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復(fù)合高斯雜波中相干雷達極化自適應(yīng)檢測算法研究

劉立東,  吳順君,  孫曉聞

劉立東, 吳順君, 孫曉聞. 復(fù)合高斯雜波中相干雷達極化自適應(yīng)檢測算法研究[J]. 電子與信息學(xué)報, 2006, 28(2): 326-329.
引用本文: 劉立東, 吳順君, 孫曉聞. 復(fù)合高斯雜波中相干雷達極化自適應(yīng)檢測算法研究[J]. 電子與信息學(xué)報, 2006, 28(2): 326-329.
Liu Li-dong, Wu Shun-jun, Sun Xiao-wen. Polarimetric Adaptive Detection Algorithm in Compound-Gaussian Clutter with Coherent Radar[J]. Journal of Electronics & Information Technology, 2006, 28(2): 326-329.
Citation: Liu Li-dong, Wu Shun-jun, Sun Xiao-wen. Polarimetric Adaptive Detection Algorithm in Compound-Gaussian Clutter with Coherent Radar[J]. Journal of Electronics & Information Technology, 2006, 28(2): 326-329.

復(fù)合高斯雜波中相干雷達極化自適應(yīng)檢測算法研究

Polarimetric Adaptive Detection Algorithm in Compound-Gaussian Clutter with Coherent Radar

  • 摘要: 研究了在復(fù)合高斯雜波中相干雷達極化自適應(yīng)檢測問題，基于廣義似然比檢驗提出了一種新的檢測算法。該算法關(guān)于雜波的結(jié)構(gòu)分量統(tǒng)計特性有恒虛警的性質(zhì)，敏感度分析表明虛警概率僅輕微地受到雜波相關(guān)特性變化的影響。仿真分析了不同狀態(tài)時該算法的檢測性能。結(jié)果表明該算法與先前的基于廣義似然比的極化自適應(yīng)檢測算法檢測性能接近，計算復(fù)雜度較低，有實際應(yīng)用價值。
    Abstract: Polarimetric adaptive detection of targets in compound-Gaussian clutter with coherent radar is addressed in the paper. An adaptive polarimetric detection algorithm is presented based upon the Generalized Likelihood Ratio Test (GLRT). The proposed algorithm has the Constant False Alarm Rate (CFAR) property with respect to the texture statistical characterization. A sensitivity analysis shows that the probability of false alarm is only slightly affected by variations in the clutter correlation properties. Resorting to simulation, the performance of the algorithm is analyzed in different cases. The proposed algorithm has an close performance as previously proposed algorithm, but it has less complexity, than the previously proposed one.
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  • 莊釗文等. 雷達極化信息處理及其應(yīng)用[M]. 北京: 國防工業(yè)出版社, 2000: 12.16.[2]Giuli D. Polarization diversity in radars. Proc. IEEE , 1986, 74 (2): 245269. .[3]Novak L M, Burl M C. Optimal polarimetric processing for enhanced detection, IEEE Trans. on AES, 29(1): 1993, 234.243.[4]Novak L M, Sechtin M B, Cardullo M J. Studies of target detection algorithms that use polarimetric radar data. IEEE Trans on AES, 1989, 25(2): 150.165.[5]Park H, Li J, Wang H. Polarization-space-time domain generalized likelihood ratio detection of radar targets[J].Signal Processing.1995, 41(2):153-[6]Maio A D, Ricci G. A polarimetric adaptive matched filter. Signal Processing, 2001, 81(3): 25832589. .[7]Pastina D, Lombardo P, Bucciarelli T. Adaptive polarimetric target detection with coherent radar. IEEE Trans. on AES, 2001, 37(4): 1194.1219.[8]劉立東, 吳順君, 王萬林. 相干雷達極化自適應(yīng)匹配濾波器。電子科技大學(xué)學(xué)報，2005, 32(1): 98102. .[9]Conte E, Longo M. Characterisation of radar clutter as a spherically invariant random process. IEE Proc. Part F ,1987, 134(2): 191.197.[10]Conte E, Di Bisceglie M, Galdi C, Ricci G. Aprocedure for measuring the coherent length of the sea texture[J].IEEE Trans. on Instrumentation and Measurement.1997, 46( 4):836-[11]Maio A D, Ricci G. Polarimetric adaptive detection in non-Gaussian noise[J].Signal Processing.2003, 83(3):297-[12]Goodman N R. Statistical analysis based on a certain multivariate complex distribution[J].Annals of Mathematical Statistics.1963, 34(1):152-[13]Scharf L. Statistical Signal Processing[M]. Addison-Wesley, 1991: 65.66.[14]Echard J D. Estimation of radar detection and false alarm probabilities. IEEE Trans. on AES, 1991, 27( 2): 255.260.[15]Watts S. Radar detection prediction in sea clutter using the compound K-distribution model. IEE Proc.-F, 1985, 132(7): 613.620.
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出版歷程
  • 收稿日期:  2004-03-12
  • 修回日期:  2005-10-24
  • 刊出日期:  2006-02-19

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