In this work, we propose two adaptive receivers achieving enhanced range estimation capability through a joint exploitation of the oversampling and the spillover of target energy in adjacent range samples. To this end, a proper discrete-time model for the received signal is introduced. Then, the generalized likelihood ratio test (GLRT) and the so-called two-step GLRT are derived and assessed. The performance analysis, conducted using both simulated data and real recorded datasets, is aimed at assessing the effectiveness of proposed solutions, also in comparison with existing detectors sharing range estimation capabilities. The illustrative examples highlight that better detection performance and increased range estimation accuracy can be achieved by exploiting the oversampling at the price of an additional processing cost.
Radar Detection and Range Estimation Using Oversampled Data
Aubry A;
2015
Abstract
In this work, we propose two adaptive receivers achieving enhanced range estimation capability through a joint exploitation of the oversampling and the spillover of target energy in adjacent range samples. To this end, a proper discrete-time model for the received signal is introduced. Then, the generalized likelihood ratio test (GLRT) and the so-called two-step GLRT are derived and assessed. The performance analysis, conducted using both simulated data and real recorded datasets, is aimed at assessing the effectiveness of proposed solutions, also in comparison with existing detectors sharing range estimation capabilities. The illustrative examples highlight that better detection performance and increased range estimation accuracy can be achieved by exploiting the oversampling at the price of an additional processing cost.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.