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GLRT Detection of Nonfluctuating Targets in Background Noise Using Phased Arrays

Abstract:

This work assesses the performance of a phased array radar working in background noise. To do so, we consider the presence of a nonfluctuating target embedded in complex white Gaussian noise (CWGN), in which the amplitude of the target echo and the noise power are assumed to be unknown. Making use of the generalized likelihood ratio test (GLRT), we design and analyze a detector based on the phased-Array front end. We obtain exact closed-form expressions for the probability density functions (PDFs) corresponding to the detection statistics. In addition, we derive a fast convergent series for the probability of detection (PD). The derived series presents a low computational cost while maintaining a tractable and efficient solution. Numerical results and Monte Carlo simulations corroborate the validity of our expressions. The performance of the proposed detector is also compared with the idealized Neyman-Pearson (NP) detector to quantify the practical losses in terms of the signal-To-noise ratio (SNR).