Adaptive Detectors For Multichannel Signals In Non-ideal Environment

Adaptive detection for multichannel radar signals is one of the key problems in the field of signal processing.Most of the previous signal detection theories are established under ideal environment.However,with the emergence of the Air Early Warning(AEW),the environment for radar detection becomes complex and variable,and the multichannel signal detection is also facing new challenges.In this paper,multichannel signal detection problems are mainly studied in terms of non-homogeneity environment,signal mismatch,unknown jamming,and insufficient secondary data.The main contributions to this paper are listed below:1.The problem of adaptive subspace signal detection in a type of structure non-homogeneity environment is considered,and a detector based on 2S-Rao test is proposed.To overcome the problem of structure non-homogeneity environment with unknown jamming.Firstly,we assume the jamming belongs to a subspace which is orthogonal to the signal subspace in the stage of detector design.Moreover,resorting to the criterion of 2S-Rao test,an adaptive detector is devised.Finally,numerical experiments show that the proposed detector can provide better detection performance than other detectors both in the situations where the detector designed and other non-homogeneous environment.2.In order to deal with the adaptive detection for subspace distributed target in homogeneous environment(HE)and partially homogeneous environment(PHE),detectors based on Gradient test is proposed.Comparing with other detectors which based on GLRT test,Rao test,and Wald test,the detectors we proposed in the case of specific parameters have superiority than competitors both in the HE and PHE.Moreover,when the detection targets are point-like targets,the proposed Gradient-based detector will degenerate into GLRT-based detector.In addition,we have proofed the CFAR property of the Gradient-based detector for HE.3.The problem of detecting distributed target for the situation of signal mismatch happens is investigated,and for which a tunable detector is proposed.When signal mismatch happens,the actual signal steering vector is not aligned with the nominal one which is assumed by radar system.Within this framework,we propose a tunable detector which can adjust its directivity(robustness or selectivity)flexibly and effectively by changing a tunable parameter.Moreover,this tunable detector encompasses the generalized Kelly's generalized likelihood ratio test(GKGLRT)and the generalized adaptive matched filter(GAMF)as its two special cases.Finally,to test the effectiveness of this detector,the real data received by the IPIX radar are used for experiments.The results illustrate the superiority of the proposed detector both in simulation environment and realistic environment.4.The problem of detecting a distributed target embedded in subspace interference and Gaussian noise is investigated,and some detectors based on Wald test and two-step Wald test(2S-Wald)are proposed.The target signal and interference are assumed to lie in two linearly independent subspaces,but with unknown coordinates.To estimate the unknown covariance matrix of Gaussian noise,a set of secondary data,free of signal components,is assumed to be available.Under the above assumptions,we proposed two adaptive detectors resorting to the criterion of Wald test both in homogeneous environment(HE)and partially homogeneous environment(PHE).Performance assessment indicates that the two proposed detectors can provide better detection performance than existing detectors in some scenarios.5.The problem of detecting a distributed target in the limited-training environment is investigated,and three adaptive detectors are proposed.Since the working environment for radar are non-homogeneous,the training data are usually deficient,which will degrade the detection performance of the conventional detectors.To overcome this problem,we combine the diagonal loading(DL)technic and principal component analysis(PCA)technic into three adaptive detectors.Simulation results demonstrate that the proposed detectors achieve a detection performance improvement over the conventional detectors.