Two novel adaptive distributed target detectors, the range frequency domain-Rao (RFD-Rao) and range frequency domain-Wald (RFD-Wald) tests are proposed in this work. The application methods for these tests consider a ...Two novel adaptive distributed target detectors, the range frequency domain-Rao (RFD-Rao) and range frequency domain-Wald (RFD-Wald) tests are proposed in this work. The application methods for these tests consider a partially homogeneous disturbance environment and a target range walking effect in a coherent processing interval (CPI). The asymptotic performance of the detectors is analyzed, and the constant false alarm rate (CFAR) properties with respect to the clutter covariance matrix and power level are shown. The performances of the proposed adaptive detectors are assessed through Monte-Carlo simulations, and the results are presented to demonstrate the effectiveness of the proposed detection algorithms compared to those of similar existing detectors.展开更多
This paper deals with subspace detection for rangespread target in non-homogeneous clutter with unknown covariance matrix where structured interference is presented in the received data.Through exploiting the persymme...This paper deals with subspace detection for rangespread target in non-homogeneous clutter with unknown covariance matrix where structured interference is presented in the received data.Through exploiting the persymmetry of the clutter covariance matrix,we propose two adaptive target detectors,which are referred to as persymmetric subspace Rao to suppress interference and persymmetric subspace Wald to suppress interference("PS-Rao-I"and"PS-Wald-I"),respectively.The persymmetry-based design brings in the advantage of easy implementation for small training sample support.The signal flow analysis of the two detectors shows that the PS-Rao-I rejects interference and integrates signals successively through separated matrix projection,while the PS-Wald-I jointly achieves interference elimination and signal combination via oblique projection.In addition,both detectors are shown to be constant false alarm rate detectors,significantly improving the detection performance with other competing detectors under the condition of limited training.展开更多
基金Project(61771367)supported by the National Natural Science Foundation of China
文摘Two novel adaptive distributed target detectors, the range frequency domain-Rao (RFD-Rao) and range frequency domain-Wald (RFD-Wald) tests are proposed in this work. The application methods for these tests consider a partially homogeneous disturbance environment and a target range walking effect in a coherent processing interval (CPI). The asymptotic performance of the detectors is analyzed, and the constant false alarm rate (CFAR) properties with respect to the clutter covariance matrix and power level are shown. The performances of the proposed adaptive detectors are assessed through Monte-Carlo simulations, and the results are presented to demonstrate the effectiveness of the proposed detection algorithms compared to those of similar existing detectors.
基金supported by the National Natural Science Foundation of China(61901467,61701370)the Aeronautical Foundation of China(20180181001)+2 种基金China Postdoctoral Science Foundation(2019M653561,2020T130493)the Aerospace Science and Technology Fund(SAST2018-098)the National Defense Science and Technology Foundation of China(2019-JCJQ-JJ-060)。
文摘This paper deals with subspace detection for rangespread target in non-homogeneous clutter with unknown covariance matrix where structured interference is presented in the received data.Through exploiting the persymmetry of the clutter covariance matrix,we propose two adaptive target detectors,which are referred to as persymmetric subspace Rao to suppress interference and persymmetric subspace Wald to suppress interference("PS-Rao-I"and"PS-Wald-I"),respectively.The persymmetry-based design brings in the advantage of easy implementation for small training sample support.The signal flow analysis of the two detectors shows that the PS-Rao-I rejects interference and integrates signals successively through separated matrix projection,while the PS-Wald-I jointly achieves interference elimination and signal combination via oblique projection.In addition,both detectors are shown to be constant false alarm rate detectors,significantly improving the detection performance with other competing detectors under the condition of limited training.
