IEEE Signal Process Lett, 2007, 14: 731–734

    Article  Google Scholar 

  31. Hao C, Orlando D, Hou C. Rao and Wald tests for nonhomogeneous scenarios. Sensors, 2012, 12: 4730–4736

    Article  Google Scholar 

  32. Bandiera F, Besson O, Orlando D, et al. GLRT-based direction detectors in homogeneous noise and subspace interference. IEEE Trans Signal Process, 2007, 55: 2386–2394

    Article  MathSciNet  Google Scholar 

  33. Bandiera F, Besson O, Ricci G. Direction detector for distributed targets in unknown noise and interference. Electron Lett, 2013, 49: 68–69

    Article  Google Scholar 

  34. Liu W J, Liu J, Wang Y L, et al. Adaptive array detection in noise and completely unknown jamming. Digital Signal Process, 2015, 46: 41–48

    Article  MathSciNet  Google Scholar 

  35. Liu W J, Liu J, Hu X Q, et al. Statistical performance analysis of the adaptive orthogonal rejection detector. IEEE Signal Process Lett, 2016, 23: 873–877

    Article  Google Scholar 

  36. Bandiera F, De Maio A, Greco A S, et al. Adaptive radar detection of distributed targets in homogeneous and partially homogeneous noise plus subspace interference. IEEE Trans Signal Process, 2007, 55: 1223–1237

    Article  MathSciNet  Google Scholar 

  37. Liu W J, Liu J, Huang L, et al. Rao tests for distributed target detection in interference and noise. Signal Process, 2015, 117: 333–342

    Article  Google Scholar 

  38. Gao Y C, Liao G S, Liu W J. High-resolution radar detection in interference and nonhomogeneous noise. IEEE Signal Process Lett, 2016, 23: 1359–1363

    Article  Google Scholar 

  39. Shuai X F, Kong L J, Yang J Y. Adaptive detection for distributed targets in Gaussian noise with Rao and Wald tests. Sci China Inf Sci, 2012, 55: 1290–1300

    Article  MathSciNet  MATH  Google Scholar 

  40. Hao C P, Orlando D, Ma X C, et al. Persymmetric Rao and Wald tests for partially homogeneous environment. IEEE Signal Process Lett, 2012, 19: 587–590

    Article  Google Scholar 

  41. Liu J, Liu W J, Chen B, et al. Modified Rao test for multichannel adaptive signal detection. IEEE Trans Signal Process, 2016, 64: 714–725

    Article  MathSciNet  Google Scholar 

  42. Besson O. Detection in the presence of surprise or undernulled interference. IEEE Signal Process Lett, 2007, 14: 352–354

    Article  Google Scholar 

  43. Yanai H, Takeuchi K, Takane Y. Projection Matrices, Generalized Inverse Matrices, and Singular Value Decomposition. New York: Springer, 2011

    Book  MATH  Google Scholar 

  44. Liu W J, Wang Y L, Xie W C. Fisher information matrix, Rao test, and Wald test for complex-valued signals and their applications. Signal Process, 2014, 94: 1–5

    Article  Google Scholar 

  45. Bandiera F, Besson O, Ricci G. An ABORT-like detector with improved mismatched signals rejection capabilities. IEEE Trans Signal Process, 2007, 56: 14–25

    Article  MathSciNet  Google Scholar 

  46. Hao C P, Liu B, Cai L. Performance analysis of a two-stage Rao detector. Signal Process, 2011, 91: 2141–2146

    Article  MATH  Google Scholar 

  47. Liu W J, Liu J, Zhang C, et al. Performance prediction of subspace-based adaptive detectors with signal mismatch. Signal Process, 2016, 123: 122–126

    Article  Google Scholar 

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Acknowledgements

This work was supported by National Natural Science Foundation of China (Grant Nos. 61501505, 61501351).

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Authors and Affiliations

  1. Air Force Early Warning Academy, Wuhan, 430019, China

    Weijian Liu, Hongli Li & Yong-Liang Wang

  2. State Key Laboratory of Complex Electromagnetic Environment Effects on Electronics and Information System, Luoyang, 471003, China

    Hui Han

  3. National Laboratory of Radar Signal Processing, Xidian University, Xi’an, 710071, China

    Jun Liu

  4. Collaborative Innovation Center of Information Sensing and Understanding, Xidian University, Xi’an, 710071, China

    Jun Liu

  5. School of Electronic Information, Wuhan University, Wuhan, 430072, China

    Kai Li

Authors
  1. Weijian Liu
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  2. Hui Han
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  3. Jun Liu
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  4. Hongli Li
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  5. Kai Li
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  6. Yong-Liang Wang
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Correspondence to Yong-Liang Wang.

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Conflict of interest The authors declare that they have no conflict of interest.

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Liu, W., Han, H., Liu, J. et al. Multichannel radar adaptive signal detection in interference and structure nonhomogeneity. Sci. China Inf. Sci. 60, 112302 (2017). https://doi.org/10.1007/s11432-016-9105-7

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  • DOI: https://doi.org/10.1007/s11432-016-9105-7

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