Simultaneous Radar Detection and Constrained Target Angle Estimation via Dinkelbach Algorithm

Simultaneous target detection and angle estimation with a multichannel phased array radar system is addressed in this paper. Starting from a linearized expression for the array steering vector around the beam pointing direction, the problem is cast as a composite binary hypothesis test where the unknowns, under the alternative hypothesis, include the target direction cosines displacements with respect to the array nominal steering. The problem is handled via the Generalized Likelihood Ratio (GLR) criterion where a decision statistic leveraging the Maximum Likelihood Estimates (MLEs) of the parameters is compared to a detection threshold. If crossed, target presence is declared and MLEs of the aforementioned displacements directly provide target angular position with respect to the pointing direction. From the analytic point of view ML estimation requires the solution of a constrained fractional quadratic optimization problem whose optimal solution can be found via Dinkelbach's algorithm. The analysis of the proposed architecture is developed in terms of detection performance and angular estimation accuracy also in comparison with some counterparts available in open literature and benchmark limits.