UNIFORM RECTANGULAR ARRAY RADAR OPTIMIZATION FOR EFFICIENT AND ACCURATE ESTIMATION OF TARGET PARAMETERS
Keywords:phased array radar, uniform rectangular array, surveyed area, target, detection threshold, accuracy
Background. If the intensity of moving targets within a surveyed area is low, some sensors of the uniform rectangular array (URA) radar can be (symmetrically) turned off. However, this does not guarantee detection of any target because sometimes the threshold detection, by which the main parameters of the target are estimated, fails.
Objective. In order to improve detection of ground-surface targets, the goal is to find an optimal number of URA radar sensors along with improving the stage of threshold detection. The criterion is to determine such a minimum of these sensors at which the main parameters of the target are accurately estimated. In addition, the threshold detection is to be modified so that a number of detection fails would be lesser.
Methods. To achieve the said goal, the URA radar is simulated to detect a single target. The simulation is configured and carried out by using MATLAB® R2021b Phased Array System ToolboxTM functions based on a model of the monostatic radar.
Results. There is a set of quasioptimal URA sizes included minimally-sized and maximally-sized URAs. The best decision is to use, at the first stage, the minimally-sized URA (by turning off the maximal number of vertical and horizontal sensors). If the detection fails, then the maximally-sized URA radar is tried. If the detection fails again, the next minimally-sized URA is tried, in which one horizontal sensor is additionally turned on. Additional horizontal sensors must be enabled while the detection fails but the number of vertical sensors should not be greater by about a third of their minimal number.
Conclusions. An optimal number of URA radar sensors is in either the minimally-sized URA (or close to it) or maximally-sized URA (or close to it). The URA size is regulated by (symmetrically) turning off vertical and horizontal sensors. The threshold detection stage is modified so that the threshold is gradually decreased while the detection fails. This allows increasing a number of detected targets on average, which is equivalent to increasing the probability of detection.
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