一种改进的自适应匹配滤波方法
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摘要
针对雷达目标检测中由于训练数据缺失导致传统自适应检测方法的检测性能下降的问题,提出一种改进的自适应匹配滤波方法.该方法首先将杂波用自回归过程表示;然后假设自回归参数已知,推导出广义似然比检验表达式;最后将采用训练数据估计得到的自回归参数的最大似然估计值代入广义似然比检验表达式中,代替已知的自回归参数.仿真实验结果表明,与传统的自适应方法相比,这种方法能在训练数据不足时提高检测性能.当雷达回波数目较大时,这种方法的检测性能接近理想的匹配滤波方法.
In order to overcome the detection degradation for the conventional detectors in the limitedtraining environment,a modified adaptive matched filter is proposed by modeling the disturbance as an autoregressive process with unknown parameters.The detector is derived by resorting to a two-step design procedure:first derive the generalized likelihood ratio test under the assumption that the parameters of the autoregressive process are known,and then,the maximum likelihood estimates of the parameters,based on the training data,are substituted in place of the true parameters into the test.The detection performance of the new receiver shows that the proposed receiver can lead to a noticeable performance improvement over the conventional adaptive matched filter.For a moderate size of radar echoes,the proposed detector performs close to the optimum matched filter even in the limited-training environment.
In order to overcome the detection degradation for the conventional detectors in the limitedtraining environment,a modified adaptive matched filter is proposed by modeling the disturbance as an autoregressive process with unknown parameters.The detector is derived by resorting to a two-step design procedure:first derive the generalized likelihood ratio test under the assumption that the parameters of the autoregressive process are known,and then,the maximum likelihood estimates of the parameters,based on the training data,are substituted in place of the true parameters into the test.The detection performance of the new receiver shows that the proposed receiver can lead to a noticeable performance improvement over the conventional adaptive matched filter.For a moderate size of radar echoes,the proposed detector performs close to the optimum matched filter even in the limited-training environment.
引文
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[2]ROBEY F C,FUHRMANN D R,KELLY E J,et al.A CFAR Adaptive Matched Filter Detector[J].IEEE Transactions on Aerospace and Electronic Systems,1992,28(1):208-216.
[3]de MAIO A.Rao Test for Adaptive Detection in Gaussian Interference with Unknown Covariance Matrix[J].IEEE Transactions on Signal Processing,2007,55(7):3577-3584.
[4]de MAIO A.A New Derivation of the Adaptive Matched Filter[J].IEEE Signal Processing Letters,2004,11(10):792-793.
[5]KRAUT S,SCHARF L L.CFAR Adaptive Subspace Detector is a Scale-invariant GLRT[J].IEEE Transactions on Signal Processing,1999,47(9):2538-2541.
[6]PULSONE N B,RADER C M.Adaptive Beamformer Orthogonal Rejection Test[J].IEEE Transactions on Signal Processing,2001,49(3):521-529.
[7]REED I S,MALLETT J D,BRENNAN L E.Rapid Convergence Rate in Adaptive Arrays[J].IEEE Transactions on Aerospace and Electronic Systems,1974,10(6):853-863.
[8]周宇,张林让,刘楠.贝叶斯雷达自适应检测算法研究[J].西安电子科技大学学报,2012,39(1):36-42.ZHOU Yu,ZHANG Linrang,LIU Nan.Research on Bayesian Radar Adaptive Detection[J].Journal of Xidian University,2012,39(1):36-42.
[9]高永婵,廖桂生,朱圣棋.复合高斯噪声中知识辅助的贝叶斯Rao检测方法[J].西安电子科技大学学报,2013,40(6):46-51.GAO Yongchan,LIAO Guisheng,ZHU Shengqi.Knowledge-aided Bayesian Rao Detection Approach in Compound Gaussian Noise[J].Journal of Xidian University,2013,40(6):46-51.
[10]BOWYER D E,RAJASEKARAN P K,GEBHART W W.Adaptive Clutter Filtering Using Autoregressive Spectral Estimation[J].IEEE Transactions on Aerospace and Electronic Systems,1979,15(4):538-546.
[11]KAY S M.Asymptotically Optimal Detection in Unknown Colored Noise via Autoregressive Modeling[J].IEEE Transactions on Acoustics,Speech,and Signal Processing,1983,31(4):927-940.
[12]SHEIKHI A,NAYEBI M M,AREF M R.Adaptive Detection Algorithm for Radar Signals in Autoregressive Interference[J].IEE Proceedings:Radar,Sonar and Navigation,1998,145(5):309-314.
[13]ALFANO G,de MAIO A,FARINA A.Model-based Adaptive Detection of Range-spread Targets[J].IEE Proceedings:Radar,Sonar and Navigation,2004,151(1):2-10.
[14]WANG P,WANG Z,LI H B,et al.Knowledge-aided Parametric Adaptive Matched Filter with Automatic Combining for Covariance Estimation[J].IEEE Transactions on Signal Processing,2014,62(18):4713-4722.
[15]BOUKABAA T,ZOUBIRB A M,BERKANIA D.Parametric Detection in Non-stationary Correlated Clutter Using a Sequential Approach[J].Digital Signal Processing:a Review Journal,2015,36(C):69-81.
[16]GAO Y C,LIAO G S,ZHU S Q,et al.Generalised Persymmetric Parametric Adaptive Coherence Estimator for Multichannel Adaptive Signal Detection[J].IET Radar,Sonar and Navigation,2015,9(5):550-558.
[17]HAYKIN S S,STEINHARDT A.Adaptive Radar Detection and Estimation[M].New York:Wiley-Interscience,1992.
[18]LI J,HALDER B,STOICA P,et al.Computationally Efficient Angle Estimation for Signals with Known Waveforms[J].IEEE Transactions on Signal Processing,1995,43(9):2154-2163.