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Adaptive radar detection and estimation schemes are often based on the independence of the training data used for building estimators and detectors. This paper relaxes this constraint and deals with the non-trivial problem of deriving detection and estimation schemes for joint spatial and temporal correlated radar measurements. In order to estimate these two joint correlation matrices, we propose...
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...
Target detection is one of important roles of radar systems. In this paper, we present a detection method using total correlation based on information theory for noise radar systems which enables a system detects multiple targets at low signal to noise ratio regimes. The proposed method utilizes the largest eigenvalue of the sample covariance matrix to extract information from replica of the transmitted...
Multiple-input multiple-output (MIMO) radars utilize various sources of diversity to improve the performance of the radar. A MIMO radar in which angular diversity is achieved by using widely distributed antennas has been proposed to reduce the impact of the fluctuations of the target radar cross-section. This type of system is also known as the statistical MIMO radar. Typically, it has been assumed...
The problem of adaptive CFAR detection of a pulse-to-pulse partially correlated target with 2 K degrees of freedom in a pulse-to-pulse partially Rayleigh correlated clutter and multiple target situations is addressed. The target and the clutter covariance matrices are modeled as first-order Markov processes. The probability of detection for the mean level (ML) detector is shown to be sensitive to...
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